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Top 10 Examples of 3D Print Alternatives to Traditional Manufacturing Create Business Case for Design

10/22/2018

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3D Printing is set of manufacturing processes that progressively add layers of material to manufacture your products, and it could change the way you go about engineering your products. Instead of being held back by manufacturing constraints, you can design the component you need focused only on the function it requires to perform and meet warfighters needs.

You have full control over the interior structure of the part, so you can include voids, lattices, and other hard-to-manufacture structural components that can help cut down on material use and increase functionality. Subassemblies used to require multiple parts can be combined into a single component. You can customise everything you make to suit your individual customers preferences.

With all the recent innovations in the additive manufacturing industries, now is the time to consider additive as a viable alternative to traditional manufacturing approaches and how to best take advantage of the design freedom it offers.

What began as a rapid prototyping tool has now transformed into a multi-faceted manufacturing system capable of producing a wide variety of parts to functional specifications.

3D design data described in a digital file is used to develop a component by depositing materials — including metals, plastics, and composites — in layers. Technology and innovation are reshaping industries across the world at a breathless and breakneck speed. 3D printing or additive manufacturing is one technology that is set to revolutionised the aircraft industry.

Significant advances in the field over the past decade have transformed the design, development, manufacturing, and distribution processes in the sector, making ways for novel designs, lighter and safer products, shorter lead times, and lower costs.

3D printing has become the one of the most exciting prospects of the aircraft world, enhancing the functionality and value of existing products in every way. The concept seems new but has been around for more than 30 years. It involves a process where 3D design data described in a digital file is used to develop a component by depositing materials in layers. The materials used in 3D printing include a wide range of metals, plastics, and composite materials.

The additive manufacturing field is highly competitive and, therefore, large and small players in the space focus on specific capabilities that can lead to greater competitiveness. Some of these capabilities include fewer design restrictions and direct production of final components by eliminating the need for new tooling.

When you set out to design products, you typically have to design around the manufacturing process, which results in additional costs, time, or even material. Imagine being able to fully combine what was previously a set of subassemblies into one manufacturable part.

You have likely had to over-design certain parts to withstand common manufacturing processes, creating a dilemma that additive manufacturing can help you get around. When you design with additive manufacturing in mind, you can forget about designing for anything other than functionality. Looking deeper into this, you can save time in the design process while also saving money in manufacturing costs relative to design complexity.

As engineers, we’re always thinking of new ways to improve components and designs. We have all had amazing ideas, only for them to crumble with the realisation it would be nearly impossible to manufacture. With AM, you can enter the realm you previously thought impossible – releasing your full problem-solving potential. Design for manufacturability is a proactive process used to maximise the design of components for the intended manufacturing process.

Looking over the typical manufacturing processes of machining, casting, injection molding, and forming, we see the shortcomings in each technique. When you design with injection molding, you are bound by many limitations, from quality assurance to assembly issues.

In addition to being limited to solid components, you are also limited by shapes and designs of parts to allow for mold separation. However, what if you don’t need a solid structured part or need one with a complex shape? With previous forms of manufacturing, you would be kind of stuck; but not with additive.

Let’s look to machining, one of the many great forms of manufacturing, yet full of limitations. When your part is being machined, there is room for operator error and you are limited in degrees of freedom from the machining head. While you can generally design around these constraints, why do it when you don’t need to?

Each manufacturing process you want to use requires that you have some knowledge of how it works when you design a component. All the time you spend learning how a manufacturing machine works could be spent improving your original design.

In situations where additive is applicable, it can compensate for many of the downsides of traditional techniques. You may also want to focus on improving the design and functionality of a part, but given time constraints you may not get a chance. Eliminating constraints in a project allows for you to focus your energy into actually improving your designs, rather than hassling with manufacturing.

While focusing on manufacturability may decrease cost, you can significantly increase value by focusing on improving design and functionality. Compromising on design just to make a product manufacturable hurts both the engineer and the integrity of the end product.

Perhaps the key aspect of additive manufacturing and what makes it the perfect fit for your possible needs is its ability to produce fully functional products without manufacturing setbacks. 3D printing overcomes traditional constraints and pushes you completely into designing for functionality. and passing test/evaluation benchmarks

There are obviously material limitations, but where it’s applicable, it can help out in your design process significantly. Since you have more time to focus on design and functionality with additive manufacturing there is a whole new array of opportunities that have never existed before, improving function. You now have options.

Your specific computer programmed design has its limits, but additive can push beyond them. For example, modeling latticed structures can be time-consuming at best. With many additive techniques, you can actually manufacture more complex parts and automatically pinpoint areas where material is unnecessary, and either remove it altogether or easily replace it with a complex lattice structure.

3D printing isn’t just about increasing the time you can spend on design, it’s about being able to manufacture beyond what you can currently easily design. It creates true design freedom.

Instead of creating complex subassemblies through multiple designs, you can focus on the function of your component.

Additive manufacturing requires absolutely no tooling, so the end product can be exactly what is needed to satisfy your customer. Instead of needing to compromise on certain specified design criteria due to manufacturing capabilities, additive manufacturing allows engineers to solve problems without constraints.

Whether you’re talking to your board of directors or your line manager, switching gears out of engineering mode to make a business case can be tough, especially when it comes to justifying a major capital expense.

It takes more than great specs to persuade senior executives to invest in new equipment, and with the rapidly changing pace of manufacturing, simple cost-per-part estimates don’t always illustrate the full benefits of acquiring new production technology.

3D printing or—when it’s referred to as a production technology—additive manufacturing is a great case in point. Traditionally, people equate a business case with the cost model of a part. So relative to a conventional part, the additive part is either more expensive or less expensive. And that’s the business case for a lot of companies. But it’s definitely not for additive manufacturing—we think it’s a lot more.”

Making a business case for additive manufacturing can be challenging. It’s still a relatively new technology and while 3D printers have been around for more than thirty years, many decision makers in manufacturing have been around longer than that.

Additive manufacturing also has a reputation as being good for prototyping, but unable compete on production applications compared with more traditional technologies, such as injection molding and computer numeric control machining.

Good business cases incorporates three components; a cost model, performance factors and supply chain disruption. A cost model represents the production part, tooling and infrastructure costs for a component. Business cases that focus on this aspect alone are typically not as successful as those which include these other factors.

Performance factors quantify the system-level benefits or impacts of a component or product in terms of their lifecycle costs. Supply chain disruption refers to innovative strategies for overcoming existing “pain points” within your business.

Seeing additive manufacturing from this broader perspective should make it easier to put together a business case for it, but you still need to do the actual legwork.

So, how do you make a business case for additive manufacturing? Defining a business case for additive manufacturing begins with understanding the cost distribution for the part being considered.

More broadly, it’s important to ask where most of your manufacturing costs are today.

If they’re concentrated in labour, materials or post-processing, you could potentially argue that using 3D printing would help drive those costs down, though the justification may not always be obvious.

For example, although materials for additive manufacturing may be pound-for-pound more expensive than their subtractive counterparts up front—consider the cost of a block of aluminum versus the equivalent mass of aluminum powder—they are also subject to considerably less waste.

In addition, the design freedom that comes with using additive manufacturing may allow you to reduce the amount of material that goes into each part, and cost of materials. The second component to designing a business case for additive manufacturing is identifying your desired part performance factors. during test/evaluation period.

In other words, what benefits can you point to that additive offers over traditional manufacturing processes?
If your application is in the aerospace industry, you can always point to the capability to produce lighter and stronger parts with additive manufacturing.

Once you’ve come to grips with your cost distribution and desired part performance factors, the next question to ask is, “What can you do to disrupt your supply chain? Maybe you have a part that is chronically on back order, Maybe you haven’t been able to negotiate with a supplier because you’ve been locked into their process for so long. That’s what we call supply chain disruption.”

In addition to disrupting your supply chain, additive manufacturing can also create new opportunities for growth. For example, additive could enable you to manufacture highly customised products or bring your parts to market faster.

“The business case is the sum total of all these factors and considerations. The fiscal values for some of these factors are obvious. If you can cut down on lead time or reduce the number of operations you need to make a part, the savings are straightforward. But consider part consolidation. What is the value proposition on reducing the number of parts in an assembly? Or what is the value of having the capability to consolidate parts in future assemblies?

