​Experiment by experiment, the company is weaving aircraft, ground vehicles, satellites, and the rest into a network that will someday give commanders unprecedented decision-support options.

The Pentagon’s efforts to digitally connect everything on the battlefield has a big challenge to overcome: getting disparate vehicles and weapons to share data. 

“The interoperability of various, different systems, that’s really where we are struggling. We don’t have that machine to machine connection to begin with.”

Over the past several years, we’ve been working to build those connections, piece by piece and plane by plane. We started by asking, “How would we go fight in 2030, 2045?” and then working backwards.

There are efforts underway to link the stealthy F-22 and F-35 combat jets. The Air Force has announced that they are to test a similar link next month, but the Air Force is establishing more complete linkages, including new forms of secure radio linkages using software defined radio, and also including other assets such as drones. 

Experiment by experiment, we tried to “systematically work” to build the components of a  larger network of networks.

Ultimately, we want all this to add up to a “virtualized cloud-based architecture like the branches of a tree. A handful of ships and planes might form one network. That will, in turn, connect to a larger network that would, in turn, would be connected to the larger network

 “You end up with virtual networks on the edge with a computing architecture you could have on an aircraft, on a ship, or any of the deployed nodes..  

Bringing all these pieces together will enable a new sort of operating system for warfare, a new experimental battle management display to illustrate the concept.

The system presents the operator with a list of effects, from devastating explosions to a quiet disabling of some enemy system; a list of available assets, including planes or drones; a map of targets; and recommendations for the best way to deliver effects to targets. 

As circumstances change — fuel gets low, ammunition is depleted, targets are destroyed, new enemy forces arrive, etc. — the system can send out alerts that a new plan is needed — or automatically update the plan with new instructions for pilots and drone operators. It all depends on how high the operator wants to set the autonomy.

That vision is very different from the way mission tasking works today. “Right now, our commanders are very limited in who they can assign to do certain” things. “More often than not, you have to assign someone because they happen to be in front of a specific place in front of a specific computer. 

Of course, realtime data sharing across platforms isn’t a simple or clear-cut affair, even after successful experimentation. It’s hard to simply to share data between operators and just one platform. The challenges of sharing data between multiple platforms, in the middle of battle in a highly contested airspace, are far larger.

Navy is making integration of ships, planes, sensors and weapons a priority going forward and is in the requirements-writing stage of development an integrated combat system. Today’s ability to pass information from sensors to operators at sea to fleet commanders ashore is not happening “at the speed of warfare.”

“It’s every ship, it’s every radar, it’s every airplane, it’s every weapon. And if we don’t optimize every one of them, the margin of victory is so slim right now we risk defeat. That’s how we approached strike group command, and that’s how we are approaching the push to develop the requirements for an integrated combat system.”

“We have to have the ability for that operator, when he looks at that track, to have confidence – whether it’s coming from an unmanned vehicle 200 miles away – that it’s the same thing they’re seeing on a cruiser, the same thing they’re seeing on Control Channels, the same thing that’s displayed in the Maritime Ops Center.”

All those leaders, from the cruiser to the strike group to the fleet commander, should also have a level of awareness that extends to what sensor is doing the tracking and therefore what its limitations might be; and what weapon is most appropriate to go after the threat, so it’s effective but not wasting a costly high-end weapon to defeat a less-capable target.

While leaders at sea might have access to this information, those at the Maritime Operations Center ashore see a lag in getting those details. We want everyone at all levels to have access to the same information in real time “so we can make good, sensible decisions and employ our weapons wisely against the threat. Or not react at all, if that’s the most prudent case, depending on the mission.”

“We should be able to, with this level of technology, to take what we are seeing on the carrier should be available in the operations center in real time so that when a fleet commander is told, ‘these are my intentions and I’m engaging here,, they can look at it and go, absolutely, and I’m moving this or that or whatever the case may be to support you.

“We deserve better information to the decision-maker. The information is there, somewhere; we’re just not getting it in the right hands at the right speed.”

A run-through of “what we need to win” includes the amphibious force, the submarine force, mine warfare and mine countermeasures communities, combat logistics and more. While much effort has been put into creating and strengthening the Naval Integrated Fire Control-Counter Air structure for the carrier strike group force, other communities in the Navy have been left out of previous efforts.

“We are going to do things differently, we are going to do things in a completely netted environment. … We have the weaponry to go a lot farther than we’re able to do because of the sensors.

Priorities include long-range targeting, which will require these netted sensors; a universal common operating picture and combat logistics.

Air Force is preparing an experiment it hopes will link the F-22 and F-35 fighter jets, the first in a series of experiments dubbed “connect-a-thons.”

The goal is to identify a fleet of aircraft with a communications issue, invite voices from inside and outside the Pentagon to offer solutions, and then test those offerings in a live experiment.

The F-22 was built with an older data link that can’t match up with the Multifunction Advanced Data Link system used on the newer F-35; while the F-35 can receive data , it can’t share the data back — a key capability given the envisioned role of the F-35 as a major sensor for the future Air Force.

For the test, the service will use a “universal translator” for the two jets. The first test, will feature the equipment on a pole on a test range, with the jets pinging their information back and forth from that fixed location.

It’s not the first time a drone has been used as a link between the two fighters. Global Hawk unmanned system, equipped with a new radio has been designed to act as a translator between the aircraft.

A cloud-based common operational picture that tracks where friendly forces are and displays a map of their constantly updated positions.

Why is this so difficult? As stealth aircraft whose whole raison d’être is to evade detection, the F-22 and F-35 would rather not use conventional radios to communicate in combat because the transmissions are too easy for an enemy to pick up. 

So both jets use so-called Low Probability of Detection/Low Probability of Interception communications – but they each use different ones that operate on different frequencies with incompatible software. F-22s use a unique Intra-Flight Data Link that works only with other F-22s, while the newer F-35s use the Multifunction Advanced Data Link , which can only talk to other F-35s.

The goal is to get something that works well enough to test in real-world conditions and get feedback from real pilots. Then you take that data and improve your solution and run the improved version through another test- then rinse and repeat until you get something good enough to field to actual combat forces.

We have product categories that we care a lot about. We want to be able to integrate sensors. We want to get data off of them. We want to secure the process. We want to be able to put applications on the system and connect capability and people together. And we want to output an effect, like  jamming a radar, to hacking a network, to blowing everything up.

The system features new methods of data sharing between air and ground forces, a common operational view that can track updated positions, and most prominently, a data connection to allow F-22s and F-35s to share data without exposing their positions.

The F-35 was designed to take in large amounts of data regarding battlefield positions and situations. The F-22 has a more limited mission and capability -- and the F-22's Intra-Flight Data Link and the F-35's Multifunction Advanced Data Link are currently incompatible.

The fighter planes, and other platforms, have different communications protocols and radio frequencies, and were not designed with a digital gateway to integrate their communications capabilities.

"The main point is that we want both the F-22 and the F-35 to be able to share communication over a link that allows them to do so in a way that protects their survivability."

Imagine a network of manned and unmanned systems, with relatively expendable drones actively emitting signals while the rest of the force stays silent, stealthy, and survivable. Imagine a multi-domain command and control network that can pull together forces from air, land, sea, networks reorganizing as needed on the fly. The goal: create a dispersed, flexible force our adversaries’ centralized systems can’t keep up with.

How would that work? A commander inputs the task the force needs to do, identifies the units to be made available for tasking, enters some constraints like geographic bounds, timing, etc., and the system comes back with some proposed courses of action. To develop the courses of action, the system runs an auction across all the units available to determine which can best accomplish the tasking like match passenger’s desired pickup points and destinations with available drivers, in seconds, millions of times a day.

Of course, the artificial intelligence driving this kind of Joint All-Domain Command & Control system would be complex, distinguishing between ride type and it would need to know the capabilities of different types of drones, planes, ships, ground vehicles, satellites, and more.

Then it needs to calculate which was best able to do a mission based on both its inherent capabilities and its current location. Instead of just knowing where to drop off a passenger, it would need to figure out the best kind of bomb to drop, or jamming to conduct, or network toodto deploy, against a wide variety of targets.

Traditional  military organization is like a jigsaw puzzle, where every piece can fit in one and only one place in the larger picture; the future organization needs to be like a mosaic, where a set of tiny building blocks can be combined in all sorts of ways to make an infinite variety of images.

This kind of networked force could survive enemy attack – physical destruction, hacking, or jamming – by reorganizing itself to pass data around the damaged nodes, making  it difficult for adversaries to knock out by jamming a few key links or physically destroying major headquarters, bases, ships, and satellites.

“The tools available to field commanders are insufficient to enable them to develop and plan creative operations. As a result, commanders, particularly junior ones who lack large planning staffs, will tend to fall back on doctrine, habits, and traditions that the enemy can predict.” We heed to enable leaders up and down the chain of command to creatively plan, adapt, and recompose their forces and operations.”

These new tools would help commanders rapidly retask and reorganize a new kind of force. Instead of relying on large, powerful aircraft that can do all aspects of an electronic warfare mission alone by themselves – which simplifies both US planning and the enemy’s countermeasures – the future force would disaggregate capabilities across multiple manned and unmanned platforms. 

Expendable drones might emit radar signals, while other drones and manned systems would passively receive the radar returns, then compare notes over hard-to-detect datalinks to figure out where the enemy forces were. Other expendable drones – possibly launched from a manned mothership — could transmit the powerful signals required for jamming, but every unit in the network would have the capacity to passively listen for enemy transmissions.

1. Saved Money

Automation cuts down on the amount of labor your business needs and the number of mistakes you make, which themselves turn into more labor. For example, if you have a customer service policy that allows customers to keep an incorrect product that you sent by mistake, a growing error rate can be very costly.

2. Saved Time

It takes far less time for computers to do data entry. While your human employees are sleeping, you can run jobs in the middle of the night so that they're ready when people arrive in the morning. By handling a larger workload, you can do things in advance instead of just in time. If an order comes in on a Monday and needs to be out on Wednesday, automation can often help you get it sent by Tuesday, helping your business to perform beyond its previous limits.

3. Customer Satisfaction with Product

By reducing the number of errors you commit, automation helps your final output be better. In addition, providing automation-enabled features, such as self-service and faster turnaround time, makes your customers want to come back to do business with you.

Automation doesn't just bring benefits on your side of the equation; it can also make your customers happier too. For example, if you run an e-commerce site, your customers can log into a self-service portal containing their order histories. Once you've entered the tracking number into your system, your customers can view exactly where their orders are in the process, without having to email or call customer service.

4. Happier Staff

Tedious and repetitive tasks are the bane of every worker's existence. By automating these activities, you can free up your employees from spending too much time on lower-level functions and let them better apply their knowledge. In doing so, they can learn new facets of the business and you'll develop more well-rounded employees. Automation make your staff smarter and help you find and retain the right people in the first place by improving your hiring processes and internal workflows.

5. Improved Control and Visibility

Having visibility into and oversight of manual processes is difficult because you can't always see how far your employees have progressed with a certain task. As such, one of the major benefits of automation is predictability and control: you know exactly how your processes are being executed every time. In addition, automation is often able to consolidate processes by reducing the number of steps involved, decreasing the complexity.

6. Improved Quality and Reduced Errors

If you're using manual processes, errors are nearly inevitable. What's more, the greater number of humans involved in the process, the greater the chances that mistakes will be introduced, especially with tedious tasks like data entry. Automating your processes gives you consistency: the knowledge that as long as you've set up the system correctly, you'll always get back the right results.

7. Improved Measurement Ability

Automation gives you more data, which means it's easier to measure all sorts of metrics and key performance indicators about your processes. For example, if you know you can ship a certain number of orders during a single day or hour, you can use that as a baseline for your future forecasts. You can also more easily find problems and shortcomings. If you know there's a bottleneck in a given process and you've already automated two steps, it's easier to find the bottleneck in the remaining manual parts.

8. Improved Communication

There are two ways automation can improve communication: between technologies and between people. First, an expert automation partner can help you connect two completely independent systems and have them start talking to each other and working together relatively seamlessly. Second, automation can connect you better with your clients by providing information, such as order and shipping status, so they're kept up-to-date at all times.

9. Improved Ability to Scale and Grow

Too many businesses struggle to scale their manual processes under the weight of increased growth. By helping to shoulder a good deal of the workload, automation can help you become more productive and efficient without having to hire additional workers. The more quickly and correctly you can complete business-critical processes, such as ordering and customer service, the better prepared you'll be to scale your business.

10. Improved Compliance and Security

As mentioned above, automation gives you more predictability and visibility into the results of a process, which are extremely important for compliance reasons. Automating your processes helps you be certain you're following a given compliance framework. In addition, by automating a given process, you're exposing any sensitive information to fewer human eyes, helping you keep this data more secure.

​The purpose of a wingman was established to provide mutual support within a formation, protect the flight lead and provide pilot with the additional capacity to manage the formation, operate the aircraft, and make decisions.
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The most important tasks for the wingman were to help avoid an attack by an unseen enemy, contribute to the formation’s situational awareness, and watch out for obvious signs the leader had either missed something or made an error. At the very heart of the idea was an acceptance that the pilot is fallible and, in the heat of battle, task saturation was likely to result in mistakes and errors in tactical decision-making.

In the early years of aviation, a wingman would be positioned slightly behind the lead aircraft in close visual proximity to the wings of the leader. But as advances in technology introduced new inter and intra-flight data links and increased levels of integration with airborne early warning/control systems, formations became invariably separated beyond visual range of each other and able to benefit from shared situational awareness.

There are, of course, still times when a wingman is required to be in close visual range, but these are becoming more suited to non-tactical reasons such as transits through controlled airspace or through poor weather conditions.

So what started out as a role providing visual lookout support has now been transformed by the introduction of multi-sensor fusion displays and data links, with mutual support by proximity now measured in miles rather than metres. The fundamental purpose of a wingman has changed over the years from supporting and protecting the leader, to one which is focused on the greater concentration of firepower and more effective application and multiplication of force.

Yet perhaps the most transformational aspect of the evolving wingman role is that of the unmanned ‘Loyal Wingman’, a wingman that does as it is told and does not get distracted by the fear and chaos of battle.