As difficult as it may be, when defining a business case, it’s important to remove your engineering hat. You can talk about delamination and porosity until you’re blue in the face, but sometimes it all comes down to dollars and cents. Some parts will benefit from being additively manufactured, others will not. Of course, there are many cases where it’s obvious which parts you should and shouldn’t print.

Is your design prohibitively expensive—or even impossible—to machine? Then it’s probably a good candidate for additive manufacturing. Is this a high-volume application? Then you might want to explore injection molding.

Making a business case for implementing additive manufacturing in production goes beyond looking at discrete parts. “With 3D printing, you can look at parts as a system, rather than as individual pieces. You can combine multiple parts together or add functionality—things we could not have done with conventional manufacturing.”

For this reason, simple cost-per-part calculations are unlikely to yield accurate numbers when making a business case for additive manufacturing as a production technology.

If you look at a single part in isolation, producing it additively may be more expensive. However, if you look at it as part of an assembly and consider the new design options that additive opens up, then those numbers could be quite different.

“We have developed training programmes based on our own use of additive manufacturing . “What we don’t know are the requirements each customer has for their parts. They are of course the experts in their own parts, so by putting these two elements together, we think you will be able to rapidly accelerate customer additive prospects.

Additive Manufacturing Use Cases

One of the best examples of the benefits of additive manufacturing comes from one of the most famous parts in the aerospace industry:  the additive fuel nozzle for a jet engine.

“Part consolidation came from looking at this in terms of a system. But when you have a part that’s five times as durable, customers will absolutely pay to maintain and service that part much less frequently.”

Additive manufacturing has reduced the weight of fuel nozzle by 25 percent. The benefits to weight reduction in aerospace applications include the ability to add new functionalities, carry heavier payloads or extend your range. Then there’s the cost. This part is less expensive than its predecessors.

A second example comes from replacing the structural castings on an engine with additive components. “By going additive, we shortened overall engine development time—almost cutting it in half—because we didn’t have to wait for tooling. Tooling can often be a chokepoint in development and manufacturing. The efficiency gains from being able to do without it should not be underestimated. The extra capital that comes from not needing tooling is able to be redirected to other efforts.

“We were able to invest in developing the heat exchanger by freeing up funds that had previously been used for structural castings and tooling. If you only need to spend a quarter of what you used to in development costs, you can do four separate parts for what you used to pay for one.”

As with any disruptive technology, new users often have trouble identifying the return on investment because they don’t appreciate the full extent of what it can do. Consider taking advantage of all the available resources and experts to help you navigate from business case to qualification and everything in between.

Additive manufacturing is well suited for many applications where parts are needed that simply can’t be easily produced using other methods like machining or injection molding.

One method uses a printhead that works on a level flat printing surface by laying down the choice of conductive chemical or material. This functionality is very similar to the way additive manufacturing works and it allows for fast production of custom circuit boards. Given the current way that circuit boards are mass manufactured, this additive technique makes possible one-off iterated designs.

3D printed circuit board technology uses an extruder head that can lay down beads of solder or conductive material on a printing surface in layers. Couple this “wire printing” method with a secondary material head, and manufacturers are slowly gaining the ability to create 3D printed circuit boards with intricate internal wiring.

Having the ability to design 3D connections in compact spaces is something that is otherwise impossible within the ways that circuit boards are currently produced. With 3D printed circuit board manufacturing, a drastic change in how electrical engineers see and build projects is beginning to form.

The current state of the additive manufacturing industry lies mostly with mechanical engineers and makers alike. 3D printing and other additive techniques allow engineers to rapidly prototype a given mechanical component or assembly. Even with all of the advancement that has surrounded this industry in recent years, it’s still early in development.

It’s important to point out that there are a few methods that allow for 3D printed circuit boards and are simultaneously fighting to become industry standards. But the world of 3D printed circuit boards can get a little more complex in both extrusion and material methods.

Conductive gels are used as well as embedded copper filament. Some machines utilise graphene substrate printing and on the cutting edge of experimentation, there is even conductive aerogel printing. Each of these various printing methods is undergoing extensive research in their practicality and usability. The idea of manufacturing circuits in this form will change how engineers think about electrical design.

This new manufacturing technique, like most new tech, won’t be a solution to all the electrical engineer’s problems, but these techniques will certainly emerge in the future.

There is a small niche in large-scale manufacturing that could allow for circuits to become integrated into materials. But as you can probably guess , any large scale industry adoption of 3D printed circuit boards is far off.

The most drastic way that we’ll see change is in the world of the makers. Production of machines capable of rapid-prototyping circuits will alter the art of the possible. Engineers may soon be able to rapidly prototype a circuit board without dealing with the harsh chemicals necessary with printed circuit board manufacturing.

As additive manufacturing and electronics continue to be merged together, the excitement around the tech will grow. This all means that soon we may be able to print and prototype not only mechanical parts from our desktop, but also integrated electronics parts. We’re beginning to see the push to rapidly prototype virtually anything… and this capability could radically alter our training jobs The next age of rapid manufacturing is approaching fast.

Additive manufacturing is well suited for many applications where parts are needed that simply can’t be easily produced using other methods like machining or injection molding.

On method uses a printhead that works on a level flat printing surface by laying down user choice of conductive chemical or material. This functionality is very similar to the way additive manufacturing works and it allows for fast production of custom circuit boards. Given the current way that circuit boards are mass manufactured, this additive technique makes possible one-off iterated designs .

3D printed circuit board technology uses an extruder head that can lay down beads of solder or conductive material on a printing surface in layers. Couple this “wire printing” method with a secondary material head, and manufacturers are slowly gaining the ability to create 3D printed circuit boards with intricate internal wiring.

The advantage to this technique is that a given circuit isn’t constrained by the traditional flat printed circuit board , and can be made to perfectly fit the shape of a given product. Having the ability to design 3D connections in compact spaces is something that is otherwise impossible within the ways that circuit boards are currently produced.

With 3D printing circuit board manufacturing, a drastic change in how electrical engineers see and build projects is beginning to form.

The current state of the additive manufacturing industry lies mostly with mechanical engineers and makers alike. 3D printing and other additive techniques allow engineers to rapidly prototype a given mechanical component or assembly. Even with all of the advancement that has surrounded this industry in recent years, it’s still early in development.

It’s important to point out that there are a few methods that allow for 3D printed circuit boards and are simultaneously fighting to become industry standards.

The world of 3D circuit boards can get a little more complex in both extrusion and material methods, however. Conductive gels are used as well as embedded copper filament. Some machines utilise graphene substrate printing, and living on the cutting edge of experimentation there is even conductive aerogel printing.

There is a small niche in large-scale manufacturing that could allow for circuits to become integrated into materials. But as you can probably guess, any large scale industry adoption of 3D printed circuit boards is far off. Each 3D printing method is undergoing extensive research in their practicality and usability. The idea of manufacturing circuits in this form will change how engineers think about design.

Additive manufacturing and 3D printing have already changed the way that we think about manufacturing. This technology that appeared to be overhyped at first is now carving out its own developed sector in the manufacturing industry.

New manufacturing tech won’t be a solution to all the difficult problems engineers face. 3D printing techniques will also make an emergence in the following product areas primed for future field use:

1. 3D Printed Antennas

The plastic antenna panel and the embedded dielectrics are printed in one go. Rather than trucking or airlifting in antennas for the growing number of connected devices that are appearing on the battlefield, DoD is studying ways to print dielectric antennas, even from non-conductive materials like ceramic or plastic, directly on location. Researchers are working on several different approaches for 3D printing high-frequency circuits and electromagnetic devices.

2. 3D Printing Composites for In-Field Use

3D printing process being developed based on the use of composites, where scientists can engineer advanced composite cement, fiber-reinforced polymers, metal composites and composite ceramic and metal matrices: all of which can be tailored for use in the field.

3. 3D print Biometric Sensors

Like 3D printing antennas, being able to 3D print multi-material electronic circuits opens up the potential for several different applications for “future warfighters”. Researchers at have long envisioned the potential to embed a radio antenna on the side of a soldier’s helmet, or 3D print sensors that monitor status directly onto a weapon or an article of clothing, such as a combat boot.