The manned-unmanned narrative is now sensibly shifting towards “and” rather than “or”.  Manned and unmanned teaming is a powerful concept which leverages the strengths and mitigates the weakness of each platform and concentrates the mind on the important operational aspects, such as imaginative new roles and the challenges of integration.

It should come as no surprise, then, to see the expansion of the loyal wingman concept in recent times into the other warfighting domains.

Recent developments in unmanned surface and sub-surface combatants are opening new ways of warfighting and creating opportunities to reconceptualise joint operations and move away from the platform-on-platform engagements which have traditionally characterised the battlespace.

The new unmanned platforms are expected to carry a range of sensors and weapon systems almost certainly configured for anti-surface warfare and maritime strike. Yet the potential for broader counter-air missions set within the cooperative engagement framework opens up new possibilities and significantly leverages existing manned surface fleet capability as well as providing a means of enabling integrated fire control, with the air layer containing E-2D Hawkeye, F-35C, F/A-18F Super Hornets and EA-18G Growlers.

The distributed architecture will require a complex web of advanced datalinks and communication systems to make it operate as a combat system. Designing and building this ‘kill web’ so that it can enable the delivery of manned-unmanned firepower across domains will be a huge challenge not least due to the laws of physics.

And then the ability to train, test, evaluate and validate tactics and procedures will add a whole new level of complexity to generate the ‘trusted autonomy’ required for warfighting. And that is exactly why we should do it.

Now robots understand verbal instructions, carry out a task, and report back. The potential rewards are tremendous. A robot that can understand commands and has a degree of machine intelligence would one day be able to go ahead of troops and check for ambushes. It could also reduce the number of human soldiers needed on the ground.

Soldiers will soon use VR technology widely to train for such experiences as jumping from an airplane. You can create a virtual reality of the exact environment you would be in and it’s extremely realistic. so you don’t have to go through the stress and expense of getting on the plane and learning exactly where to put your hands on the door. 

Virtual reality enables you to practice time after time and get better at it. Soldiers in a recent VR session found digital jump training so realistic they automatically assumed the jump position and “reached out where they needed to put their hands.”

The new techniques won’t stop with training. Troops in the field already “receive information on enemy location, friendly location, targeting – all things to absorb and react to.
 
We are putting real-time input from different sources into one package. “What we’ve done is basically put a digital wrapper around the soldier that allows them to take different inputs.  "We can interchange sensors, algorithms and it becomes plug and play.”

Every time a parachute unit hits the ground, it shatters. A well-ordered formation breaks apart into individuals, strewn across the landscape and unsure of where their comrades and commanders have landed. Leaders race to reform a fighting force before the enemy can pick the scattered paratroopers off.

Now we are testing to see how much faster could that force form up and move out if paratroopers could see each others’ locations in real time on a digital map. What new tactics would become possible?

Yes, drones, satellites, and datalinks have dramatically improved the amount of information available today to static command posts and troops in vehicles. But more advanced communications systems have been too bulky and too hungry for electricity for paratroopers, still relying on backpack push-to-talk radios. “It hasn’t changed much for the dismounted infantryman. It was more like wrestling in the dark when you don’t really know where your hands and your feet are all the time.”

With the new network available  to leaders at every level down to the four-man fire team, “that commander at all times knows exactly where his hands and his feet are. We’ll eventually get to the point with the smart goggles now in testing that will go to every infantry soldier – “where we know all the fingers and toes are too.”

Do commanders really need to know the location of every private? “In the chaos of an airborne assault, commanders actually do care about where individuals are.. Today, for instance, we can’t call in artillery or airstrikes too close to the landing zone for fear they’ll hit stray paratroopers he hasn’t accounted for yet. With goggles on every soldier, calls could be put in in heavy firepower in even in the first critical, vulnerable minutes after hitting the ground and not have to worry about friendly fire.

“Right now, we try to jump consolidated-  put as many members of this brigade on a single piece of terrain as possible.” In other words, you drop the entire brigade in the same location to make it easier to link up. But if you’re already linked virtually as soon as you hit the ground, you can be spread out.”

Instead of one big drop from lots of vulnerable transport aircraft, which require blasting a wide path through enemy air defenses, you could do several small drops from a few planes and exploit smaller holes in the enemy defensive system. Instead of a brigade or battalion hitting the ground in one place, getting organized, and moving out against multiple objectives, you can hit each objective at once, giving the enemy less time to respond.

Even after the initial landing, the new network lets the troops spread out more without losing the ability to support each other, because it has longer range than the current FM radios. “Right now, the problem is, not how fast I can move, its can communications reach far enough?’”

Currently, the brigade has to send out specialist FM transmission teams to relay messages to keep units in contact when they’re separated by distance or radio-wave-blocking terrain like hills or buildings. Those teams have to set up on high ground to ensure unobstructed transmissions, where they then start pumping out lots of radio signals. That makes them easy for an enemy to find. And the brigade doesn’t have many retrans teams. Only battalion commanders and above have any.

By contrast, every company in the new network will get its own relay drone. Because long-range radios are bulky and power-hungry, these drones aren’t portable systems. They have to be carried on the company commander’s vehicle air-dropped in with the first wave to carry special equipment – which is also the only vehicle in a standard rifle company. 

Even in flight, the drones need an electrical cord back down to that vehicle to draw power, so they can only fly in circles, tethered to a specific location. But they don’t have to set up on high ground, since they’re effectively instant radio towers. A bulkier version of the drone, it “greatly enhanced our ability to extend our mesh network,” That meant forward units could push forward aggressively and remain in touch.

Longer range communications are even more important on the brigade level. We have a cavalry squadron, but today the commander can’t send them out very far before they are no longer able to report back, which defeats the point of doing reconnaissance. With the new network, there is the ability to push the scouts out farther, allowing them to find the enemy faster. That, in turn, gives the rest of the brigade more warning time to attack, dig in or evade.

Longer range also helps link the brigade to supporting units, like AH-64 helicopter gunships. Today, “unless they’re within FM range of one command post, they’re going to be hard for us to talk to. But with the new system a frontline platoon leader, for instance, talk to the gunship pilot “the entire time that Apache is moving through my battlespace… from the minute the wheels are up.”

Keeping the tech light is critical to a unit that moves mostly on foot. So is making it easy to use and to maintain. While the brigade has its own Forward Support Battalion, it has nowhere near the deep bench of mechanics and technicians that an armored or helicopter unit has. Adding that many personnel and all their gear would make the brigade much bulkier and slower to deploy, defeating the point of a light infantry unit.

“Is the equipment going to the right echelon? Do we have the technological capability to maintain it?” For brigade commanders, this is one of the biggest concerns, it’s one of the things they asked us to pay the most attention to. We don’t want to … have to give the rifle platoon a vehicle and a trailer and a generator.”

We don’t want paratroopers to become dependent on technology, not when hacking, jamming and ordinary breakdowns can take it away.

“In everything we do, we have to take into consideration what happens when that technological advantage is denied to us, for whatever reason. That means training in “basic skills” like using map, compass, and human contact.

“But even with these big advances, the infantry’s a hands-on business. “Sometimes you just need to put your hand on somebody’s shoulder and have a conversation eye to eye.

With the next generation of network technology expected to become more widespread, we are exploring how the new hardware could improve global asset management, “smart depots" and augmented or virtual reality. The technology will help with training, network security and artificial intelligence capabilities.

Advanced network technology will also allow troops to process information faster, key to developing better artificial intelligence. “In order to really use artificial intelligence you’re going to require a lot more bandwidth than we currently have.

1. Saves Time

The first and most valuable benefit Digital Process Automation provides is time-savings. Providing your employees with the right information at the right time and in the specific context will help them do their tasks more quickly and easily while reducing manual tasks. Automating many of these repetitive tasks can save hundreds, even thousands of working hours for organizations.

2. Cost Reduction

Every business faces global pressure to increase their profitability. One approach is to reduce costs. But, reducing the capabilities of the computer center negatively impacts the entire company.

Automation software is a better and more intelligent approach to cost containment and reduction. The greatest opportunity is to increase service to the customer while systematically reducing costs. Management often overlooks this potential for savings. 

3. Operational Stability

Another significant advantage of Digital Process Automation is operational stability. By following fixed guidelines, Digital Process Automation eliminates situations in which documents may be displaced, or where processing steps might be missed. This allows your employees to effortlessly provide value to clients while handling all the needed steps to ensure accuracy and security of the process.

4. Prevents Errors

Process changes  can lead to work-errors. Digital Process Automation  systems can easily adapt to these changes and eliminate risks. With updated-to-date workflows around new document templates, employees can easily follow the predetermined workflow. Such automation helps organizations avoid document processing errors because most of these errors are human errors.

5. Responds to Customer Demand

The ability of Digital Process Automation provides ability organize and digitize processes allows for easy adaptations and improvements. This enables organizations to quickly launch new solutions to scale and to adjust to the needs of the market. This ability of rapid experimentation is crucial for the success of organizations.

6. Productivity

As an organization’s technology demands grow, productivity becomes a bigger concern. Typically, as other business areas were given tools to increase their productivity and effectiveness, but network operations took a back seat. 

As people use computers more, they place greater demands on the system. More users are generating more jobs, and printed output has increased despite efforts to reduce printed reports. In spite of the trend to online transaction-oriented and client/server systems, batch workloads continue to grow. Production batch jobs still consume the majority of time, and in large shops, jobs are constantly being added.

7. Job Scheduling

Job scheduling  increases batch throughput by automating the production batch schedule. In the early days, computer throughput was limited by how fast operators could reset switches on the console not allowing idle time while waiting for the operator to release the next job. You save time and money by eliminating the lag time between jobs and minimizing operator intervention to process more work and significantly improve system use.

Once the job schedule is established, automation executes the commands precisely and in the correct sequence, eliminating operator errors. Forecasting job completion and being able to perform “what if” analyses of schedule changes benefits operations by removing much of the guesswork from daily tasks.

8. Availability

Companies are continually more reliant on networks to conduct day-to-day business like: order entry, reservations, assembly instructions, shipping orders—the list goes on. If the computer is not available, the business suffers.

High availability is clearly one network primary goals. Here too, automated operations can help. A driver may crash, but the situation becomes serious when there is not an adequate backup— or worse, the tape cannot be found. A key advantage to automation is the ability to automate your save and recovery systems to ensure protection from the potential disaster of disk loss, or inadvertent damage to system objects from human error.

9. Reliability

Productivity is an obvious benefit of automation. However, reliability is the real gem that sparkles with automation. It is the cornerstone of any good network operations. Without it you have confusion, chaos, and unhappy users. Network operations requires two opposed skill sets.

On one hand, an operations person needs highly technical skills, such as the ability to understand the complexities of an operating system and to analyze and solve problems as they arise. On the other hand, this same person has to be content pushing buttons and loading paper.

Automated operations ensure that jobs are not forgotten or run out of sequence, that prerequisite jobs are completed successfully, that the input data is correct, and that any special processing is performed.

10. Performance

Every company would like to have their enterprise perform like a thoroughbred. In reality, it is more likely to be overburdened with work. Even though advancements in computers make them faster and less expensive every year, the demands on them always catch up and eventually exceed the level of capability that a company’s computer infrastructure possesses. That leaves a lot of companies wanting to improve their system performance.

Two options to improve performance are to upgrade/purchase a newer system—both expensive choices. It’s also possible to tune a system for better performance, but this takes a highly skilled person who is not normally available 24 hours a day. And, once a system is tuned for a specific workload, if the workload changes, the settings are no longer optimum.

​As the Services push its top priorities for modernization through a collection of cross functional teams, a lot of the headline-grabbing items include longer range fires, missile defense, new helicopters, new vehicles and new rifles.

But for soldiers to use that gear best and practice round after round, they’ve got to be able to train.

Training now means more than mock squad grass drills behind the barracks. Technology is finally getting to a point where soldiers can enter a simulated world and run through combat-like scenarios on the actual terrain where they will fight, whether that’s boots on dirt, flying in the skies or firing from remote platforms.

Soldiers, Marines try out new device that puts ‘mixed reality,’ multiple functions into warfighter’s hands. The system melds navigation, targeting, situational awareness and communications into a single device with advanced thermal and night vision.

Advanced trainers have already pushed out with more on the way, including the backbone of how a multitude of soldiers, commanders and units will conduct realistic training at home station to help them prepare in ways they never before could.

Another key piece of gear with the Soldier Lethality is Integrated Visual Augmentation System, a kind of headset that ties in navigation, weapon and troop location information into one device.

Some of that will combine old items, such as the engagement skills trainer, for items such as call for fire, use of force and others, into one system with the Soldier-Squad Virtual Trainer to help a squad operate in the simulated environment together in real time.

The advantage that gives is to allow for “reps and sets” of training to be done at home station regardless of range availability.

“Train wherever you are. Set up a barracks as an entire shoot house, use a series of buildings. They’re not tied to some facility scheduled way in advance. That lets soldiers be intuitive and execute parts of their training when they need to, practicing in the terrain they’ll actually fight on.

The most pressing and promising work, though has been in developing “One World Terrain models from real world data. Processing times for the data needed to create a usable environment shrank from months or weeks down to days or hours since the team started work.

The next steps for One World Terrain include expanding the system’s database. Some of the challenges include improving latency and bandwidth so that the fidelity or realistic qualify of the terrain remains high. However, even lower fidelity versions can help with training and mission planning. 

As they continue building the individual, squad and collective trainers, training is pushing into the combined simulation to improve the decades-old gear with force-on-force laser-based shooting simulators. Also alternatives both for the engagement system that runs the shooting devices and the devices themselves.

Roll out the talking robots – or at least the artificial intelligence technologies that can manage human communication networks on the future battlefield. The unprecedented complexity of communications management in a future with exponential increases of ubiquitous information technology devices in Multi-Domain Operations needs AI solutions. 

Military must develop AI-supported assured communications management capabilities to understand and monitor network structures and their availability throughout the environment. to seamlessly integrate commercial and military communication networks to the warfighter’s devices. 