4. 3D Printed Beachheads with Local Materials

Robot capable of 3D printing objects independently, from materials found on location: We drop a black box in a place where you wouldn’t want to send your soldiers. It could be a dense jungle, the top of a mountain, a dangerous extreme environment, etc. Through a suite of sensors, this manufacturing unit senses what’s around it, what minerals are in the sand, and what trees are around it. It then prints robots to go collect those materials, to collect sap from trees, mud and straw to make bricks. These robots bring those materials back.”

5 3D print Micro Assembly Robots

Magnetically Actuated Micro-Robots for Advanced Manipulation Applications will be used to build smart structures with high-performance mechanics. Thousands of micro-robots manufacture high-quality macro-scale products while providing millimeter-scale structural control. For example, some micro-robots will carry electronic and mechanical components. Some micro-robots will deposit liquids, and others will perform in-situ quality analysis. Mounted to a mobile robotic base, a micro-factory will be able to build parts of practically any size. The micro-robots themselves could also be 3D printed.

6. 3D Printers at Sea

Navy has permanently installed a 3D printer on a warship for the first time. However, the printer aboard the amphibious warship is not used for building replacement parts. The crew has been making many useful things, like a new cap they designed for an oil tank, to model planes to move around their mock-up of the flight deck.

7. 3D printing Metals

Open Manufacturing programmes seek to speed up adoption of metal additive manufacturing for end-use components. While test parts for jets have been developed they are not yet approved for in-flight use.

8. 3D Printing Equipping Prototype

9. Rapid Equipping Force 3D design a prototype solution and upload it to provide inspiration for workshops where Troops will bring virtual blueprints to life by manufacturing 3D prototypes using Expeditionary equipment.

9. 3D Printed Uniforms

Through 3D printing, DoD is studying ways to combine different advanced materials, reduce the number of seams for added comfort and durability, and even create embedded ballistic sections into a single piece of clothing. One alternative and futuristic approach is the Tactical Assault Light Operator Suit.

10. 3D Printed Food

DoD is considering using a 3D printer to make the soldiers’ chow.
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Top 100 Factors Considered When 3D Print Products Subject to Operational Test/Evaluation Process

10/22/2018

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Military doesn’t usually disclose its current and real capabilities. On the other hand, they do like to talk about future possibilities and the research they’re conducting on long-term projects.

Leaders have sketched out a variety of potential uses for 3D printing for the military.

These range from intelligence to communications, and even to terraforming the battlefield, along with a few other future applications for the military force of tomorrow.

New threats demand logistics command-and-control capabilities that emphasise speed and agility. Agile manufacturing technologies, such as additive manufacturing, enable speed and agility. These technologies support Future Operating Concept by providing DoD with competitive edge against our adversaries through a smaller deployed footprint, more agile/efficient maintenance and modification, and faster supply-chain resourcing.

While additive manufacturing presents itself as a viable solution to rising costs associated with diminishing manufacturing sources, the process requires a rapid reverse-engineering capability and a workforce that understands how to leverage it in order to provide a responsive, resilient parts supply chain.

Leveraging new manufacturing technologies, such as additive manufacturing, results in a more agile and efficient logistics supply chain that can quickly deliver the right part on demand, but it also induces risk to the war fighter as we strive to secure our gains.

In terms of specific initiatives to improve service-wide logistics, additive manufacturing is playing a large role. DoD has been pursing this for some years and still has work to do, Advancements in 3D printing allow the force to not worry about the supplying and ordering of parts cutting out the supply chain and reducing timelines for making parts.

The next phase for the service in terms of additive manufacturing is mainstreaming the process, which means transitioning from plastic parts to metal. Plastic works really well, but we don’t want to replace all aircraft parts with a piece made out of plastic.

While the Defense Department is interested in additive manufacturing, particularly downrange in operational scenarios where certain items might be harder to acquire, more work needs to be done by industry to certify 3D printed parts by rigorous test/evaluation criteria to prove parts can stand up to the stresses of military use.

Suppliers are developing “hybrid” applications, where 3D printing and traditional manufacturing techniques like forging are both used to make a qualified part. This technique is attractive for both the commercial and defense aerospace markets that need qualified parts but want to reap the benefits of 3D printing.

It’s hardly a new technology at this point, but two things have changed for how DoD looks at the potential of 3D printing. The first is that the technology has become more widespread and adopted across the Pentagon. Where even a few years ago there was resistance to the idea a 3D printed part could be as reliable as a classically forged piece, there is now acceptance that parts printed via additive manufacturing can become secure and stable as long as test/evaluation steps are met.

Subassemblies used to require multiple parts can be combined into a single component. You can customise everything you make to suit individual customer preferences. With all the recent innovations in the additive manufacturing industries, now is the time to consider additive as a viable alternative to traditional manufacturing approaches and how to best take advantage of the design freedom it offers.

When you set out to design products, you typically have to design around the manufacturing process, which results in additional costs, time, or even material. Imagine being able to fully combine what was previously a set of subassemblies into one manufacturable part.

You have likely had to overdesign certain parts to withstand common manufacturing processes creating a dilemma that additive manufacturing can help you get around. When you design with additive manufacturing in mind, you can forget about designing for anything other than functionality. Looking deeper into this, you can save time in the design process while also saving your client money in manufacturing costs relative to design complexity.

With 3D printing, you can enter a world you previously thought impossible – releasing your full problem-solving potential. If you want to make internal voids or complex lattice structures, there’s a form of additive manufacturing that can make it happen. The freedom and potential you can have in your future designs are immense if you cast off all design limitations. The path for design without limitations can be paved with 3D printing, although it can have some material and production limitations.

You may want to focus on improving the design and functionality of a part, but given time constraints and the need of Design for manufacturability, you may not get a chance. Eliminating Design for manufacturability in a project allows you to focus your energy into actually improving your designs, rather than hassling with manufacturing.

While focusing on manufacturability may decrease cost, you can significantly increase value for the client by focusing on improving design functionality. Compromising on design just to make a product manufacturable hurts both the engineer and the integrity of the end product.

Perhaps the key aspect of additive manufacturing and what makes it the perfect fit for your needs is its ability to produce fully functional products without manufacturing setbacks. 3D printing overcomes the drawbacks of Design for manufacturability and pushes you fully into designing for functionality. There are obviously material limitations, but where it’s applicable, it can help out in your design process significantly.

Since you have more time to focus on design and functionality with additive manufacturing , there is a whole new array of opportunities that have never existed before. If you want to significantly improve function, you now have options.

By using computer assisted 3D printing tech, you can automatically pinpoint areas where material is unnecessary, and either remove it altogether or easily replace it with a complex lattice structure. Additive manufacturing isn’t just about increasing the time you can spend on design, it’s about being able to manufacture beyond what you can currently easily design. It creates true design freedom.

You can virtually eliminate the need for subassemblies with 3D printing tech. You have the capability to consolidate all of your parts into one design and one production batch. Other than decreasing design time, you can increase your material strength and decrease component fatigue all through additive manufacturing consolidation.

Consolidation is one of the key areas you can focus on to reduce manufacturing costs, part complexity and even reduce failure points. When you combine all needed functionality into one easy-to-manufacture solid component, nearly all of your design criteria are optimised.

You can only customise a part up to the extent that your manufacturing process allows. There’s a gate that gets unlocked by additive manufacturing, which allows you to fully customise your parts.

If you’re an engineer, your head might start hurting a little when you hear the phrase “customer preference.” Customers can be some of the most demanding people you will work with, but after all, that’s where your paycheck comes from. Currently, when a customer comes to you with certain preferences, you feel additional pressure from what is capable of being machined or forged.

Additive manufacturing solves this, allowing you can start focusing solely on making the customer happy and designing a good part. You can optimise your components however you want, and create the part exactly to the functionality the customer wants.

Computer assisted design forms the basis of most engineering professions, and it is perhaps the key aspect of your everyday job. Whatever design tools you use, there is one out there that is optimised and perfected for every form of additive manufacturing. When designing a very complex part, you may struggle with how to optimise your Computer assisted design tools to create such designs.