Like any adversary, the complexity of Future Operational Environments will challenge future warriors’ abilities to command and control their warfighting systems. For example, Multi Domain Operations are expected to be composed of vast formations of unmanned, robotic, and autonomous systems that depend on massive amounts of data and rapid, assured communications across the spectrum, from tactical to strategic battle areas.

Engagements in the future environment will “far exceed the reaction time of humans. Decision-making processes require much greater speed; information and intelligence…so that commanders can make decisions at increasingly rapid rates.” 

Future forces may have to operate in a communications denied environment, potentially requiring the employment of robotic and autonomous systems highlighting the importance of maintaining “assured communications and sufficient network bandwidth” as operational tempo increases with the integration of greater numbers of manned and unmanned systems. 

Despite the compelling need for AI-based capabilities, their development has been slow, potentially leading to degraded battlefield communication management, and ultimately communication gaps. AI-based innovations may reduce the warfighter’s need to pause operations for lack of communications must develop capability can monitor network status and seamlessly integrate warfighters’ communications networks and devices. 

Consider scenarios where such capabilities can enhance command and control during MDO:

A battlefield truck driver needs to give a status report to operations centers, from the strategic to the tactical support areas. What communications are available along the route? What onboard technology will feed into the report? Must the driver find a friendly command post or a commercial node to transmit his report? Is there a single channel, line-of-sight, or beyond line-of-sight option mounted to the truck? AI assured capabilities knows instantly and will automatically establish network connections, provide assured communications, and send the status report to the proper recipients.

Special operations forces and local militias engaged in a fight against a common enemy must maintain command and control in an austere environment. The signal officer must develop primary, alternate, contingency, and emergency communications options. New tools understand the interoperability and interface requirements of the available communications equipment and autonomously establishes assured communications connectivity.

Such capabilities can simultaneously support a truck driver, a signal officer, a special forces operator, and virtually every other soldier, command post, or robotic and autonomous capability on the battlefield, establishing communications with the management of two key dependencies. 

First, they seamlessly employ available commercial, private, or military communication networks for the warfighter. Second, they understand the type, capability, location, and availability of all warfighters’ organic communications assets, assigned by echelons.

A robust capability should autonomously answer three questions for communications managers: Who talks to whom and when? What talks to what and when? And what means best serve these communications requirements? 

To answer these questions, an AI-empowered system requires three intrinsic, trusted data feeds that include 1) the status of all available communications systems across the battlefield in real time; 2) an inventory of units, locations, and communications assets of all friendly forces; and 3) the permissions needed to autonomously establish services between communications systems and warfighting communications assets. With these comprehensive, ubiquitous trusts, AI assured capabilities  and its data resources provides all warfighters at echelon with communications at any time, by any available means. 

These may include the following:

Managing Access Points. AI assured capabilities  must know all potential access points for wired and wireless communications capabilities across the battlefield. Access points provide warfighters, command posts, robotic and autonomous systems with the locations and types of available communications.

Reporting Operational Status. AI assured capabilities  must know the operational status of all wired and wireless communications capabilities at each potential access point. This status identifies the quality and capacity of communications at each access point.

Mapping Routes of March and Command Post Locations. AI assured capabilities requires terrain mapping of all potential routes of march traversing a battlespace. AI assured capabilities  overlays routes of march upon access points so warfighters can readily connect to the nearest communications capability. 

The result is war fighters and command posts receive ‘on the move’ and ‘at the halt’ communications. AI assured capabilities  also requires terrain mapping of potential command post locations, to include improved buildings and unimproved field locations that can support ‘at the halt’ and fixed communications requirements. AI assured capabilities  overlays command post locations upon access points so warfighters can establish command posts at a location with the best network connectivity.

Managing All Available Communications Devices. AI assured capabilities requires a trusted awareness of all available communications capabilities by unit, with the ability to geolocate each device. This awareness of friendly force information must include all echelons of capability. From a truck with an FM radio to the four-star command post, to any number of future warfighting devices, and capability operating on the battlefield. The alignment of network connectivity with warfighter capability produces assured communications.

Providing Trusted Network Provider Access and Contracts. AI assured capabilities  requires trusted relationships communications providers to seamlessly enable leased or military services for authorized users. AI assured capabilities must automatically establish  contracts processes to rapidly establish communications connectivity for the warfighter and for other systems on the battlefield.

Providing Information Fusion. AI assured capabilities capability fuses information feeds and provides a real-time alignment of: 1) access point communications capabilities; 2) routes of march; 3) command post locations; 4) available devices by location; and, 5) automatic contracts and service provision. An AI assured capabilities system-of-systems becomes a ‘matrix’ of all available users, their organic communications capabilities, and the networks to connect them.

Who talks to whom and when? What talks to what and when? And what means best serve these communications requirements?

The result of such capability is comprehensive. From the platoon to the theater army level, and at all points in time and space on the battlefield, AI-assured communications capabilities can minimize the “the fog and friction of war” and their effects on operations..

1.  Increased Productivity

Workflow and business process automation reduces the amount of time needed to complete a task. This can result in higher productivity rates for routine tasks, with the side benefit of freeing up employees’ time to concentrate on more complex and revenue-generating activities and better customer service.

2.  Streamlined Communication

Conversations, emails, and phone calls between employees who are trying to pass on information can result in many details getting lost in translation. An automated system provides a visual and organized platform where all employees have a centralized view. Updates and documentation is recorded and managed so that all information is current. Controls are in place to prevent overlaying information and for access permissions.

3.  Reduced Time and Costs

Performing tasks manually requires a lot more time than if they were automated. This frees up your time to work on items that add genuine value to the business, allowing you to be more innovative and increasing your employees’ levels of motivation.

Expensive manual errors and inefficiencies occur where humans are involved. Automation can greatly reduce the costs associated with errors such as delayed approvals and the like. It can also save administrative labor costs.

Business process automation means that more man-hours are available to you. This means your company can have the same level of output even after reducing the human workforce. Thus, you have the chance to focus more on the quality of your employees instead of quantity. And eventually, reduce the overall cost of business operation.

4.  Improved Quality

An automated process ensures that all actions are performed identically with no room for error. Each product is produced and each service is performed consistently, without deviations. This results in higher quality products and customer service that is more reliable. The improved consistency also encourages the development of more feature-filled products with little or no increase in production time and costs.

5.  Greater Visibility

Business process automation systems include dashboards where you can view and monitor the process and see where things are at any given time. This is useful in managing deadlines and for capacity planning purposes.

6.  More Efficient Task Management

The various departments involved in any process can have access and visibility into the automated workflow with just a few clicks. No more emails or phone calls to other departments requesting status. You can set up regular monitoring and reminders within the automated system so that nothing in the process slips through the cracks.

7.  Improved Operational Stability

Business process automation systems have rigid guidelines regarding the control document and process actions. This eliminates situations where processing steps might be missed or documents misplaced. Employees need not worry about verifying accuracy of information and tasks; it’s all built in to the system. This greatly increases the dependability and reliability of the process.

8.  Greater Customer Satisfaction

Because they will receive more accurate and consistent products and services, your customers will be more satisfied. They’ll know that they can depend on you to get the job done right. Also, your customer service will be easier and more efficient. If a customer calls, you can quickly pull up all their related information without shuffling through a bunch of papers. Customers will appreciate the speed and quality of service, which will increase their trust and loyalty.

9. Better allocation of the workforce

Automating tasks allows your business to free up your workforce from many repeated actions that actually do not need that much human intervention. This enables you to reorganize your company’s structure and focus more on creative tasks and innovation.

At complex projects, monitoring every team member and ensuring proper flow of information often turns out to be a difficult task. Keeping track of project process, updating the different teams, setting goals and deadlines become a lot easier if these processes can be automated.

10. Deeper insights into the business process
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By computationally managing your business information, you can analyse and dig deeper into the data. Automating the business process thus gives you a way to gain deeper into different aspects of your business.
For example, you may want to see the number of leads that you are generating and compare that with the number of sales you have. Of course, this analysis can be done manually. But for large organisations, such manual analysis can be complex. Better insights also mean you can easily identify problems in any part of the business process, which may otherwise be invisible.

​Can DoD Get Speed/Security with new Digital Networks? The Pentagon is struggling to speed up acquisition at the same time it’s imposing new network security controls. But plans are in the works to do both.

If the Pentagon gets real-life scenarios on how Blockchain implementation can leverage DevOps practices and Modern Docker Network Solutions, it just might square the circle between accelerating acquisition and improving security.

 “There is a trade between the objective of tool development and the assurance properties that we’re trying to achieve. But there are ways to reconcile them.

Right now, DoD has the worst of both worlds. Network security certification can be so laborious and bureaucratic that tools are often obsolete before it’s finished testing. Yet the final product isn’t necessarily secure anyway, because new threats emerge faster than the Pentagon can upgrade its defenses.

So being too slow on acquisition is bad for security as well. But speeding up acquisition creates risks of its own. Getting the Pentagon to move faster doesn’t win any arms races if adversaries steal the new tech as fast as we can field it causing the erosion of the lethality of the joint force.

“We talk a lot about acquisition going faster, we have to have the speed. That’s great, it’s clearly slow and cumbersome the way it is, but let’s not get out in front of ourselves and get so ahead, so fast, that we are not considering security.”

Networking security needs to be as important as speed, not an afterthought to it. “We need to put security in our requirements and acquisition process. Until we grade people on security as well as cost, schedule, and performance, why would you go and do the extra credit work on security?”

Yes, there could still be a waiver process to skip security requirements when speed is of the essence – but it needs to be controlled at a much higher level than it is today. “Today there are far too many instances where there’s a program manager making risk decisions. In the system we’re putting together, the decisions are made at higher levels.

Centralizing decisions can certainly improve consistency and control – but it rarely speeds things up. The armed services agree they need to work together better — they just don’t agree on how. 

DevSecOps to the Rescue?

So, we asked, how do you reconcile security and speed? “The DevSecOps approach comes to the rescue.

DoD is desperately trying to play catch up by borrowing an industry practice known as DevOps.  Instead of having development and operations done by separate teams with little contact, DevOps merges the two, so the people writing new code can get instant feedback from the people who actually have to use it, and the users can request upgrades directly from the developers. 

The common variant is DevSecOps, which brings security experts into the mix so they can check the code both as it’s being written and while it’s being used.

One best practice that DevSecOps teams often use is to keep most of the code constant and introduce new features as plug-and-play modules that don’t affect the fundamentals of how the network tools work. That way, you can upgrade one aspect without affecting the others, such as security.

How Does Configuration Management Fit With DevOps?

Yes, it is true that you cannot really do DevOps without configuration management in place. Here we present principles and examples around the comprehensive configuration management, without which the artifacts and other useful information will be all over the place, in a disorganized manner.

Remember the objective of DevOps — developing tools as quickly as possible. This objective can only be done through proper organization and planning. Comprehensive configuration management gives you sufficient ammo to power up the DevOps machine.

But be advised there is some confusion between promoting configuration management solutions as "DevOps in a Box," because some say DevOps is about collaboration between people, while others say configuration management tech are tools for automating the application of configuration states. 

DevOps is the extension of flexible practices across both the development and operations departments. In fact, DevOps seeks to unify the goals of both departments. At some companies, the development department seeks change while the operations department seeks stability. But companies that embrace DevOps want both stability of their deployed assets and frequency of change. However, achieving this outcome requires change.

Like Flexible Tools, configuration management gives teams the confidence to move quickly with their changes. Under flexible practices, the company gives configuration management responsibilities to the development teams, empowering them to provision, configure, and manage their own infrastructure. You build it, you run it.

If the provider sets certain network security specifications, the clients must comply – in fact, if they don’t, their application tools may not be able to run on the infrastructure at all. Conversely, the users no longer have to reinvent the network security wheel for each of their databases and applications: They can rely on new architectures to protect them much of the time.

The goal is to design the new structure overall architecture – the “container” into which users’ code must fit – to be “loaded with as many security properties” as possible. Then you keep that foundation as stable as possible, making changes only slowly and deliberately and with extensive testing. 

Meanwhile, on a different and much shorter cycle, you can allow what’s built on top of that foundation – the “business logic” used by a given client – to evolve rapidly.

Of course, none of this is easy to do. DoD has hundreds of different network systems already, many of them incompatible, and it keeps adding more. Actually building the new computing infrastructure – and building it securely – will be harder still.

Today’s consumers demand frequent product refresh. This is posing signifcant challenges in terms of managing product configuration in their race to deliver the right connected products at the right time. 

Risks of escalating costs, increasing product complexity, failure of business cases, weakening information security, and growing regulatory compliance, further aggravate the situation. 

How can DoD stay ahead amidst the disruption? Ensuring collaboration, adopting a customer-centric mindset, and creating sustainable business models and processes, are key to competitive success. Amidst the disruption, systems engineering continues to remain relevant and fundamental to product configuration. 

However, it is important to combine it with information-based management using emerging digital technologies. This requires repositioning of configuration management principles to focus on customer centricity. 

We illustrate a pragmatic approach to reimagining product configuration from a consumer’s perspective, thereby transforming configuration management from the traditional static model to a dynamic one.

Product definition has progressed over time with changes outpacing their adoption.

With advancing technology and evolving customer expectations, product configuration has gone through dramatic change. It has moved from standardized configuration to mass customization, and finally to infinite product configuration. 

The journey of product progressions has had numerous milestones and will continue to remain  progressive. First there was the start of the product economy with empirical design facilitating volume production of standardized products but providing very little opportunity for product variations. However, with continual development and stabilization of product and process, product customization took center-stage. 

Later, there was the rise of service economy with increased focus on mass customization. Some of the salient features of products conceived in this phase include system design with product variations, product configurability, and real time management of supply and demand. 

The service-as-a-product phase was immediately superseded by the experience economy with customer experience identified as the key, and intuitively designed products and innovative business models were built around it. 

Now, a typical product definition has seen infinite configurations. With global digital market, consumers are becoming increasingly hyperconnected across multiple devices.  They are looking for continuous product refreshes while aspiring to gain full control over them.  As the industry gears up for future transition, the digital data economy is ushering in an immense range of product features, enabled by emerging technologies and advanced analytics. 

Through all these transformations, product complexity has grown manifold and has reached an inflection point, making it critical for businesses to re-imagine the entire product value chain from the perspective of the consumer. Digital Disruption is upending the classical configuration management style.

Digital disruption is now challenging the traditional configuration management lifecycle and its inherent waterfall structure. Every function creates a structure around its processes, which tends to get heavy and gradually becomes outdated as it moves along the lifecycle. 

Classical configuration management, for instance, is highly structured comprising part information, bill of material, and other components. Such a static approach lacks modularity and fails to meet the configuration needs of complex digital products and system requirements. Its rigidity leads to time and cost pressures, and makes it unsuitable to meet consumer demands for frequent product refreshes.

What does this mean for DoD business? Configuration management will need to be repositioned in the context of digital disruption to ensure sustained success. Repositioning configuration management is compatible with connected, smart products and services. 

In the age of digital disruption, there is a need to shift gears from traditional change-driven static configuration management to data-driven dynamic configuration management, ensuring near real-time responsiveness. 

In the future, instead of taking a structure-centric approach, product information must adopt an attribute-centric approach to incorporate rich consumer context. Given the multidisciplinary nature of digital products, such an approach will provide enormous configuration flexibility in the customer arena and foster new business models that create deeper insights.  

Early movers in this arena are engines builders for sale or lease but also offers light efficiency services on an analytics-as-a-service model by leveraging the data generated from aero engines and their surrounding system

In essence, product configuration will move closer to the consumer ecosystem in the digital age as consumers demand greater control of product configurability after taking possession of the product.  As a result, the focus will shift to maximizing product features that are configurable during runtime in the customer arena, using embedded systems, smart materials and so on.

However, it is important to note that the extent of configurations in the consumer arena will depend on regulatory  and compliance requirements.  Embracing the new paradigm has several levers embracing customer-centric dynamic configuration.

Given the complexity of digital products, their definition and requirements should be mapped top-down and validated bottom-up for conformity.

Model-based concepts help simplify the complexity of a multi-disciplinary product and its system of systems by representing the set of connected systems and their structure, behavior, and requirements in a model-based arena, using digital models.

Agile methodology enhances effectiveness of product development by increasing responsiveness and ability to accommodate multiple refreshes in the product to meet changing customer demands. 

Knowledge management infrastructure secures the pipeline of data and builds the configuration pipeline, which manages the bill of information across the lifecycle of the product in conjunction with the Digital Twin.
 
Analytics and insights converts the abundant data available across the digital thread into meaningful information that provides insights for smart run time updates in product configuration.

The levers enable the transformation of multiple versions of systems engineering across the value chain into a single model representing the end-consumer arena that comprises infrastructure, mission space, and product-to-product consumer behavior, supported by the data backbone of the Digital Twin, enabled by forward engineering and reverse correlation capabilities. Emerging technologies provide the flexibility required to achieve this. 

At the same time, emerging business architecture allows enterprises to expand the boundary of their core system with end-to-end management of data pipeline, creating a connected enterprise. 

Ensuring data coherence and building a dynamic configuration pipeline to manage the bill of information across the product lifecycle in conjunction with Digital Twin, is the first step towards customer-centric configuration management. Dynamic configuration management drives competitive differentiation.

Dynamic configuration management propelled by data is fundamental to postponing configuration to the customer arena - a key competitive differentiator in today’s digital world 

In achieving this transformation, organizations need to mitigate digital waste and network threats through robust data governance, and build a culture of innovation by demonstrating credibility of technology and systems. 

In addition, it is important to identify relevant data specific to consumer context and integrate configuration rules with a knowledge management framework that can be leveraged by product teams for continuous innovation. The key to success of product configuration lies in the ability of organizations to develop well-defined business models aligned with their goals and transition trajectory.  

The digital configuration management program consists in analyzing and transforming product configuration processes with digital technologies, to accelerate the response to customer requests, standardize product offerings, reduce costs and delivery times and increase quality.

The combined use of digital catalogs, to increase productivity with the management of technical information, costs, research and inventory through the digitization of parts catalogs, and digital configurators can be the right tools to:

1. Guide the user during the selection of the product in the design phase

2. Standardise the products used with certain costs and specific delivery times

3. Provide the supply department with the tools to negotiate with suppliers

4. Reduce deviation from the standard

5. Map the products in stock with a series of unique parameters and search them later, greatly reducing the creation of new parts

6. Accelerate and reduce waste of time in a simple, standard and defined workflow process

7. Give traceability and guide the user through a non-standardised workflow

8. Connect the functions of offer, engineering, procurement, production, warehouse

9. Enable continuous and real-time communication with Enterprise Resource Platform and product life cycle management system to build a unique and integrated architecture
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10. Leverage product configuration management to handle more options with less 

​Digital Twin configuration is determined by the type of input data, number of data sources and the defined metrics. The configuration determines the value an organization can extract from the Digital Twin. So a Twin with a higher configuration can yield better predictions than can a Twin with a lower configuration.

What if the product configuration data required for being delivered via DevOps method can be recorded on a Blockchain? This would make the process easier, transparent for both and would eventually improve the quality.
Blockchain and DevOps are growing and gaining wide acceptance. These two products/process already offer so many advantages alone, but together they can provide tactical and strategic planned advantages. 

The main response can center on the fact that on making product delivery chains which is DevOps, a more transparent and reliable method which is Blockchain technology.

Configuration management is important in DevOps because it helps you automate otherwise tedious tasks and allows an organization to increase agility. Moreover, configuration management supports the DevOps big picture, and it’s widely agreed upon that configuration management is essential to DevOps, as opposed to being just another component of the process.

Configuration management takes on the primary responsibility for three broad categories required for DevOps transformation: identification, control, and audit processes.

Seeing configuration management as separate and aside from DevOps creates problems in  perspective. Comprehensive configuration management is essential to a properly functioning DevOps organization, as it lays the groundwork for far more automation than that which it impacts directly so enterprise businesses communicate better and function as a more agile development unit focused on continuous integration and continuous delivery.

By manipulating simple configuration files, a DevOps team can use application development best practices, such as version control, testing, small deployments, and design patterns. In short, this means Blockchain code can be written to provision and manage an infrastructure as well as automate processes.

Product Configuration Management has often been thought of as a design problem, but the reality is that decisions are made about what product variants to offer long before designers begin work. The implications of those decisions impact teams across the product lifecycle.

With product configuration inside product lifecycle management, you can meet the demand for more advanced and varied product offerings, without driving up costs. Leverage the product configuration blockchain backbone to provide a common definition of variability across the lifecycle. 

Take control of your product configurations – whether you deliver products with a defined set of supported variants, more complex products with an exponential number of possible variations and combinations, or engineered to order products that require new variants of parts and designs with every order.

Creating a good configuration depends on how good the map is. The map describes the selection route from the requirements to the outcomes of configuration. Configuration of complex products may include several sub-systems and have multiple loops within the quotation process. 

Design structure approach is used for system assessment of decomposition and integration showing interactions flow between elements. The elements may present components of a product, phases of product development, people in organisations or design parameters of a product. The main idea of design structure approach is to map the interactions where elements are listed.

Product configuration can be roughly defined as the task of producing a specification of a product individual, a configuration, from a set of predefined component types while taking into account a set of restrictions on combining the component types. 

Process of configuration is the construction of a technical system according to the requirements of a specification by selecting parameters and positioning instances of suitable existing component types from a catalogue so process of configuration does not involve the development of new component types. The development of new component types, e.g. for addition to the component catalogue, rather is a typical task in the domain of design.

Looking closely at the various variants of the configuration task, subtle differences exist that have an impact on what knowledge is involved and how the task can be performed.

A first source of variation is the set of components. On the one hand, the set of components can entirely be determined in advance, as is the case in the configuration of a block for the production of a completely defined product. 

The components, their shape and dimensions are known and the configuration problem consists in finding the optimal layout of the block components. The example domain of Lego block boat configuration also fully specifies the components. 

Set of basic blocks could be specified as a generalised block parameterised by length, width height, and color. In that case the specification of the component space would contain one type, ie the rectangular block with replacement parameters.

The relations making up the arrangement of components provide another source of variation in configuration design. One extreme in the spectrum of configuration problems is the case where the arrangement is fixed and the configuration task is reduced to assigning values to parameters of the components, ie parametric design.

A less restricted case is where the block skeleton arrangement is given, but the specific arrangement still has to be determined. The other extreme case is where the space of possible arrangements is not limited in any way by the specification of the problem. 

The Lego block problem is an example of a configuration problem where the blockchain skeleton arrangement is given, but the constituent blocks and their relations still have to be determined.

Another source of variation in the task is the degree in which the requirements can be directly related to the components and their relations. For example in in some problems the requirements are specified in terms of a number of initial value assignments to component parameters. 

Other variants of configuration assume the requirements to be functional, in which case some relation between the arrangement of components and the required function must be determined. In the Lego block problem, the requirements are not directly related to the components themselves, but to geometric properties of the final assembly. Testing the requirements against a possible solution will involve some aggregation over the properties of the individual components.

Although the terms component, parameter and assembly suggest that configuration design mainly applies to the configuration of physical artifacts, the components can also represent  other things, e.g. activities.

 From that perspective scheduling is in many respects similar to layout design: the components, ie activities are fully specified and the problem is to find an arrangement of the activities in time that satisfies a number of constraints. 

A planning task where the possible actions that constitute the plan are known, but where the time order and dependencies between actions are unknown, can also be viewed as an example of a configuration design task.

The set of solutions to a configuration problem is a subset of the space of all possible assemblies of components. This space is often subdivided into the space of valid configurations that satisfy all constraints, the space of suitable configurations satisfying the constraints and requirements and the space of optimal configurations--  suitable configurations that satisfy optimal criteria. 

In addition to these distinctions, its also possible to distinguish between configurations that can be constructed and those that cannot be constructed in the real world. For example, one could imagine a configuration of components that performs a motor function, but such a device would be very difficult to construct given state-of-the-art technology. In principle, constructability conditions could be formulated as constraints, but in practice they are often omitted.

Dimensions on which configuration problems can differ are summarised and shows for each of these dimensions some of the values that a problem can have. A space of configuration problem types can be constructed by taking the cross product of the values on the three dimensions and much more subtle differences could be included but are restricted to a limited range of values.

Methods for solving configuration-design problem, given a knowledge base that contains the described knowledge types and the configuration-design task could -in principle- be solved by a straight forward search process. 

But the combinatorial nature of the problem makes this option an unrealistic one in practice. So problem solving methods are needed that in some way or other constrain the search process by using knowledge metric or otherwise- and by introducing additional assumptions that restrict the search space. 

Problems for construction problems include model-based construction and case-based construction. Methods for configuration include blockchain skeleton construction, and propose/revise and least-commitment.

Problems in the context of a general family of methods based on a top-level decomposition of the design task includes process models of design like decompositional design, case-based reasoning and transformational design. 

Models for case-based configuration include structure-oriented approaches where components are mapped onto a blockchain , and a resource-oriented approach based on balancing of resource requesting and production model of components. 

A simple variant of configuration design that can be handled with case-based methods, arises when a set of  arrangements is given from which a potential solution can be selected, which subsequently needs to be verified against the problem-dependent requirements and constraints. 

The selection process can be simple or can be based on a more complex matching process where requirements are matched against properties of the given arrangements. Classification is a way of selecting and verifying solutions to configuration problems.

The select-and-verify problem solving methods assumes that a solution can be found among the given set of arrangements. In general case-based reasoning this assumption is relaxed such that a solution can be found by modifying a given configuration. 

Two aspects of case-based configuration are problematic: finding the best candidate from the set of given configurations and blame assignment, i.e. identification of those aspects of the solution stored on blockchain that cause violations of constraints and requirements. 

Other approaches have defined specific configuration domain oriented conceptual foundations. These include the three main conceptualisations of configuration knowledge as resource balancing, product structure and connections within a product. Despite efforts, there are few formal models of configuration aiming to unify the different formal and conceptual approaches. Such models are needed to facilitate rigorous assessments and comparison of the different approaches.

The resource concept is useful in configuration for modeling the production and use of characteristics. A component type specifies the resource types and amounts its individuals produce and use by production definitions and use definitions. Each production or use definition specifies a resource type and a magnitude specifies how much of the resource type component individuals produce or use. A resource type is represented as a domain predicate. 

Only one resource individual with the same name as the type is needed, since a resource is not a countable entity. A production and a use definition of a component type is represented using multi-domain operational mission space predicate on component individuals of the producing or using component type, individual of the produced or used resource type and the magnitude. Use is represented as negative magnitude.

The combinatorial nature of a configuration problem is well captured by constraint satisfaction problems consisting of a set of variables with domains on which allowed value combinations are specified as constraints. Constraint solutions can be used to express compatibility knowledge in configuration tasks.

One of the special features of configuration is it being well-structured. Configuration approximations are problem class with no indefinite goals, no unspecified constraints, with completely described objects, relations and constraints between them, etc. This provides a suitable platform for a formal description of configuration knowledge normally not achievable in many design problems by this technique. 

1. “Design Control,” requires, in part, that measures be established for design documentation and the identification and control of design interfaces.  design changes be subject to design control measures commensurate with those used for the original design.   

 2.  “Instructions, Procedures, and Drawings,” requires, in part, activities affecting quality be prescribed by documented instructions, procedures, or drawings of a type appropriate to the circumstances and that these activities be accomplished in accordance with these instructions, procedures, or drawings to include appropriate quantitative or qualitative acceptance criteria for determining that important activities have been satisfactorily accomplished.   

3.  “Document Control,” requires, in part, that all documents that prescribe activities affecting quality, such as instructions, procedures, and drawings, be subject to controls that ensure that authorized personnel review documents, including changes, for adequacy and approve them for release.   

 4.  “Control of Purchased Material, Equipment, and Services,” requires, in part, that measures be established to ensure that purchased material conforms to the specifications in procurement documents.   

5.  “Identification and Control of Materials, Parts, and Components,” requires, in part, that parts and components be identified to prevent the use of incorrect or defective parts or components.    

6. “Handling, Storage and Shipping,” requires, in part, that measures be established to control handling, storage, shipping, and preservation of materials to prevent damage.   

7. “Inspection, Test, and Operating Status,” requires, in part, that measures be established to indicate the status of inspections and tests and the identification of items passing the inspections and tests.   