Many programs have become tailored or are directly compatible with additive techniques like laser sintering and 3D printing. This allows you to design your part in Computer assisted design like anytime else, then simply export your design to manufacturing. The result is both instant and perfect.

When a component is topologically optimised, it ends up looking far more organic than would be easily-designed in many Computer assisted design software. With the advancements in organic Computer assisted design abilities, you can actually use natural flowing structure for functionality rather than simply how attractive the part is.

You can test your Computer assisted designs and optimise them for handling actual stress and strain that are key components to test/evaluation phase of the project. The process as a whole ensures your parts are strong, but removes virtually every bit of unneeded material, saving both you and the client a lot of money in possible excess material costs.

Structures within the same external dimensions of a part end up becoming organic flowing supports instead of geometrical shapes like commonly seen in traditional designs. This technique is unique to additive manufacturing, and it allows you to design for real-world stress conditions. It is a pain to design using organic structures, as we all know. The key is to understand that advances in Computer

As engineers, we constantly try to mimic and recreate real-word examples of design. Generative design is exactly that, and through additive manufacturing, it can become a relatively easy reality. There are many generative design programs where engineers can input constraints and Computer assisted design will develop organic and perfected structure.

Generative Computer assisted design tech iterates each design automatically until the generated structure is organically perfect for your design needs. It does the work that used to take days or weeks of test/evaluation in just a few minutes.

By saving time and money, boosting creativity, and integrating beautiful geometry, generative design may be exactly what you need to impress your boss. You now have the ability to do weeks’ worth of intensive engineering in no time, which is something to consider when weighing design options.

The drive to push 3D printing into the field is getting a boost from an unexpected source — artificial intelligence that can monitor robots and teach them how to do a better job.

One thing about aircraft—especially ones that fly from aircraft carriers where they are battered by saltwater and tough deck landings is that they need lots of spare parts that are not always on hand.

Instead of flying in new parts, future Navy ships may be able to make new ones to order. Picture an intelligent, laser-wielding robot that can assess the damage and 3D print required titanium alloy parts from an onboard supply of metallic dust.

This is one glimpse of the future proposed by the Office of Naval Research which awarded a contract to create a new generation of super-smart 3D printers. The printers would not only make parts on order wherever they are needed, but can observe, learn and make decisions by themselves.”

The team is starting with a common titanium alloy used in aerospace. If the project succeeds, it could demonstrate how artificial intelligence could change everything you know about manufacturing.

It’s easy to see how manufacturing new parts on the spot could change the game for the. Navy. But there’s a problem uncovered with 3D printing test/evaluation that limits its use with machines that endure extreme stress like aircraft,

Consider the materials themselves. Aerospace-grade metals, including several recipes of titanium alloy, are supplied by foundries and have well-known characteristics. This raw metal comes with guaranteed strength, porosity, and thermal tolerance characteristics.

Not so with 3D printed metal, which is made layer-by-layer on the spot. What engineers call the microstructure of the metal, meaning the size, shape, and orientation of the grains, for example, is not guaranteed from a 3D printed metal part. That piece could look identical to a traditionally manufactured one but perform differently.

“With traditional, subtractive manufacturing you have the same properties in the final part. “But with additive manufacturing the material and mechanical properties are not as well understood.”

But Navy has a plan to outfit the 3D printing robot arms with commercial sensors, hoping to create a database that ties 3D printing processes and conditions with the resulting microstructure with predictive models that will enable 3D printing machines to create parts with foundry consistency, but from anywhere. “We have to build quality into the part.

This is where artificial intelligence comes into play. Machine learning tech allow these 3D printers make adjustments on their own to match the material qualities the military is looking for.

It’s manufacturing by wire: Simply provide the shape and needed performance properties of the metal, and the 3D printer will take it from there. In other words, the printers will train themselves to make decisions on how to build things.

“When you can trust a robotic system to make a quality part, that opens the door to who can build usable parts and where you build them. A fleet of future Navy ships could learn from each other’s experience by feeding the data from each robot back to a central station “The project with is at the inception of this.”

Artificial Intelligence 3D printers open up new ways of building things, saving money on launch costs and nearly impossible quality control.

“It could enable on-site manufacturing, “Think about the freedom additive manufacturing might enable when you can trust the certification of material properties enabled by the following system test/evaluation process:

1. Effective systems must be suitable

2. Suitability issues with the highest risk must be identified

3. The operation scenario drives suitability demands

4. Terminology must be consistent

5. There are always limitations to operational testing

6. Operational suitability applies to each level of support

7. Operational suitability has many dimensions

8. Availability is critical characteristic must be considered in early planning process

9. System availability is difficult to measure during short operational testing periods

10. Operational test planning must address methods of measuring times for evaluation period

11. System standby time may be important

12. Realistic logistics support must be objective in planning for operational testing

13. Reliability parameters must be defined early in programme

14. System operating modes can drive reliability

15. Firm reliability requirements are essential

16. Reliability measurements can require lengthy testing periods

17. Assumptions are made in reliability test planning

18. Early operational testing may give first realistic view of system reliability

19. Reliability measurements can have statistical confidence calculations

20. Computer program reliability is always an issue

21. Reliability growth is usually important factor

22. Maintainability measurements requires reasonable number of maintenance events

23. Maintainability demonstrations can be used in operational testing if realistic

24. Built-in test equipment & diagnostic systems must be tested record false alarm rates

25. Routine scheduled or preventative maintenance must be examined during operational testing

26. Time for off-equipment repairs can be significant

27. Unique maintainability characteristics must be identified an included in operational testing

28. Supporting/companion systems must be identified in early versions of test/evaluation plans

29. Consideration of Supporting/companion systems must address other systems under development

30. Maturity of Supporting/companion systems must be understood

31. Determination of adequate suitability depends on performance of support systems

32. Interoperability problems may cause system limitations

33. Interoperability must be addressed in operational testing prior to planning

34. Developmental testing results may help focus planning

35. Early operational testing may indicate unforeseen compatibility problems

36. Nominal operations may not expose incompatibilities

37. Operational testing tech must address needs for special resources/systems requirements impact compatibility problems

38. Compatibility of procedures can be factor in system performance

39. Early integrated logistics support planning for critical systems must be assessed

40. Part of logistics supportability evaluation includes system performance

41. Logistics support can provide basis to assess planned services

42. Test planning must address support for items under test

43. Operational test metrics should be compared to logistics support planning factors

44. Supportability of tech application must be considered

45. Supply support during operational testing may be unrealistic

46. Unique transportability requirements must be identified

47. Transportability of system must be verified as part of operational testing

48. All projected areas of operation must be considered in transportability assessment

49. Transportability must include movement of the system into combat locations

50. Testing of systems after transport can be critical for some systems

51. Documentation must be available for operational test phase

52. Documentation may not be available for operational testing schedule

53. Assessment of Documentation may be in a separate test phase

54. Only a sample of the operational maintenance and support tasks may be addressed

55. Support Task documentation may be occurring in operational testing

56. Manpower supportability includes observation of operating crew

57. Manpower deficiencies may reside in other suitability areas

58. Skill levels and numbers may be hard to evaluate

59. Proper manning levels for systems are critical for efficient operations

60. Operational testing experience can be used to modify training requirements

61. Operational test planning must address when the training programme will be available

62. Inter-relationship between training, documentation and personnel factors must be recognised during operational test planning