8.  “Corrective Action,” requires, in part, that conditions adverse to quality, such as failures, malfunctions, and deficiencies, be identified and that the cause be determined, the condition be corrected, and the entire process be documented.   

 9. “Quality Assurance Records,” requires, in part, that sufficient records be maintained so that data that are closely associated with the qualification of personnel, procedures, and equipment are identifiable and retrievable.  “Quality Assurance Program,” requires, in part, that activities affecting quality be accomplished under suitably controlled conditions.    

 10. “Audits,” requires, in part, that a comprehensive system of audits be conducted, results of those audits be documented, and corrective actions remedy deficiencies.

​Here’s the definition of configuration management: it’s the discipline of ensuring that all the assets which a company owns are known and tracked at all times—any future changes to these assets are known and tracked. You can think of configuration management like an always up-to-date inventory for your technology assets, a single source of verification.

With that defined, let’s talk about how it works in practice. Configuration management usually spans a few areas. It often relates to different ideas, like creating “pipelines” to build and test our products. Or it might relate to writing “infrastructure-as-code” to capture in code the current state of our infrastructure. 

Configuration management was traditionally a purely manual task, completed by a systems administrator. The role was a lot of manual work involving carefully documenting the state of the system. But the industry has changed completely. These changes came from the popularity of DevOps, advances in network computing, and new automation tooling.

Now that we’ve set the scene, we can dive into the details of configuration management. So let’s get to it.

What the World Looks Like With Configuration Management. Before we explore different tools for configuration management, we need to know what end results we’ll receive for our efforts.

What are the outcomes of well-implemented configuration management?

Let’s cover the benefits:

Disaster Recovery

If the worst does happen, configuration management ensures that our assets are easily recoverable. The same applies to rollbacks. Configuration management makes it so that when we’ve put out bad code, we can go back to the state of our tools before the change.

Uptime and Site Reliability

The term “site reliability” refers to how often your service is up. We have all worked at companies where each second of downtime causes disasters. 

A frequent cause of downtime is bad deployments, which can be caused by differences in running production servers to test servers. With our configuration managed properly, our test environments can mimic production, so there’s less chance of an unwelcome surprise.

Easier Scaling

Provisioning is the act of adding more resources like servers to our running application. Configuration management ensures that we know what a good state of our service is. That way, when we want to increase the number of servers that we run, it’s simply a case of clicking a button or running a script. The goal is really to make provisioning a non-event.

These are just some of the benefits of configuration management. But there are some other ones, too. You’ll experience faster onboarding of new team members, easier collaboration between teams, and extended  lifecycle of products/assets, among other benefits.

The World Without Configuration Management

Sometimes it’s easier to understand a concept by understanding its opposite. What does trouble look like for configuration management, and what are we trying to avoid? Let’s take a look.

A developer implementing a feature will commonly install some tools and deploy code. If things are sloppy, this developer probably makes the team and manager aware of the intention to come back later to clean it all up—that it’s simply a demonstration and will be rewritten soon.

But then the deadline starts pressing, and the task of going back through and rewriting the installation steps as a script gets pushed lower and lower in priority. Before we know it, a lot of time has passed, and a new developer gets put on the project. That developer is now left to pick up the pieces, trying to understand what happened. It’s quite likely they aren’t even going to touch the configuration of the server. Who knows what it would do?

The above situation is precisely what configuration management helps you avoid. We don’t want to be left in the dark as a result of developers setting up tools without proper documentation/traceability. Rather, we want to know the answers to questions like

What services are we running?

What state are those services in?

How did they get to their current state?

What was the purpose for the changes?

Configuration management can tell us these answers.

That hopefully paints a clearer picture of the problems that configuration management is trying to solve.

How Configuration Management Fits in With DevOps, Continuous Delivery, and More…

Hopefully by now you’re starting to get the hang of what configuration management is and what it aims to do. Before we go on to discuss tooling, lets take a moment to address how configuration management fits in with other concepts like DevOps, continuous integration, continuous delivery, and Docker so that you can understand how these concepts fit in with the ideas of configuration management.

Is Configuration Management Compatible With Tool Flexibility?

Yes. It reflects the desire to make changes to our tools faster so that we can respond to market demands. Configuration management helps us to safely manage our changes and keep velocity high.

Where Do Pipelines Fit Into Configuration Management”?

Pipelines are the steps or “value stream,” which we can create with tools that we usually automate, taking code from commit to production. Pipelines usually involve steps such as unit testing code, integration testing code, and creating artifacts. So a pipeline is a form of configuration management. When we build with tools like Docker, we codify our build instructions into our Docker Work Order. This allows us to better understand the dependencies of our artifacts.

Is Infrastructure-as-Code Configuration Management?

Infrastructure-as-code is the practice of ensuring all provisioned infrastructure is done so through code. so we have a written record of which services exist, where they are located, and under what circumstance. Configuration management might choose to leverage the code in order to achieve the full understanding of all the technology assets a company owns.

Is Continuous Integration/Delivery Configuration Management?

Continuous delivery is the process of ensuring that tools are always in a releasable state. You can achieve this through heavy automation and testing. Continuous integration is the process of bringing separate artifacts together into a single location on a frequent basis, for the purposes of verifying that the code integrates properly. Continuous integration tools, which are typically servers that run automation-testing suites, act as a form of configuration management by providing visibility into the steps required to set up and configure a given artifact.

That should clear up some of your questions about how configuration management fits with some practices or ideas that you might be using or are familiar with. Any discussion of configuration management would be incomplete, however, without a discussion about tooling. So, let’s take a look at the different tools we have at our disposal for implementing configuration management.

What Are Configuration Management Tools?

There are many different tools for configuration management. In fact, it can get confusing, as there are tools that support configuration management without explicitly being configuration management tools.

For instance, Docker neatly packages up steps needed to set up and run an application in Docker Work Order. However, people don’t often consider Docker a configuration management tool.

To make things clearer, let’s divide up the common tools that might fall under or relate to configuration management:

Configuration Management Tools

These are the tools you see typically associated with configuration management that provide ways to codify steps that we require in order to bring an asset in line with a current definition of how that asset should look. For instance, you might create a playbook that ensures that all of our X servers have Y installed within them.

Infrastructure-as-Code Tools

If our configuration management tools include the setup we need on our assets, our provisioning tools are how we get those assets. It’s this blurred line that explains why we need to bring these tools into our discussion of configuration management. And many consider it an anti-pattern to use configuration management tools for provisioning.

Pipeline Tools

We talked briefly about delivery pipelines, but implementing them requires tooling. By using tools to codify our build process, we make it easy for other developers to understand how our artifacts are modified and created, which is a form of configuration management.

Source Control Tools

While we need to codify our automation in scripts, if we don’t appropriately track the history of our changes, then we aren’t really achieving configuration management.

How Can I Get Started With Configuration Management?

Where to start? Do you begin by researching tools? Implementing some automation? Auditing your existing servers? Talking to others in your company?

Where you start with anything always depends on where you currently are. That said, only you are aware of your current situation and the limitations and resources available. Below are a couple different places you can begin your journey to effective configuration management:

Audit your tools—What tools do you currently have? What’s the state of it? Is it well documented? Are the setup and run instructions known for the tools

Perform a tools assessment—Do an assessment of what tools exist on the market for configuration management. The ones listed above are a good start. Identify which tools could help you solve some of your configuration management problems.

Learn about best practices—Successfully implementing configuration management isn’t a one-and-done task. It takes time and work to continually ensure that all new tools are  appropriately audited and tracked. So you might want to look into some different key concepts, such as Infrastructure-as-Code  and build and release pipelines.

It’s Time For Everything-as-Code!

And that’s all! Hopefully that helps to clear things up for you about configuration management. It’s all about keeping track of the current state of your tools infrastructure.

There are many ways to implement configuration management, and there are lots of different tools and processes. So when it comes to strategy, be sure to take your time assessing options and understanding how you want your configuration management processes to work.

It will all be worth it in the end, though. Get your configuration management right and your teams will be safer, more productive, and faster to make changes.

So from now on, audit, track, and write everything-as-code. The minimal set of activities to be covered by the configuration plan should accomplish the following:   

1. Identification and control of all tooling requirements, code and design change interfaces 

2. Control of tooling user, operating, and maintenance documentation 

3. Control and retrieval of qualification information associated with tooling designs and code; configuration accounting  

4. Control of tooling building, release, and delivery of products. 

5. For security system components, configuration items or controlled databases should include tooling requirements,

6.  Data files used and called directly or indirectly by tooling

7.  Support tooling used in development, exact versions. 

8. Libraries of tooling components essential to security

9. Tooling plans that could affect quality
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10. Test results used to qualify tooling

​The Services have lots of ideas for AI. But it has to implement them without overwhelming troops or the network with too many apps and too much data.

There are tremendous number of potential military applications for AI, from the battlefield to the back office. The trick is not overwhelming the users with too many different specialized apps to figure out and not overwhelming the network with too much data moving back and forth.

Army has launched a new effort, dubbed Project Quarterback, to accelerate tank warfare by synchronizing battlefield data with the aid of artificial Intelligence. 

The project aims for an AI assistant that can look out across the battlefield, taking in all the relevant data from drones, radar, ground robots, satellites, cameras mounted in soldier goggles, etc., and then output the best strategy for taking out adversaries with whatever weapons available. 

Quarterback, in other words, would help commanders do two things better and faster, understand exactly what’s on the battlefield and then select the most appropriate strategy based on the assets available and other factors. 
Just the first part of that challenge is huge. The amount of potentially usable battlefield data is rapidly expanding, and it takes a long time to synchronize it. 

Building Battle Strategies

AI can a quickly potential lines of sight between different points of the battlefield. That’s why the AI Task Force is working on a “fields of fire” AI that uses the new IVAS targeting goggles to determine what area each soldier can cover with their weapons. 

The AI tools would compile that data for the whole squad, platoon, company, or even battalion, giving commanders a map of exactly what approaches were defended and where any potential blind spots lie. Another potential application of this same technology would be to analyze potential fields of fire from suspected or confirmed enemy positions to identify the safest routes past them.

Ultimately, the Army is looking for a lot more than a data visualizer. They want AI to help with battle strategy.  “How do you want to make decisions based on battlefield data? How do you want to select the most efficient way to engage a target, based on probability of hit, probability of kill? Do you have indirect fire assets available to you that you can request? 

Do you have real assets that you can request? Can I you my wingman… or, does the computer then recommend, ‘Red One, our wingman should take that target instead of you for x, y reasons?’ That goes back to that concept of how you make a more informed decision, faster. And who is making that decision could be a tank commander or it could be a battalion commander.

“Sensor to shooter? It’s the network. The synthetic training environment? It’s the network. IVAS is the network. If there’s one thing that’s cross cutting everything we’re working on, it’s the network. The bandwidth requirements, the latency we can’t have, there’s a lot of technical hurdles to overcome with that.”

Data from Sensors

Shooting down drones, aiming tank guns, coordinating resupply and maintenance, planning artillery barrages, stitching different sensor feeds together into a single coherent picture, analyzing how terrain blocks units’ fields of fire and warning commanders where there are blind spots in their defenses are all uses that will be tested.

“All the vast array of current and future military sensors, aviation assets, electronic warfare assets, network assets, unmanned aerial, unmanned ground systems, next generation manned vehicles and dismounted soldiers will detect and geolocate an enemy on our battlefield. 

AI Task Force is focused on intelligence support to operations, where we’re using offboard data” – that is, data gathered from a wide range of sensors, not just those onboard one aircraft or vehicle to look for targets.”

Using Data Effectively

We need an AI system to help identify that threat, aggregate data on the threat with other sensors and threat data, distribute it across our command and control systems and recommend to our commanders at echelon the best firing platform for the best effects, be it an F-35, an extended range cannon or a remote controlled vehicle.

The idea is to pull data from a host of sources; curate it by putting it into standard formats, throwing out bad data, and so on; and create a central repository — not only for the data but for a family of AI models trained on that data. Users across the Army could download those proven algorithms and apply them to their own purposes.

This means a lot of data moving back and forth over the Army network. Modernizing that network is a major Army priority and the service is developing major increases in satellite bandwidth for its upcoming update. But the AI Task Force is also looking to reduce those data demands wherever possible.

Network Challenges

There are concerns about getting all of those systems to link up and share massive amounts of data.  “The thing that keeps us up at night is the network. “It’s not problems within the network, it’s that we’re relying on the network for so much”

“There are some huge autonomy challenges, but one of the greatest challenges we’re going to have is the network. On the ground, when you have robots wanting to talk to other robots, wanting to talk to ground vehicles and you go behind the hill, you go behind the rock, you go down in the gully; you’re in a city and you go around the corner of the building.

The Army has had bad luck trying to institute large-scale data standards. Case in point: the Joint Tactical Radio System program spent billions in a fruitless attempt to buy a single radio to serve all of its communications needs. 

Some time ago, military mandated the Commercial Mobile Device Implementation Plan — essentially an effort to lower its data-transfer costs by using commercial networks for unclassified data. But as the current debate over 5G networking shows, even commercial cellular providers are having trouble getting ahead of what they see as future demand. 

“This is commercial technology that everyone uses and relies on and so we are trying to take some of that and pass full-motion video in some cases. This is a big technological challenge and everyone is going to say, ‘I’ve got a radio that will do it.’ Fine, as long you’re 100 feet apart and can see each other. So that’s going to continue to be our biggest challenge because we just haven’t fixed the physics yet.

Techniques are being developed to inspect networks and see why these networks might come up with a certain recognition or solution or something like that” 

There’s  important emerging research in fencing off neural networks and deep learning systems while they learn, including neural networks in robots, “How we can put this physical structure or constraints into these networks so that they learn within the confines of what we think is physically okay.”

Troops in the Loop

Commanders and soldiers will have to become more comfortable with robots and software that produce outputs via processes that can’t be easily explained, even by the programers that produced them.

You could feed the AI surveillance imagery of “a forested area” and ask it, “show me every tank you see in the image.” The AI would rapidly highlight the targets – far faster than a human imagery analyst could go through the same volume of raw intelligence – and pass them along to troops to take action.

Military networks have so many thousands of users and devices that just figuring out what is connected at any given time is a challenge, let alone sifting through the vast amounts of network traffic to spot an ongoing intrusion. For all its faults, AI is much better than humans at quickly sorting through such masses of data.

The way to develop that trust is the same way humans develop trust in one another, slowly and with a lot of practice. “Most humans are not as explainable as we like to think… If you demonstrate to a soldier that the tool or the system that you are trying to enable them with generally functions relatively well and adds some capability to them… they will grow trust very, very rapidly.” 

But, when it comes to big decision aids, “that will be much harder. “You trust something because it works, not because you understand it. The way that you show it works is you run many, many, many tests, build a statistical analysis and build trust that way. 

That’s true not only of deep learning systems but other systems as well that are sufficiently complex. You are not going to prove them correct. You will need to put them through a battery of tests and then convince yourself that they meet the bar.’ 

Implementation Directions

In the meantime, the Army will work with the network it has until more capability comes online at a price it can afford. You can’t just walk away from what you had because we invested a lot of money into the network. And so thickening, augmenting, improving the network with commercial solutions, and in short increments so you can capture the very best technology you possibly can.”

Consider self-driving cars as an everyday example. AI matches drivers with customers, but each individual user isn’t actually sending or receiving all that data. It boils down to “here I am, I want a ride to there” or “here I am, I’m willing to give someone a ride this far.” Likewise, a combat vehicle could transmit “here I am, I have this much ammunition, I have this much fuel. Please send supplies ASAP.”

You can extend this principle to even more complex functions like spotting targets or predicting breakdowns. If you put enough processing power and software on the frontline platforms themselves – a concept called “edge computing” – they can analyze complicated input from their own sensors and only send a summary report back over the network, rather than having to transmit raw data to some central supercomputer for analysis. 

A vehicle could send, “I need X maintenance in Y hours,” for example, rather than every bit of data collected by the diagnostic sensors on its engine. Or a drone could send “I see tanks here, here, and here, and a missile launcher there” rather than transmit full-motion video of everything in view.

Now, not every present-day weapons system is smart enough to do the analysis by itself. Many systems don’t even have sensors to collect data, and installing them would be prohibitively expensive. “We can’t afford to retrofit all our Humvees from 30 years ago.

So one of the task force’s priorities will be to ensure that all the Army’s new weapons systems, from long-range missile launchers to targeting goggles, can collect and transmit the right kind of data on their own performance. That means embedding enough computing power to perform a lot of analysis at the edge, rather than having to transmit masses of data to a central location.

Big data gets a lot of attention and can put a lot of strain on networks. But, for many applications, we can just start little.”

1. Integration with existing processes

All the processes running in business are different from one another. So, the process that is automated should seamlessly integrate with the existing processes. The integration can happen at various levels of the automation process but it is essential for all the automation processes to work smoothly with the environment.

2. Consistency

The automated processes should be consistent with other processes and their corresponding inputs and outputs.

3. Step by step approach

It is not necessary to perform the automation of all the necessary tasks at once. Depending on funds, resources and overall logic of the business processes, you can divide the job into several stages.

4. Process flexibility

Over a period of time, business processes tend to change. The automation solutions should be flexible enough to incorporate and reflect these changes.

5. Simplicity

The aim of automation is to make the business processes simpler and not more complicated. If after automation, the process requires a lot of human intervention, you must understand that something is wrong.
6. Training the staff

For efficient functioning of business processes, it is important for the staff to have a complete understanding of the workflow. The better they know a process, the better it will function.

7. Reduce business process automation operational costs

Running a business is costly . Automation can substantially help in reducing cost and increasing profitability. However, most of the people find it difficult to choose tasks for automation. Well, any task that that doesn’t require human thought process but just a series of steps that can be predicted using computer logic can be chosen for automation.

8. Complete conventional tasks 

Paper processes can be completed using automation. These days, you can digitally sign documents, sign contracts and also easily manage organizational expenses using various tools available in the market making it easier to manage the flow of work. 

9. Avoiding mistakes

Rectification errors cost businesses a ton of money every year. The greater the rate of error more is the cost for rectification. A small misconfiguration can expose vulnerabilities to attackers or disrupt business processes.

Automation can help you in improving efficiency and ensuring accuracy. You can take basic tasks out of human hands and engage their brain more into developing strategies and more important functions.

10. Deliver superior customer service

With major advancements in the field of technology, today, the way customer service is provided has changed a lot. Using artificial intelligence, you can create great customer service that will answer all of their questions directly and provide the team working at the back end with required information and resources.
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Automated customer service can help you greatly reduce the response time. Time zone constraints do not affect automated customer service. Robots can help in responding to customer queries almost instantly, something which human support cannot guarantee. Thus customers no longer have to wait for hours just to get a response and virtual assistants will be able to predict what customers are looking for by tracking their actions and understanding their needs. 

​Marine Corps is identifying ways to reduce manpower-intensive logistics requirements — reducing and removing manned transportation assets is critical Unmanned air, ground, surface and subsurface “technologies are the way of the future and will … improve the sustainment of our forces.

Robotic systems can help reduce warfighters’ presence on the ground in dangerous areas. “Robots going into these areas ... have the dexterity and the capabilities to clear rubble,. These technologies have features that can be directly applied to robotic systems on the battlefield. 

Unmanned platforms could be used to complement Marines working at forward arming and refueling points in remote locations. Such technology is already present in industry, like exoskeletons that provide support to manufacturing lines. 

“That's the small, lethal footprint that required to get after for this logistics concept that we seek. The Navy is also examining how it can integrate unmanned vessels into its logistics fleet. 

Specifically, the Navy and Marine Corps are looking at how they can leverage medium and large-size vessels for logistics operations, “We don't have specific requirements or specific plans as of this moment, but that's going to be a big growth area for the Navy and Marine Corps over the next couple years.” 

Additionally, the Navy is working to ensure that its logistics enterprise is able to support all warfighting functions “with increased speed, agility and survivability. The service is employing multiple lines of effort to do so, which include diversifying distribution, improving sustainment, enabling logistics awareness, optimizing installations and supporting sustained operations.

Future fighting environments will push sea bases further from fleet Marine forces ashore. That means there will be a need for long-range connector capabilities that can operate from sea bases hundreds of miles off the coast. The services will also need to make its equipment lighter and more economical to use.

Robotic Applications

The Army’s future plans rely a lot not just on AI but also on ever-more-intelligent ground robots. Right now, a single Army operator can control about two ground robots. The Army’s plans are to get that ratio to one human to a dozen robots. 

That will require those future ground robots to not just collect visual data but actually perceive the world around them, designating objects in their field of perception. Those robots will have to make decisions with minimal human oversight as well since the availability high-bandwidth networking is hardly certain. 

Team ran robotic experiments where ground robots demonstrated that they could collect intelligence, maneuver autonomously and even decipher what it meant to move “covertly,” with minimal human commands. The robot learns and applies labels to objects in its environment after watching humans. 

Army is determined to field a mid-sized combat robot vehicle, but the prototypes are outstripping the datalinks that would connect them.

One prototype is a  10-ton, 20-foot electrically-powered treaded minitank that can carry a small aerial drone on its back and can pop a smaller ground robot out of a front compartment. Army leaders say that they’ve also been experimenting with battle concepts that combine soldiers, unmanned tanks, and small UAVs

Beyond its quest for semi-autonomous ground robots, the Army is looking into more and more data-intensive gear, such as the Integrated Visual Augmentation System, or IVAS, a set of augmented-reality goggles intended to give soldiers a lot of visual real time data to help with tasks like targeting during operations, and also with training and simulation during downtime. 

That’s also supposed to hook up with data feeds from tanks or other robots. But the rush to develop and field the newest tech concepts, and to integrate heavy amounts of data into all facets of operation, have driven the Army’s data needs skyward. 

Open architecture will allow the Army to upgrade its communications and data networking as needed, as well as to incorporate higher levels of autonomy, as those capabilities emerged. Teams experimented with integrating ground and aerial robots with the Ripsaw, but not yet in a communications-denied environment, in part because the Army has not yet published their specific needs for future mid-sized robot combat vehicles. 

Robots may help extend solid data connectivity further afield, serving as flying or rolling cellular towers in a moving mesh network. “We’re also looking at unmanned vehicles to expand the network, to expand the line of sight so we can push these robots out as far as possible. So that they get in the riskiest places on earth and the soldier. 

Manoeuvre Roadmap will forward strategies by listing the types of AI that will be needed year-to-year to support military strategy and maintain a firm understanding of what AI is and how it will be used to benefit the organisation. This understanding should go beyond buzzwords and definitions. 

The trickier and more relevant question for many is: How will it do so, when it will do so, and in which markets and applications will it have the most impact? Certainly, professional computing applications  and virtual work spaces are among those most clearly in the crosshairs of machine learning and professional spaces

“There's a reason for the confusion between Artificial Intelligence and Machine Learning“
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Vendors are rushing AI solutions to market before the ultimate decision-makers and buyers are up to speed on what they need. But the plot thickens when Military Leaders are asked about the specifics of what AI can accomplish—and how AI differs from machine learning and deep learning.

Very quickly,  technology leaders recognize that they need to put AI and its various subcategories e.g., machine learning, deep learning into practice—and into a common business vocabulary that everyone can understand.

The first step is communicating what the definitions are for AI, machine learning ML, and deep learning. There is some argument that AI, ML, and deep learning are each individual technologies. Leaders must view AI/ML/deep learning as successive stages of computer automation and analytics that are built on a common platform.

On the first tier of this platform sits AI, which analyzes data and quickly delivers analytical outcomes to users. 

Machine learning sits on the tier two application of AI that not only analyzes raw data, but it also looks for patterns in the data that can yield further insights. 

Deep learning is a third-tier application that analyzes data and data patterns, but it goes even further. The computer also uses advanced algorithms developed by data scientists that ask more questions about the data with the ability to yield even more insights.

The best way to demonstrate these different layers of increasingly complex analytics is by finding a business example that can show the benefits to the decision makers in the business.

Let's take the sample of traffic planning.

Tier one: AI

You develop an AI application that tells your traffic engineers and planners where the major traffic congestion points are located in the city. This assists them in planning for road repairs, stop lights, and other infrastructure that, hopefully, can relieve congestion in certain areas.

Tier two: Machine learning

You further develop your AI/analytics so that it also looks for patterns in the data. For instance, it notices the traffic at certain intersections is most congested in the morning between 6 am and 8 am, or that traffic queues up in the evening, ahead of a sporting event.

Knowledge of the situation gives planners and engineers more insight because now they can plan not only for traffic snarls but also for future events like football and hockey games.

Tier 3: Deep learning

Deep learning is where data analytics moves beyond raw data and data patterns. Deep learning adds specific algorithms that data scientists develop to further expand the querying and insights derived from the data.

Algorithms that could be added to the traffic analysis might include: What areas of the city will see the greatest population growth over the next ten years? Or, which roads will need major repairs in the next five years? Or, do weather projections say that we will have more or less snow over the next five years? By adding these algorithms on top of pattern and data analyses, users get a more complete picture of the situation they are trying to act on and assess.

Putting it all together into an AI roadmap

Being able to break down the differences between AI, machine learning, and deep learning is important because it shows Leaders not only the different tiers and capabilities of AI automation but also the increasing levels of business insights that can be gained from it. 

By visualising these different AI tiers into a strategic roadmap, an organisation can measure tangible results for mission objectives.

So a city, for instance, can say that next year it will have a comprehensive understanding of its road system, and where the traffic congestion is located. In year two, the city will be able to predict traffic jams from rush hour and special event traffic and be able to proactively inform travelers to use alternate routes. And in year three, the city will be able to develop plans for the future by assessing population/traffic growth and infrastructure repair shutdowns.

New contract to apply artificial intelligence to Marine Corps maintenance could streamline logistics and help lessen dependence of fighting forces from long supply lines. Ultimately, AI could enable the far-ranging manoeuvres envisioned by the multi-domain operations concept.

Most debate about military AI centers on robots, but professionals usually talk logistics. Without fuel, ammunition, spare parts, and maintenance, no weapon, manned or unmanned, is going anywhere.

What’s more, while AI has made great progress in recognising objects/targets and navigating the physical world, autonomous combat robots are far in the future.

Marines will apply AI-driven “predictive maintenance” to part of its aging fleet troop carriers equipped with diesel engines, heavy-duty transmissions, and other features with hundreds million hours of metrics on diesel engines alone, and in the world of AI machine learning, the more metrics you have, the more accurate your predictions get.

The concept of self-driving cars has been around for years, but only recently have increasing advances in networking, satellites, and laser equipment made this dream a reality. 

Vehicle manufacturers realized that they could use camera systems to relay data to an onboard computer that would process images of the road and create responses. Although we do not have robotic vehicles filling our roadways as of yet, some vehicles already contain numerous autonomous features that make driving easier and safer than ever before. Some models offer assisted parking or braking systems that activate automatically if they sense an issue. Vehicles can sense lane position and make adjustments there as well.

1. Reduce the number of accidents that occur on roadways.

When we are riding along in a driverless car, then what happens on the road is no longer subject to the numerous bad behaviors that human drivers exhibit as they attempt to reach their destination. A great majority of automobile crashes are as a result of human error. If computers are in more control, then there could be fewer behavioral incidents, costs that are associated with damage and help to reduce overall driving times.

While autonomous trucks aren't yet completely safe and accident-proof, especially in certain weather environments and road conditions, various reports that have been conducted claim that they will lead to a significant decrease in accidents compared to human-driven trucks. 

2. Driverless cars could work with higher speed limits.

As human populations move toward the use of driverless cars, it may become possible to raise the speed limit that vehicles can drive on extended trips. The computers would calculate the operations of the automobile to ensure the occupants remain safe. That means passengers could take care of other needs while the vehicle does the work of transportation without compromising the safety of the people who are on the roadways.

Higher Speed limits might be considered as an option if more people are using self-driving cars. Since the computers calculate operation of the vehicle safely, driving time could be reduced by faster speeds allowed on the road.