63. Training and operational testing tasks must be correlated

64. Demanding tasks that caused workforce problems must be identified

65. Usage parameters must be fully defined

66. Usage rates should be developed with new system capabilities taken into account

67. Operating tempo during operational testing must be developed from planned usage rates

68. Operational testing may be incapable of directly demonstrating surge usage rates

69. Some evaluation of system capability to perform must be made at planned surge usage rates

70. Planning for modeling and simulation must be evaluated for potential credibility of results

71. Detailed descriptions of planned operating and support scenarios are essential

72. Latest programme information must be incorporated into support activities

73. Defined plans for the use of support must be presented in test/evaluation plans

74. Test/evaluation documentation must include model rationale

75. Test/evaluation models must be planned for suitability assessments

76. Approach to system diagnostics should be included in early system planning

77. Firm diagnostic requirements must be established early

78. Diagnostic shortfalls must be evaluated for total impact on system and support resources

79. Diagnostic shortfalls may be obscured by activities in other suitability areas

80. Indications of poor on-board diagnostic systems performance early in programme must be followed closely

81. Lack of diagnostics performance can lead to major suitability problems

82. Common problem with diagnostics is immaturity at early stages of operational testing

83. Automated diagnostics capability of system usually improves as system design matures

84. Poor diagnostics performance can have serious effects on system suitability

85. Operational scenarios must always be quantified and understood

86. System requirement documents should include assessment of operating scenario

87. Limitations to system operation and/or maintenance should be projected prior to operational testing

88. Evaluate how workforce operating/maintaining system will be affected by operating scenario

89. Systems with on-board sensors can have limited performance in some operating scenarios

90. Accurate operational scenario conditions at operational testing sites are usually limited

91. Operational testing is usually not performed outside system intended operating scenario boundaries

92. Operational testing may determine additional conditions limiting operational scenarios

93. Complimentary systems and unusual conditions must be included in assessment

94. Application documentation can be key to effective support

95. Maintainability of application depends on design and arrangement

96. Interface application issues present can be critical to system operation

97. Ability to maintain/modify application depends on presence of adequate support resources

98. Maturity of application can be evaluated by examining status errors

99. Faults found in status of individual corrective actions are important

100. Application maturity depends on testing exposure


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Top 100 Aircraft Sustainment Factors Impact Service Life Extention Challenges Improve Readiness/Availability

10/15/2018

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While sustainment strategies do not guarantee successful outcomes, they serve as a tool to guide operations as well as support planning and implementation of activities through the life-cycle of the aircraft. Specifically, at a high-level the strategy is aimed at integrating requirements, product support elements, funding, and risk management to provide oversight of the aircraft. For example, these sustainment strategies can be documented in a life-cycle sustainment plan, postproduction support plan, or an in-service support plan, among other types of documented strategies. Additionally, program officials stated aircraft sustainment strategies are an important management tool for the sustainment of the aircraft by documenting requirements that are known by all stakeholders, including good practices identified in sustaining each aircraft.

1. Key support program elements include developing support equipment and technical data, testing requirements for avionics, and facilities requirements

2. Experiencing maintenance and supply issues. actions to mitigate these challenges include waiting for available space at depots and cannibalizing parts— moving parts from one aircraft to another

3. Maintenance challenges include whether the maintenance occurs in close proximity to the squadron, capacity of depots, and personnel

4. Shortage of depot and field maintenance personnel due to attrition, inability to find skilled workers, and a hiring freeze.

5. Ongoing and planned actions include establishing additional maintenance support for a number of systems such as the electronic warfare system and the generator control unit

6. Increasing the available depot maintenance spaces, training depot and field maintainers to be proficient in repairing parts of the aircraft outside their assigned position; and allowing depot and field maintainers to work overtime to keep up with maintenance schedules.

7. Experiencing shortages of parts because , it takes a long time to repair parts. Also, contractors are no longer producing some of these parts

8. Ongoing and planned actions include locating another vendor source, reverse engineering, cannibalizing parts i.e., removing serviceable parts from one aircraft and installing them in another aircraft, or waiting until the part is available

9. Unit manpower, operations, and maintenance costs have decreased, partly because permanently transitioned out of service

10. In-Service Support Plan documents the engineering, logistics, and financial resources necessary to ensure continued readiness and supportability for the remainder of the aircraft’s service life

11. Aircraft are maintained organically under planned maintenance intervals

12. Extend the service life flight hours by inspecting and repairing airframes, and replacing major components and parts

13. Actions to mitigate these challenges include extending the service life of the aircraft, allowing maintainers to work overtime to reduce backlog, and cannibalizing parts—moving parts from one aircraft to another

14. Cost of depot-level reparables is the most significant contributor to maintenance costs, averaging while the “other” maintenance accounted for the smallest share of maintenance costs

15. Ongoing and planned actions include extending the service life flight hours through its replacing major components including the landing gear—to increase the service life of the aircraft, and moving aircraft between squadrons to meet the requirements of deploying missions.

16. Requiring additional maintenance for repairs that were not originally planned, such as repairs for corrosion, and maintenance activities are taking longer to perform.

17. Shortage of depot and field maintenance personnel because of attrition, inability to find skilled workers, and a hiring freeze

18. Ongoing and planned actions include: training personnel on prevention and mitigation efforts for unplanned maintenance, such as corrosion

19. Identifying all parts and components that need to be repaired and replaced during the inspection phase

20. Training depot and field maintainers to be proficient in repairing parts of the aircraft outside their assigned position, as well as allowing depot and field maintainers to work overtime to keep up with maintenance schedules

21. Experiencing shortages of parts because vendors are no longer producing these items

22. Ongoing and planned actions include identifying alternate vendors

23. Reverse engineering parts, cannibalizing parts i.e., removing serviceable parts from one aircraft and installing them in another aircraft and waiting until parts become available

24. Training maintainers to transition to vacated positions, and cannibalizing parts—removing parts from one aircraft to another

25. Increases in maintenance costs can be attributed to the high operational tempo of the aircraft requiring additional maintenance repairs, which is taking longer to perform

26. Cost of depot-level reparables is the most significant contributor to maintenance costs while the “other” maintenance accounted for the smallest share of maintenance costs

27. Ongoing and planned actions include plans to extend the service life to increase its flight hours through modifications, repairs, and inspection

28. Monitoring depot induction flows, and obtaining contractor support to assist with initial program challenges, including knowledge, skills, and facilities.

29. Shortage of depot and field maintenance personnel due to attrition, inability to find skilled workers, and hiring freezes has caused maintenance backlogs

30. Ongoing and planned actions include corrosion prevention efforts, such as a corrosion-resistance initiative and corrosion action teams to identify corrosion early in the inspection phase

31. Depot and field maintainers trained to be proficient in repairing parts of the aircraft outside their assigned position

32. Allowing depot and field maintainers to work overtime to keep up with maintenance schedules

33. Experiencing shortages of parts that suppliers are no longer producing. suppliers are slow, which increases maintenance wait times

34. Maintenance costs have generally increased due to the increase in contractor logistics support.

35. While depot inductions were down, the time the aircraft spent in depot increased, which caused the cost increase

36. Ongoing and planned actions include implementing corrosion plan revised to military standards and contracting for corrosion-specific engineering assess

37. Contractor commercial-based maintenance plan, which does not focus on long-term structural issues that require inspection and maintenance, instead of a military-based plan

38. Current plan has inefficiencies in discovering and repairing unplanned issues

39. Ongoing and planned actions include rewriting and implementing the depot maintenance plan to military standards

40. Improve time aircraft spends in depot, the contractor adopted a gated process to track the stages of repair and ensure issues are identified as early as possible

41. No established supply chain for the part, so lack of availability is extending the maintenance time.

42. Diminishing manufacturing sources and vanishing vendors are an issue for other parts, such as those affecting the aircraft’s secure data capabilities

43. Ongoing and planned actions include creating a pylon mid-spar fitting facility with dedicated space and personnel, developing a process to swap pylons between aircraft, and changing the parts-ordering methodology

44. Maintains a diminishing manufacturing source plan with options to mitigate, upgrade, or obtain waivers for parts

45. Identifying all parts that need to be replaced during the inspection phase of maintenance, and identifying alternate vendors for parts

46. Aircraft are maintained organically and through contract maintenance at the designated air logistics complex and field locations

47. Depot-level repair upgrades are performed organically, while contractors are used to conduct some maintenance, such as field maintenance repair

48. Service Life Extension Program identified life-limiting structural components through durability testing

49. Developing modifications and repair designs, validating modification and a repair kit

50. Requiring additional maintenance for repairs that were not originally planned, such as replacing the bulkhead, longerons, and skins i.e., repair of major structural elements that may exhibit areas of cracking related to stress

51. Mitigation efforts include to counter corrosion by identifying all parts and components that need to be repaired and replaced during the phase inspection

52. Experiencing shortages of parts because of diminishing manufacturing sources and increasing need for low-demand items

53. Ongoing and planned actions include identifying alternate vendors, reverse-engineering parts, and cannibalizing parts from other aircraft.