3. It could reduce the amount of fuel that we consume for transportation needs.

Computers would make it possible for driverless cars to maximize the fuel economy of every trip in multiple ways. Platooning would allow for the vehicles to draft with one another to reduce the effort that the engines would need to work while on the road. Real-time updates to driving conditions could help automobiles avoid high-traffic areas, places where weather disruptions are possible, and other potential hazards in the road. Because these vehicles would likely communicate with each other while on the roadway, they could ensure that everyone reaps these rewards of this advantage while still providing a higher level of safety.

4. Driverless vehicles could reduce commute times.

Because a driverless car would likely communicate with the other vehicles around it and the roadway, it would know where to maximize speed and movement to ensure the quickest possible commute. Other automobiles would react when a vehicle needed to exist a highway, for example, preventing the need to force oneself into lanes, cutoff drivers, or miss an exit. Vehicles could travel in bumper-to-bumper platoons while automatically merging to accommodate oncoming traffic.

5. Decrease in Traffic Jams and Congestion

Another often overlooked advantage that autonomous trucks can provide is that they can greatly reduce traffic jams and congestion, especially on highways. That's because autonomous trucks will be programmed to take the most optimal route and will also not be susceptible to delayed human reactions that often lead to traffic backups.

Because self-driving cars are rarely involved in accidents, their potential to ease congestion is high. Not only that, because self-driving cars can communicate with each other, they would eliminate the need for traffic signals. By driving at a slower rate but with less stops, better coordinated traffic would lead to less congestion.

7. Cost Savings

An advantage is that autonomous trucks can result in cost savings to the companies that use them. Of course, there will be a large upfront investment in buying a vehicle that's capable of autonomous driving, but over time, this is expected to pay off through a combination of increased efficiency and a decrease in drivers that have to be paid.

:8. Nearly No Error

The incredibly complicated technology behind self-driving cars lets the on board computer make hundreds of calculations a second. These include how far you are from objects, current speed, behaviour of other cars, and location on the globe. These super accurate readings have virtually eliminated driving errors for test cars on the road, as the only accidents so far are while human drivers have been in control.

A computer might not be 100% perfect, but it is far closer to that standard than a human driver could ever be. By using complex algorithms that guide the vehicle in the correct lane, calculate the appropriate stopping distance, and other information that’s available while on the road, there is a significant decrease in the risk of an automobile accident when using this technology.

9. Less space in between vehicles

Autonomous cars allow vehicles can ride closer together, therefore allowing more cars on the road with actually less traffic. We could drive faster with driverless vehicles on the road.

Because computers would be handling the driving responsibilities for long-distance trips, the design of our highway system would support a higher speed limit on straight stretches of road. That means we could arrive at our destinations faster without increasing the risk of an accident. Each autonomous vehicle could calculate its distance between vehicles, determine the highest and safest possible speed.

10. Sensor technology 
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Sensors could potentially perceive the environment better than humans could, seeing farther ahead, better in poor visibility, and detecting smaller and more subtle obstacles. Plus, several cameras might be used at once, and cameras have no blind spots, so they will be more aware and vigilant than a human driver ever could be.

​AI can maximize integration of complex communications networks for warfighters and ensure the message gets through to save the battle and win the war. 

There are significant risks to consider with such a powerful capability. Mitigation of  network attack or data breach of the Artificial Intelligence capability can manage exposure of every tactical, operational, and strategic vulnerability to enemy exploitation. Another risk could be the loss of control of the Artificial Intelligence capability  system, causing the system to deny all warfighter communications capabilities – such an occurrence would rewind the clock returning communications management to its largely human-led process as it is today.

The Artificial Intelligence capability  concept is ahead of technology. The capability does not exist today, and critical support research and resourcing decisions to even pursue something as powerful as an artificial intelligence capability.

There is plenty of reason for optimism about future autonomous AI systems. The Artificial Intelligence capability  concept leverages the link between AI and deep learning. AI systems trained to learn and think independently will likely dominate the field of AI. The key to deep learning is access to large, high-quality datasets.”

High speed robot and autonomous capabilities will become features of future battlefields.  Army needs these capabilities to manage all warfighting functions – especially command and control — to win the next war. It depends on systems that rapidly and reliably communicate with our troop formations. Artificial Intelligence capability  offers an ‘always-on’ connection to command and control these complexities. 

Even lower fidelity versions can help with training and mission planning. On those lines, the synthetic training environment will start distributing One World Terrain as they work out the data management and data storage hurdles.

The trainer is looking at alternatives both for the engagement system that runs the shooting devices and the devices themselves. As the Army works to deliver new synthetic training technology, it recently set up a new network to more effectively integrate software into the program.

The synthetic training environment is a 3D training and mission rehearsal tool that brings together live, virtual, constructive and gaming environments to improve soldier and unit readiness. 

The new training environment is network dependent and will interface with operational networks and network-enabled platforms. For now, the cross-function team is working to ensure it can stay on a glide path to reach initial operating capability in line with the current schedule,.

Behind the eye-grabbing new night vision, more lethal artillery and faster aviation being developed by the Army’s new cross functional teams sits a group that gets little attention but without which many soldiers would be grabbing blindly in the dark on the battlefield.

The Assured Position, Navigation and Timing trainer has the task of figuring out how to find ways to move friendly troops safely in hotly contested terrain and also help connect a lots of systems to put the right effects at the right time and place in the most precise way.

Teams have built a camera that sees through dust, helping pilots better guide and land in desert environments.
Something that’s taken for granted, the signal strength on a cell phone, for instance, isn’t something that’s readily available to soldiers using navigation or even targeting equipment. It takes specialists in certain areas to even detect and evaluate if a system is being jammed.

Efforts are working toward a way for any user of any such equipment to see their own signal strength and jamming concerns. Teams are working mounted, dismounted and situational awareness efforts currently. Soldiers will, for the first time, have an alternate way to navigate built into their vehicles that’s not GPS.

There’s also work to consolidate systems. Past equipment development often meant that each system had its own GPS. That’s created scenarios in which a single vehicle with multiple tracking, targeting and communications systems could have seven or more GPS antennae poking out.

If those efforts are successful, it can give tactical-level units beyond line-of-sight capabilities for a variety of uses without GPS. One piece of kit that’s currently under development might not seem, at first glance, like something that most infantry and close combat troops would put at the top of their list. But they should.

That’s because the Adaptive Squad Architecture program is an effort to tie together all of the current and future tech soldiers wear or carry and more. By powering all devices and using one processor, the move could streamline and lighten kit for the individual soldier.

What the squad will do is manage power and signals, and network what a soldier sees from their goggles to their weapon to their radio and what they’re linked into both within and outside of the squad.

And it means more than just what that soldier can see. It has effects on what their commanders can do, too. We give commanders more options than they ever had before, because through the data analysis a commander can best spread the load of equipment through the formations and account for the flood of variables that face the soldier and squad.

Essentially, the architecture becomes kind of a smartphone hub for the soldier and squad that can take on applications, algorithms and other measures to not just evaluate but also improve performance.

Teams will soon launch “Watchtower,” an Army app story similar to what smartphone users access. Within that, a lot of experimentation can take place, and leaders can tailor apps to their unit configurations and specific missions.

One example is soldier load.

Future ammunition is expected to be lighter. So, the commander has a decision to make: carry the same weight but with more rounds, or reduce the weight to the rounds they’ve always carried, keeping fatigue down and performance up?

The system can also use seemingly endless data to see if different weapons systems or communications gear match up, are redundant or ineffective.

Does the squad leader need an M4 or an M249, based on the mission? Does the squad need to carry HF communications gear or can it make do on this mission with satellite and VHF comms only? Those are some examples that the data can help mission planners explore.

And beyond the squad, the aim is to have squad “talk” wirelessly with platforms that the soldiers are riding in, from Bradleys and Strykers to new helicopters and future vehicles. Developers envision a day when the soldier boards a chopper or vehicle and the systems automatically start charging batteries and uploading their data while downloading new information from the larger network.

Squads to tap into cellular networks and battle-track on tablets at network trials. The gear will include lighter and faster communication equipment, battle-tracking applications on tablets and new ways to communicate with one another, as well as partner forces. 

By using a secure-but-unclassified architecture, soldiers can tap into commercial cellular networks, like 4G, and a greater range of wavelengths, depending on the electronic threat environment.

Field Teams are getting new capabilities that include advance networking waveforms, which significantly improves our mobile ad hoc networking capability at the lowest tactical echelon.”

The soldiers will begin collective training at the squad-level to view live-streaming full-motion video from unmanned aerial vehicles through an app on approved smartphones. Dismounted troops will get 3D digital maps and the ability to send precision target coordinates.

“Ultimately it’s going to take a hard look at if we have the right radios in the right places” “Are the new capabilities really adding enough capability to justify price points and overall cost of the networks. 

It’s not a new or separate network, but instead uses existing devices and gateways alongside commercial off-the-shelf products to make sure communications can continue even in limited bandwidth environments and amid electronic attacks.

“One thing we know for sure is the capabilities we’re pursuing are better, definitely better than what we had.  "And soldiers that don’t have it today are chomping at the bit to get it.”

But the amount and specific types of gear needed for infantry, Stryker and armor brigade combat teams do vary and so each type will require different approaches to fielding equipment.

“User feedback, leader feedback and running these through a series of exercises, to include force on force combat training center rotations, will give us that kind of feedback we need to make the best decisions.

“This environment allows us to secure the network, but pass data to where, if it’s perishable time sensitive data, we can actually share it with unified action partners. “That allows us to connect better with teammates and give troops more waveform options, regardless of who they’re working with.

“If we go somewhere where we believe we can leverage the infrastructure, we can and we will. But if there’s a concern ... we have the ability to do some workaround and show up in an area and rapidly “plug and play” into the existing infrastructure is key.

1. Improved Analytics and Better Data

Realistically, you can’t track much data pertaining to human workers. Sure, you can measure their output and productivity in a variety of ways, but the information you collect is not always reliable either.

It’s the complete opposite with robotics and advanced automation systems. As they work, they collect data about anything and everything, which serves as an incredible database of information that you can put to use. It leads to better decision making with more successful outcomes. It reveals a lot more about your processes and it can help you unlock new avenues of improvement. Essentially, the more data you have the better. But it also has to be accurate, error-free, and reliable and that’s something automated systems can definitely provide.

2. Increasing productivity

A robot has the ability to work at a constant speed, unattended, 24/7. That means you’ve got the potential to produce more. New products can be more quickly introduced into the production process and new product programming can be done offline with no disruption to existing processes. 

Robot have been designed to handle routine functions while maintaining long-term precision to increase productivity without affecting quality with automated workers in place. Improving supply chain productivity can deliver significant value to warehouse robots. They can increase accuracy, accelerate routine processes, and solve a number of common problems with employees when used side-by-side.

Conventional operation consists of manual labor, such as product handling, cart pushing and equipment operation. Employees walked the entire pick path then guided the pushcart to the packaging area for staging. With an autonomous and smart-picking solution, employees remain in specific zones while the robotic units travel between pick and put operations. Because each robot is responsible for delivering products from the employee to the packaging area, the distance each employee travels during a standard shift is considerably reduced as well. 

3. Increased Quality Assurance/Reducing mistakes 

The use of robots in the warehouse means that there is little chance of errors in relation to human labor. In addition to errors, this system reduces the time taken to go to different parts of the warehouse only. That is why employees focus more on quality control.

Robots will always deliver quality. Since they’re programmed for precise, repetitive motion, they’re less likely to make mistakes. In some ways, robots are simultaneously an employee and a quality control system. A lack of quirks and preferences, combined with the eliminated possibility of human error, will create a predictably perfect action product every time.

Robotic automation eliminates risks by accurately producing and checking items meet the required standard without fail. With more product going out the door manufactured to a higher standard, this creates a number of new business possibilities for companies to expand upon.

4. Improving safety

Robots don’t need to be with people 24/7. They can work with programmed sensors to avoid other robots and objects. This benefit reduces the chances of serious accidents that could affect a worker’s safety. Some of the most common damage to warehouse employees is caused by collapsing pallet racks, slips, and trips, and often high ladders drop. Warehouse robots eliminate these common risks for employees who are able to handle climbing, pick-up, packaging, and move around the warehouse.

“Employee safety can be improved in highly hazardous environments. In distribution center robots can seamlessly zip past each other, humans, or other moving objects thanks to advanced collision avoidance capabilities, which are processed as quickly as any human can react to potential accidental run-ins.

Safety is the most obvious advantage of utilizing robotics. Heavy machinery, machinery that runs at hot temperature, and sharp objects can easily injure a human being. By delegating dangerous tasks to a robot, you’re more likely to look at a repair bill not other costs. Employees who work dangerous jobs will be thankful that robots can remove some of the risks.

5. Easier scheduling/implementation 

Traditional workers need breaks for rest and energy rehabilitation. But robots don’t need breaks. They can work throughout a long shift. Robots provide flexibility, easily retooled and repositioned for new production programs and can easily be redeployed in new applications with ability to easily switch between a wide range of products without having to completely rebuild production lines

Robots can be realistically implemented, depending on the specifics of the operation. This is a remarkably small amount of time even at the spectrum’s high end, particularly when compared to other technologies. 

6. Ability to scale

Since robots are relatively easy to install in a facility, you can use a modular deployment system, starting with a few units and adding more as your business increases and needs change. This allows you to avoid an incredibly high initial investment, as you can start with one or two and increase your floor over time rather than buy a large number of robots at once. This modular deployment frees you from the capital to pursue other initiatives, analyzing robots ‘ impact on your business, and taking the next steps.

Any process, system, or platform that is rule-based and includes repetitive tasks or operations can be automated, in full, using robotics. That also means you — as a business — can be just as versatile. There is a nearly endless supply of opportunities in regards to how you can use the technology, and it can be scaled up or down, as much as you need.

7. Reduce both direct and indirect operating costs. 

“The implementation of autonomous robots could primarily drive value by reducing direct and indirect operating costs and increasing mission success potential using autonomous robots to drive supply chain innovation.

A quick return on investment outweighs the initial setup costs.  Automation advantages reduce production cost. Decrease in Part cycle Time is crucial for increasing efficiency.  Robotics can work longer and faster which increases production rate.