54. Strategy ensuring that short-term initiatives support long-term objectives, while lowering costs, improving quality, and reducing process and lead time

55. Initiatives to support sustainment, such as maintaining a comprehensive diminishing manufacturing sources program

56. Proactively supporting the continued sustainment of component parts of the aircraft through various replacement programs to drive continuous improvement in availability

57. Issues with its low observable coating and supply funding

58. Contracting a repair facility to conduct coating reversion repair and securing additional spares funding

59. Requires extra repairs for corrosion and aging of low-observable coating

60. Shortage of maintenance personnel due to attrition, inability to find skilled workers, and a hiring freeze

61. Ongoing and planned actions to counter corrosion, by identifying all parts that need to be repaired and replaced during the inspection phase

62. Mitigates low observable issue, by depot reversion repair and an Inlet Coating Repair Speedline

63. Counters skilled worker shortage, by piloting a robotic solution to apply the low-observable coating.

64. Experiencing shortages of parts because vendors are not producing some items and were not positioned to support the increase in flying hours

65. Ongoing actions include maintaining a comprehensive Diminishing Manufacturing Sources program to minimize material shortages

66. Investing in improvements to improve durability and maintainability, to include the low-observable coating

67. Actions to mitigate challenges include moving aircraft to deploying squadrons, upgrading aircraft components, and locating other vendor sources for parts

68. Strategies focusing on the engine to make sure the aircraft can continue meeting missions

69. Moving aircraft between squadrons to meet the requirements of deploying missions

70. Requiring additional maintenance for repairs that were not originally planned due to the aging airframe

71. Identifying all parts and components that need to be repaired and replaced during the inspection phase, keeping up with maintenance schedules

72. Conducting analyses on major components and upgrading as needed

73. Increasing awareness of maintainers and other personnel to mitigate foreign-object damage

74. Not enough contracts in place to increase demand for manufacturers to keep production lines open

75. Sustainment planning focused on major components, such as the engine, landing gear, and avionics system, among others.

76. Actions to mitigate challenges include moving aircraft to deploying squadrons, training maintainers to transition to vacated positions, and locating other vendor sources for parts

77. Increased demand for outer wing panels because these parts are reaching their life limit

78. Ongoing and planned actions include moving aircraft between squadrons to meet the requirements of deploying missions

79. Requiring additional maintenance for repairs that were not originally planned, such as repairs for the propeller system and outer wing panels, which are nearing flight hour limit

80. Maintenance is taking longer because more parts need to be repaired and replaced.

81. Conducting system performance studies to identify maintenance tasks to mitigate potential failures

82. Identifying all parts and components that need to be repaired and replaced during the inspection phases

88. Maintenance is taking longer because more parts need to be repaired and replaced

89. Conducting system performance studies to identify maintenance tasks to mitigate potential failures

90. Identifying all parts and components that need to be repaired and replaced during the inspection phase,

91. Training depot and field maintainers and other personnel to transition to vacated positions and to be proficient in repairing all parts of the aircraft

92. Troubleshooting component failures, and cannibalizing parts— moving parts from one aircraft to another

93. Some components experiencing faster failure rates than originally planned, resulting in increased maintenance requirements of the aircraft

94. Avionics system much heavier than the airframe can support, resulting in additional weight and balance checks as well as airframe maintenance issues

95. Inspections of critical structure and systems, with repair conducted as needed along with known incoming defects requiring repair or replacement

96. Experiencing stress and fatigue in its airframe and components include increase in landing gear structure cracks

97. Finding cracks in the lower segment, a beam providing airframe structural support

98. Repairing for corrosion while the aircraft is undergoing other heavy maintenance or repairs at a designated base helps to minimize aircraft down time.

99. Working to directly hire skilled workers to allow managers to quickly install qualified candidates for critical positions.

100. Ongoing and planned actions include upgrading aircraft systems before they become obsolete, locating another vendor source, redesigning parts, purchasing additional parts to maintain a supply source, and accessing the virtual fleet program to acquire parts from around the world.

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Top 50 System Design for Reliable Available Maintained [RAM] Operation Status Update Criteria

10/10/2018

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Readiness is the state of preparedness of forces or weapon system or systems to meet a mission, based on adequate and trained personnel, materiel condition, supplies/reserves of support system and ammunition, numbers of units available, etc. Deficits in RAM will cause readiness to fall below needed levels or increase the cost of achieving them. Effective diagnostics helps assure both system/mission readiness and efficient repair/return to ready status.

This guide addresses RAM as essential elements of mission capability. It focuses on what can be done to achieve satisfactory levels of RAM and how to assess RAM. This Background Brief introduced RAM, what it is, why it is important, current RAM problems in the DoD, and activities appropriate to achieving satisfactory levels.

RAM refers to three related characteristics of a system and its operational support: reliability, availability, and maintainability.

Reliability is the probability of an item to perform a required function under stated conditions for a specified period of time. Reliability is further divided into mission reliability and logistics reliability.

Availability is a measure of the degree to which an item is in an operable state and can be committed at the start of a mission when the mission is called for at an unknown/random point in time. Availability as measured by the user is a function of how often failures occur and corrective maintenance is required, how often preventative maintenance is performed, how quickly indicated failures can be isolated and repaired, how quickly preventive maintenance tasks can be performed, and how long logistics support delays contribute to down time.

Maintainability is the ability of an item to be retained in, or restored to, a specified condition when maintenance is performed by troops having specified skill levels, using prescribed procedures and resources, at each prescribed level of maintenance and repair.

Many factors are important to RAM: system design; manufacturing quality; the mission space which the system is transported, handled, stored, and operated; the design and development of the support system; the level of training and skills of troops operating and maintaining the system; the availability of materiel required to repair the system; and diagnosis tools. available.

All these factors must be understood to achieve a system with a desired level of RAM. During pre-systems acquisition, the most important activity is to understand the users’ needs and constraints.

During system development, the most important RAM activity is to identify potential failure mechanisms and to make design changes to remove them. During production, the most important RAM activity is to ensure quality in manufacturing so that the inherent RAM qualities of the design are not degraded.

In operations/support phase, the most important RAM activity is to monitor performance in order to facilitate retention of RAM capability, to enable improvements in design if there is to be a new design increment, or of the support system to included support concept, spare parts storage, etc.

Although significant improvements have been made in increasing the reliability of basic components, these have not always been accompanied by corresponding gains in the reliability of equipment or systems. In some cases, equipment and system complexity and functionality have progressed so rapidly that they negate, in part, the increased reliability expected from use of the higher reliability basic component.

In other cases, the basic components have been misapplied or overstressed so that their potentially high reliability is not realised. In still other cases, past Site Visit Executives have been reluctant or unable, due to program budget shortfalls or highly aggressive schedules, to devote the time and attention necessary to ensure that the potentially high reliability is achieved.

However, in many areas of the commercial sector, increased system complexity has not negated system reliability. In fact, often products with increased system complexity are provided with increased system reliability. This is an area the defense sector must also strive to improve.

Achieving specified levels of RAM for a system is important for many reasons, specifically the affect RAM has on readiness, mission success, and logistics footprint.

“Why does System RAM disappear over time?”

1. Change in operating concept

If system is used in a manner different from that originally allowed for in the design, new failure modes can occur, and the overall frequency of failures can increase.

2. What effect does Change in Scenario Have on Mission?

In such cases, corrective actions can be expensive or impractical. If the system must operate in the new scenario, decreased RAM levels may have to be accepted.

3. What are the consequences of Inadequate training?

Inadequate operating or maintenance training usually increases the number of failures induced by improper operation or maintenance. The corrective action is to improve the training.

4. Why do systems fall apart later in Service Life

Reliability Centered Maintenance Program overhaul such parts will prevent wearout from becoming a problem. Ideally the preventive maintenance program is based on the reliability characteristics of the parts i.e., a reliability-centered maintenance program based on the field info

5. Why do design/test assessments fall short?

All engineering models, assessment tools, and test methods are imperfect. It is also impossible to perfectly model or simulate the actual operational environment during design and test. The time and funds available for testing are limited. For all of these reasons, failure mechanisms may go undetected until after the system is fielded.

6. Why do teams exhibit Lack of understanding?

Most modern weapons systems are digital in design. The mission success, available adequate he number of failures per unit time for parts having wearout characteristics will increase. A preventive maintenance program to replace or ability, and supportability. Previously, classical RAM levels were component failure intensive. Currently, software plays a more important role. Personnel labour developing, and producing these new systems need to understand some systems require a different approach to failure detection, isolation and ultimate repair or corrective action.

7. What are the effects of Change in supplier?

If a supplier chooses to stop manufacturing a part or material, goes out of business, or no longer maintains the necessary levels of quality, an alternate source of supply is needed. If RAM is not a major consideration in selecting the new supplier, system reliability may degrade. If there are a limited number of new suppliers to select from, lower RAM levels may have to be accepted.

8. Why are there deficits in configuration control?

Over a system’s life, there is the temptation to reduce costs by substituting lower-priced parts and materials for those originally specified by the designer. Although the purchase price may be lower, service lifecosts will increase, and the mission will suffer if the “suitable subs” do not have the necessary RAM characteristics. Strong configuration management and a change control process that addresses all factors, including RAM performance, are essential throughout the life of the system.

9. What are Prevalent Manufacturing problems?

Although the manufacturing processes may have been qualified and statistical processes implemented at the start of production, changes can occur during the production line that degrade RAM. This possibility increases as the length of the production run increases; therefore, constant quality control is essential.

10.What are the consequences of Inadequate funding?

“Create Assess Record Define What System Supports RAM Requirements”

Provides progressive assurance that RAM requirements are being developed, implemented, verified, enforced and that the requirements can be achieved. The case evolves between the customer and supplier as the project evolves. Initially the customer is acquisition organisation; eventually, it is subsequently the user. Reliability analyses are not an after-the-fact documentation of what resulted during the design process, but an active integral part of the design process. Immediate action should be taken if unacceptable analysis results are found.

1. Document the user needs and inform the subsequent activities. Documentation of the model provides the baseline for subsequent assessments.

2. Initial RAM projections provide the basis for technology development, fault mitigation, and risk reduction activities in pre-systems acquisition.

3. The RAM Rationale describes the level of reliability user needs in order to achieve system readiness, and mission performance goals. In DoD acquisition framework, the RAM Rationale is summarised and later updated in the Capability Development Document and the Capability Production Document .

4. The RAM Program Plan describes the structured series of RAM related activities that will achieve the needed RAM levels. accumulated evidence, at any point in the program, of demonstrated progress toward achieving the users’ RAM needs. Examine the design and its detail.

5. Examine subsystems, assemblies, subassemblies, and components: identify “knowns” and “unknowns” about each indenture level within the system to mitigate risk to success. Find, assess, and mitigate failure modes and failure mechanisms.

6. Avoid delaying corrective action in development.. Account for manufacturing. The design can contribute to minimising quality control problems that will cause mission failures in the field.

7. Evaluate the maintainability and supportability of the system such as the accessibility of components that might need to be replaced, the completeness of the built-in test equipment, the presence of on-board instrumentation, or consider issues of sparing and support

8. Develop ground maintenance support system to support maintenance decisions in the User's environment using recorders to support tasks such as maintenance planning, scheduling, configuration control, operator debrief, and usage processcollection such as operating hours or cycles. Some modern designs must be supported in the Automated Maintenance Scenario and must be designed for this support concept.

9. Develop a representative prototype of the system, and, where possible, identify composition of subsystems, assemblies, subassemblies, and components.

10. Verify that RAM is achieved in representative conditions, using developmental testing or similar activities.

“Design/Production Phase Shift to Process Control, Quality & Stress Screen”

1. Stress Screening: Defined as the removal of latent part and manufacturing process defects through application of scenario stimuli prior to fielding the equipment. Stress screen will be used to ensure that reliable, available, and maintainable systems are produced and deployed that will be devoid of latent part and manufacturing process defects.

2. Production Reliability Assurance Testing : Performed to ensure that the reliability of the components is not degraded as the result of changes in tooling, processes, workflow, design, parts quality, or any other variables affecting production.

3. Continuation of Growth/Test, assess & Fix-Test: The process of growing reliability & tech performance, and testing the system to ensure that corrective actions are effective was started-- focus becomes ensuring that the corrective actions are producible and equate to improved RAM in the produced system.

4. Reliability Growth Testing Methodology monitors improvements in reliability while deficiencies are being identified and fixed. This methodology also can assess the impact of design changes and corrective actions on the reliability growth rate of the system, specifically during O&S production design or that the system has not been degraded by component updates. Overall system maturation is important to achieve OT&E goals.

5. Continued Reliability Quality Testing and Acceptance Testing: The RAM activities shift from qualifying the proposed design to ensuring that the manufacturing process


6. The biggest change in the process where process status is captured. Instead of developmental testing being the primary source of data, information can be captured from OT&E, other field sources.

7. System Verification Review: The purpose of Functional Configuration Assessment is to evaluate the system under review to determine if it can proceed into Low-Rate Initial Production and Full-Rate Production requirements, including RAM, documented in the Functional, Allocated, and Product Baselines.

8. Production Readiness Review planning to ensure designed-in RAM levels are not degraded. At this review, the Integrated Product Team should review the readiness of the manufacturing processes, the Quality Management System, and the production planning i.e., facilities, tooling and test equipment capacity, personnel development and certification, process documentation, inventory management, supplier track

9. Operational Test Readiness Review conduct another review prior to Initial Operational Test and Evaluation focuses on ensuring that the “production configuration” system can proceed into IOT&E with a high Production Decision may hinge on this successful determination. assesses the ability of operational tests to confirm RAM requirements.

10. Physical Configuration Audit: Rate Production Decision examines the actual configuration of an item being produced to verify that the related design documentation matches the item as specified in the contract. also confirms that the manufacturing processes, quality control system, measurement and test equipment, and training are adequately planned, tracked, and controlled in order to ensure that RAM is not degraded in the production process. Additional assessments should be performed throughout the system life cycle as necessitated by changes in item design, manufacturing process and source of supply dictate.

“Monitor Field Performance in Service Review Assure RAM During Operations & Sustainment Phase?

1. Backbone of assurance technologies reliability, availability, maintainability as it provides info needed to monitor system performance and identify corrective actions to ensure RAM is not degraded after system is deployed

2. Reliability growth testing monitors improvements in reliability while deficiencies are being identified and fixed. This methodology also can assess the impact of design changes and corrective actions on the reliability growth rate of the system, specifically during O&S design changes to the deployed system.

3. Service Life factor Review: Supports overhaul decisions, changes to the maintenance concept, and risk mitigation activities through stats of component, assembly, or system info

4. Repair Strategy: Continually reviews maintenance and support concepts to ensure that repair strategy is not introducing defects into the deployed system that degrade its inherent RAM. This includes refinement of the on and off equipment maintenance processes including the automated maintenance environment support strategy.

5. Maturation: Defines the continuous process of eliminating false alarms and improving fault detection and isolation as the system matures.

6. Reliability centered maintenance logically determines if preventive maintenance makes sense for a given item and, if so, determining the appropriate time and manner in which to conduct the preventive maintenance. As field performance is monitored during O&S

7. Condition-Based Maintenance: Defines optimal maintenance point that maximises the expected results in terms of increased product output, decreased maintenance costs, etc. with the short-term and long-term of implementing the maintenance

8. It is important during O&S to verify that condition-based maintenance program is acceptable based on the monitored field performance

9. Discontinued Parts Sources Attempts to avoid potentially expensive and time-consuming problem of searching for suitable replacement parts

10. Parts that are no longer manufactured or are no longer viable to produce according to the current specification

“Translate RAM into Budget/Readiness Goals for Specs Ensure System Perform”

1. Allocate the system-level requirements down to a level i.e., subsystem, component, or assembly level meaningful to the design and manufacturing engineers.

2. Inherent factors are a function of the time and money available for design and test, the robustness of design analyses, the available technology, and other competing requirements

3. Other Performance Factors: Trade-offs between competing requirements are made to reach “optimal compromises.” For example, it is extremely difficult to optimise both of two inversely related engine requirements for an aircraft, such as high reliability and high thrust-to-weight ratio

4. Trade-off is made that produces an engine design that is reliable enough to ensure safety and an acceptable aircraft availability, but which still has an adequate thrust-to-weight ratio.