8. Enable quick ramp-ups to meet increased demand period 

Available labor, particularly during peak periods, cannot always meet seasonal demands. However, companies can turn to robots to improve operations and meet labor demands. “During high demand peak some warehouses have even used robots to quickly train temp workers so that they could add value is added with minimal training. Mixed-flow production approach allows for flexibility in adjusting to demand fluctuations

9. Consistency/Speed

Robots never need to divide their attention between a multitude of things. Their work is never contingent on the work of other people. They won’t have unexpected emergencies, and they won’t need to be relocated to complete a different time sensitive task. They’re always there, and they’re doing what they’re supposed to do. Automation is typically far more reliable than human labor.

This guarantee of quality and consistency coupled with time and efficiency savings means that you can start developing higher quality and more feature-filled products with little or no increase in production time and costs.

10. Create major efficiencies. 

Efficiency by definition describes the extent to which time, effort and cost is effectively applied for the intended task or purpose. Process automation reduces the time it takes to achieve a task, the effort required to undertake it and the cost of completing it successfully.

Autonomous robots can test, pick, pack, sort, build, inspect, count, or transport materials of various sizes and weights faster and more efficiently than ever. Robots are designed on compact bases to fit in confined spaces. In addition to being mounted on the floor, robots can be mounted on walls, ceilings, rail tracks and shelves. They can perform tasks in confined spaces, saving you valuable floor space. 
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Drone technology combined with autonomous navigation and artificial intelligence is being used to understand inventory levels and location within warehouses and enabling organizations to move inventory faster throughout the supply chain. Investing in aerial robots redirects staff to handle high-value activities and empowering their teams with rich information, which can then be revisited at any point and time and can be used to make better decisions.

​Recent reports have concluded there are gaps in Multi-domain Logistics mechanics that compromise ability of the Joint Force ability to provide reliable, agile, responsive and survivable sustainment, causing senior leaders to ask how the Services are going to sustain itself and the joint force from fort to port to foxhole. 

It is imperative Services update robust Multi-Domain sustainment Logistics enterprise that can provide support over great distances in austere environments, both inter- and intra-theater, to prevail in conflict.

The strategic security environment described in the 2018 National Defense Strategy necessitates that DoD and the military services prepare for operations on a complex and multi-domain battlefield where business-as-usual Logistics can not be successful.

The Services response to this Logistics challenge is embedded in a concept called Multi-Domain Operations MDO.  MDO calls for the rapid and continuous integration of all domains of warfare to ensure we can deter threats and prevail in battle. 

Doing so first requires neutralizing adversaries’ anti-access/area denial A2/AD capabilities as forces deploy and then employ combat power Logistics into hostile environments. Threat A2/AD capabilities impede not only the mobility but also the sustainment of forces. 

By making sure Logistics can keep up with multi-domain operations, the adversary will not just be forced to contend with multiple competing dilemmas, but be brought to the negotiating table under optimal conditions

Pentagon vision of how it will fight in the future rests on the notion of the “dilemma.” Multi-domain operations as a concept proposes that the joint force can achieve competitive advantage over a near-peer adversary by presenting multiple complementary threats that each require a response, thereby exposing adversary vulnerabilities to other threats. It is the artful combination of these multiple dilemmas, rather than a clear overmatch in terms of any particular capability, that produces the desired advantage.

An exercise offered a glimpse of what the multi-domain operations concept will look in practice like when applied on the battlefield. The 1st Infantry Division, for example, achieved some success in its ability to rapidly erode enemy defenses through the integrated use of fires, aviation attacks, tactical deceptions, vertical envelopment by light infantry, and armored penetration.

These complementary tools, when applied rapidly and in close synchronization, exchanged mass for tempo and forced the enemy into multiple dilemmas across multiple domains. What follows is an explanation of how the division accomplished this, what we learned, and how we got better along the way.

Managing Risk in the Digital Battlespace

In our initial command post exercise, the division commander challenged us to reframe how we defined risk to the force. Received experience from previous Warfighter exercises suggested that the most dangerous of all courses of action in the face of this peer enemy would be to do nothing, or worse, to halt and await favorable conditions to be set while our very limited armor capability sat within range of the enemy’s long-range artillery.
 
In this fight, audacity—when properly seasoned with a prudent understanding of the risk—is a critical combat multiplier. Must decide up front “how we would enter the digital battlespace”; how we would identify its forward edge; and once in it, how we would proceed audaciously with the simultaneous commitment of all forms of contact that the division could generate. Once in the digital battlespace we realized that the most dangerous and risky thing we could do was to stop attacking.

This challenge is further complicated by the presence of underground facilities throughout the exercise’s area of operations. How troops effectively employed underground facilities to deny coalition forces what has traditionally been our greatest asymmetric advantage—the ability to shape and attrite OPFOR prior to the advance of the main body. We observed a very carefully calibrated set of triggers for the OPFOR decision to uncover its artillery from underground facilities and a period of extreme vulnerability as the OPFOR exited those facilities—often in single file. 

Our goal then was to ensure we were prepared to exploit this window of opportunity either with the timely application of attack aviation or through the insertion of light infantry forces who would then move, often many kilometers, to block the exits to these underground facilities at the opportune moment.

Purpose-Driven Operations

Operational frameworks are difficult to conceptualize, yet they are fundamental to a logical plan. Divisions utilized operational frameworks as a digital  tool to clearly visualize and describe the application of combat power in time, space, and purpose. It provided a logical architecture and foundation on which the subsequent detail, resource, permission, responsibility, effort, operation, concept, and task were built. Through a clearly articulated concept of operations, the division ensured that actions that it and the brigade combat teams executed were in pursuit of the commander’s end state.

During planning, dividing an area of operations into parts categorized as deep, close, support, and consolidation only explains the plan by time and space. Meanwhile, assigning operations as either decisive, shaping, or sustaining and units as the main or supporting efforts explains actions by purpose. Combining all three frameworks achieved what the division and brigade commanders needed: to explain actions and responsibilities in time, space, and purpose.

Presenting Multiple Dilemmas

In this particular Warfighter exercise, the division observed that the terrain limited options for ground maneuver. A single penetration, though conservative and often effective, would not achieve the commander’s intent. The penetration presents the enemy with one problem—a problem that other units have presented repeatedly. Dilemmas are not the same as problems. A problem is a situation regarded as unwelcome or harmful that must be dealt with and overcome. 

A dilemma, by contrast, is a situation in which a difficult choice has to be made between two or more alternatives, especially equally undesirable ones. To present the enemy with multiple dilemmas across multiple domains and in multiple locations, the division combined penetrations with audacious turning movements and tactical deceptions, complemented and reinforced with nonlethal effects.

The turning movements were achieved by conducting air assaults across the coordinated fire line and up to the fire support coordination line. To avoid enemy air defenses, these air assaults were often offset by several kilometers and at least a major terrain feature away from their intended target. 

The targets were often key points of overwatch for particular underground facilities suspected of housing long-range artillery, or points of domination that could cover major avenues of approach. Timely execution of these air assaults forced the enemy to divert resources and attention from the advance of our armored formations along heavily defended avenues of approach and thereby dislocated the main enemy defenses. 

In the cases where we were successful, the division forced the enemy to react to our operations and enter the fight on our terms. More importantly, we were able to achieve tempo not just through the sustained geographical advance of the forward line of troops, but by persistently presenting complementary dilemmas to the enemy in unexpected ways to diminish adversaries decision space and disrupted their understanding of its own plan. By the time the enemy observed and oriented on one dilemma, the division sought to present another, thereby causing the enemy to not render a decision on the initial dilemma.

Sustaining both momentum and tempo against a capable enemy required the division to reframe how we achieved synchronization during sustained and dynamic combat operations. Too often our decision-making process in combat operations mirrors the activity of a football team on the gridiron. In the midst of a long offensive drive, we seek to impose periods of planning i.e., the huddle, an approach march, a decisive operation where synchronization is optimized, and a culminating point that leads into a period of disengagement and another planning session. 

This “battle period” model, thankfully obsolete at our brigade training centers with the advent of open phasing, is equally inappropriate in a Warfighter exercise. Instead, we needed to think like a rugby team, where synchronization occurred rapidly and unexpectedly with fleeting moments of opportunity quickly identified and exploited by individual players who then become the supported effort as the team synchronizes around them. This required a different and more dynamic approach with near/long term tactical planning and targeting cycles all occurring constantly as conditions changed on the ground.

Simultaneity and Momentum

Conducted simultaneously, the penetrations, turning movements, and tactical deceptions enabled the division to achieve a degree of irreversible momentum against the enemy. The armor penetrations kept the enemy’s sensors engaged. The turning movements avoided the enemy’s principle defensive positions and seized objectives behind the enemy’s current positions causing the enemy to both dislocate from its positions and to divert forces to meet the threat. The tactical deceptions kept the enemy fixed on sizable threats, which influenced the enemy’s decision to prematurely unmask forces in sanctuary inside its underground facilities. 

Additionally, the combat aviation brigade was employed as an independent maneuver organization focused on destroying enemy high-payoff targets—in particular long-range artillery. Synchronizing all of these actions in time, space, and purpose became a tremendously complex task and the primary focus for the division main command post. 

We managed this effort with a centralized division synchronization matrix that was incredibly detailed, included all subordinate, adjacent, and functional unit actions, remained prominently posted on our current operations floor, and printed in placemat form at every major battle-rhythm event, especially the targeting working group and the target decision board. The synchronization matrix allowed us to forecast time out and visualize the timing of the dilemmas that would be presented to the enemy as we fought through the typical frictions of a large and complex operation.

Targeting and the Plan

The division ensured that the targeting process was nested within the plan and that the plan was flexible enough to adapt with the targeting process. From the beginning, targeting was aligned with the commander’s intent—to “cause the rapid erosion of the enemy’s defenses and will to fight.” 

The division’s targeting imposed the commander’s will, in the form of physical, temporal, and cognitive effects, on the enemy. The division simultaneously employed multiple defeat mechanisms to accomplish its mission, while at the same time removing the ability for the enemy to present dilemmas to the division. The targeting process integrated all warfighting functions, but specifically integrated the enemy plan, the maneuver plan, tactical deceptions, lethal effects, and non lethal effects to exhaust the enemy’s ability to make sound and timely decisions.

Targeting was assessment-driven, and therefore required specificity in information collection and analysis to evaluate the effects. In the deep fight, this process disintegrated the enemy—disrupting and degrading the enemy’s ability to conduct operations while leading to the collapse of enemy capabilities and will to fight. In the close fight, this process prevented the enemy from massing combat power in the battlespace.

Our experience in this Warfighter exercise confirmed practically the conceptually central idea of multi-domain operations—that competitive advantage emerges from the skillful integration of complementary capabilities, sequenced in time, space, and purpose to create multiple dilemmas for an adversary.

When we achieved this effect, we found success. When we failed, the very capable enemy we faced quickly overwhelmed and defeated our exposed forces. Presenting multiple dilemmas required the diivison staff to redefine its understanding of prudent risk and to develop a natural bias toward action rather than inaction. 

Once in the “digital battlespace,” the most dangerous and risky course of action was the failure to act. This required a very clear intent from the commander and a staff that could coordinate, integrate, and anticipate actions in time, space, and purpose, with higher, adjacent, and subordinate unit headquarters. 

Simultaneity across all domains and irreversible momentum can only be achieved through a well-trained and experienced team of teams. “Presenting multiple dilemmas to the enemy” is more than just a catchphrase. Achieiving it requires clear intent, a culture of empowerment, a capable staff, and a level of risk tolerance that many of us may be uncomfortable with. But, when properly and artfully executed it can yield a signficant competitive advantage on the modern battlefield that ultimately saves lives and produces decisive results.

New concept of warfighting has evolved into multi-domain operations and rapidly spread in conversation to the joint force. To take the concept beyond white papers and white boards, the Army has built a Multi-Domain Task Force, which recently saw its first field experiments.

The concept looks at how services will penetrate the more sophisticated defenses of adversaries and travel along the continuum of conflict while maintaining superiority and advantage. It means using longer range fires, better missile defense, an impenetrable network and highly refined small unit capabilities. And it means all of that in more domains at once than any commander has ever had to consider.

At some point, the task forces will simply dissolve into the way the Army does business. “You’ll have these capabilities at echelon throughout the entire theater.

In the near future even company commanders will become used to thinking in all domains and using data, high-performance computing, sensors, nodes, networks and firing platforms across all of the services.

You can’t effectively prosecute a campaign using MDO if it’s not joint. Different domains can be applied to create the window of opportunity. Imagine effectively securing airspace and waterways by long-range precision fires or air missile defense. It’s turning everything on its head.

It’s fair to say in the future MDO is at the tactical level. At the company and battalion level, it’s still about combined arms at the lowest tactical level. MDO just lets the maneuver force continue to do combined arms maneuver.

Now what will be distinct is reliance on the tactical level to think, assess and employ all domains when necessary.. So the thinking will be for tactical-level commanders to see opportunities for all domains to be integrated, or leverage the benefits of other domains in their tactical space. But in the end a battalion will maneuver like a battalion.

That makes operations more dispersed and leaders must call on support from a much wider area. Operational and theater-level commanders must compete daily to enable any kind of penetration or in order to enable conflict.

“What soldiers will see is after forces get out into theater and then geographic combatant commanders recognize the virtues that they bring to their capacity and as we learn and as we go through service wide analysis what you’ll see is that we’ll start building out those echelons we’ve talked about.

“You’ll need to have a theater fires command, you’ll need to have an operational fires command. You’ll need to have network capacity at echelon. You’ll need to have access to space assets at echelon.”

1. Feeds war fighter information necessary to orient structure of battlespace

2. Perspective gives ability to see and understand the competition 

3. Provides insight into battlespace from others’ perspectives 

4. Integrate information where and when it is needed,

5. Aggressive collection and sourcing of information to provide behavior context

6. Indivisible effects depend on ISR and integration.

7. ISR is domain-neutral ISR focused on capabilities and effects, not platforms

8.  ISR is operations—not solely support to operations

9.  Interoperability required for interservice effectiveness
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10. Provides ability for quick maneuver or action between domains