5. Support Infrastructure Factors: The operating and support concepts will affect RAM performance. Specialisation of skills and other personnel policies will affect the operating and support concepts

6. The number of required spares as well as pipeline times within the support concept can be directly affected by the maintenance concept i.e., levels of repair, a single location/base performing maintenance for several locations, etc. and inspection

7. Spares buys are determined not only on the basis of the maintenance concept and available funding, economic order quantities, and other factors.

8. Operating Concept Factors: The RAM performance of any system can and will be affected by the operations concept that will govern the system when it is deployed.

9. Must accurately account for the types of mission that the system will be subjected to, deployment requirements, the need for operations at austere bases, etc.

10. Operating Scenario Factors: RAM performance is obviously a function of the type and scenario operated in. Different Operations Locations will impose different stresses on a system than others
　

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Top 50 Keys to Fielding System with Strong RAM Levels Integral Component of Engineering Process

10/10/2018

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RAM design activities start in pre-systems acquisition and continue through development, production, and beyond into operations and support.

Systems engineering is a logically sequenced, consistent set of technical activities often do not provide the balanced solution systems engineering design assessments strive to obtain. RAM prediction is any method used to assess the level of RAM that is potentially achievable, or being achieved, at any point. Achieving metrics via a RAM prediction will not ensure that the best system design is developed.

As important as it is to select the right activities, it is equally important to conduct the activities at the right time. An assessment intended to support design improvement, for example, is of little value if it is begun near or after the critical design review. For maintainability, it is of little value to require explicit levels of system testability for accurate and dependable fault detection and isolation during the design phase.

If the system does not achieve good RAM, mission performance and life cycle cost are at risk. The pressures of budget or schedule can cause Program Managers and contractors to consider reducing or eliminating RAM activities, in particular the task of ID maturation since it occurs near the end of system development just prior to technical or operational evaluation .

An objective assessment of risk and impact should be made. Specifically, any potential negative impact on the system’s ability to provide measurable increases to mission capability or operational support should be weighed against any potential short-term savings. Unless a programmatic, systems engineering and total life-cycle perspective is taken in making such decisions, the net result can be decreased mission performance and increased costs over the long term.
　
The RAM Case is a reasoned, auditable record to document how well a defined system supports the RAM requirements. It provides progressive assurance that RAM requirements are being developed, implemented, verified, enforced and that the requirements can be achieved.

The case evolves between the customer and supplier as the project evolves. Initially the customer is the acquisition organisation; eventually, it is subsequently the user. Reliability analyses are not an after-the-fact documentation of what resulted during the design process, but an active integral part of the design process.
　
The review process uses a closed-loop system that identifies each design defect, enters it into a deficiencies and serve as an accurate historical record of the design activity be of little use in achieving the requisite level of RAM if it is not conducted properly. Standards, guides, and textbooks are available that provide the correct procedure for conducting nearly every type of analysis or test related to designing for RAM.

System engineering ensures that the solution that satisfies the requirements of RAM technical considerations. Systems engineering expands the evaluation criteria to select criteria that best balance program requirements, such as system performance, total ownership cost, schedule, supportability, risk, etc. The criteria are selected based on the stated problem as well as the level and complexity of required assessments.
　
　
“What Tools are Required to Construct Complete Case Model Concept?”

1. Understand and Document User Needs and Constraints, their utilization may vary from acquisition to acquisition. Almost always there will be a need for a RAM Program Plan and often there is a strong desire to develop the RAM Rationale, but the benefit of the RAM Case may often be overlooked

2. The RAM Rationale defines the needed RAM characteristics, mission profile and use environment. The RAM Rationale identifies the RAM requirements, and their assess basis, to be documented in the request for proposal

3. The RAM Program Plan lays out the strategies, processes, resources, and organization to achieve the RAM requirements.

4. The RAM Case provides the record of how well requirements have been demonstrated at each stage of the program. The RAM Case provides the evidence that the contractor
the contractor’s evidence within request for proposal contractual documents, etc.

5. The systems engineering app roach to the acquisition process recommends technical reviews to confirm outputs of the acquisition phases and major technical efforts within the technical phases. Must Understand and Document User Needs and Constraints the following technical reviews should be conducted.

6. Initial Technical Review : Multi-disciplined technical review to support a program’s initial Program Objective Memorandum submission. This review ensures that a program’s technical baseline is sufficiently rigorous to support a valid cost estimate with acceptable cost risk, and enable an independent assessment

7. Alternative System Review: Model and expert judgment to make p reliminary RAM estimates, develop RAM Rationale, planning the RAM program. Although the RAM the activities required to achieve a reliable, available, and maintainable system. achieved RAM requirements. So without the RAM Case and the presentation of uncertainty levels is possible in terms of the contractor’s ability to satisfy the RAM requirements as defined by estimates of cost, technical, and program management subject matter experts

8. System Review: Multi-disciplined technical review that ensures that requirements agree with the customers’ needs and expectations and proceed into the Technology Development phase of the acquisition process.

9. System Requirements Review Multi-functional technical review that ensures all system and performance requirements derived from the Capability Development Document are defined and consistent with cost, schedule, risk, and other system constraints. The review determines the direction and progress of the systems engineering effort and the degree of convergence upon a balanced and complete configuration review provides the preliminary allocation of system requirements to verify that test methods and acceptance criteria, based on use of agreed-to verification methods, are incorporated into schedules, facilities requirements, manpower needs, and other programmatic imperatives.

10. Integrated Baseline Review should be conducted throughout the acquisition process identifies project milestones and resources as well as ensuring objective and rationale system measurements RAM are identified.


“Systems Engineering Work Reach System Capable User Requirements”

1. Must account for the entire service life of the system/capability acquisition.

2. Functions that systems engineering accounts for are development, manufacturing/production/construction, deployment/fielding, operation, support, training, and verification.

3. Systems engineering ensures that the correct technical tasks are accomplished during the acquisition process through planning, tracking, and coordinating.

4. Development of a total system design solution that balances cost, schedule, performance, and risk

5. Development and tracking of technical information required for decision making

6. Verification that technical solutions satisfy customer requirements

7. Development of a system that is cost-effective and supportable throughout service life

8. Adoption of the open systems approach to monitor internal and external interface compatibility for the systems and subsystems,

9. Establishment of baselines and configuration control

10. Proper focus and structure of interdisciplinary teams for system and major subsystem level design.
“Evaluate Effect of RAM Changes to System Design”

.
1. Determines rank ID the effects of each failure mode on system performance

2. Emphasises identification of single-point failures developing corrective actions.

3. Facilitates investigation of design alternatives

4. Consider high reliability at the conceptual stages of the design.

5. Provides a foundation for qualitative reliability, maintainability, logistics assessments

6. Provides the criteria for early planning of tests to characterize the weaknesses of the design

7. Determine basis for operational troubleshooting

8. Locating performance monitoring devices within the system.

9. Visibility of system interface features and problems

10. fault sensing test equipment or test points.
“Questions to Address Before Full Rate Production Proceeds”

1. Satisfy RAM and quality inspection and test requirements?

2. What full-rate production RAM problems are revealed during model fabrication, testing, and manufacture?

3. What specialized “burn-in,” parts screening, or other special manufacturing process required

4. Meet production reliability/quality inspection and test criteria?

5. How does the production rework and shrinkage rate for individual co-assemblies, units, etc., correlate with RAM of the production item as measured in factory acceptance tests?

6. What impact do proposed engineering changes, manufacturing changes, have on RAM?

7. Does production model conform to specified reliability demo requirements?

8. Are procedures and processes in place for anticipating diminishing manufacturing sources and finding alternative ways of supplying the affected items?

9. Are off equipment maintenance facilities, processes, tools in development?

10. System refined sufficiently to support the system in multiple operational scenarios?

“Service Life Cost Structure Components not Considered”

Inadequate support funding can affect many factors, including availability of repair parts, support equipment, and maintainer training with big mpact on RAM

1. System Operation Cost: Base cost to operate the system including paying the users, fuel for the system, and so on.

2. Distribution Cost: Cost to ship the product to its destination.

3. Information Technology Resource Cost: Often when deploying a new system, personnel will be deployed with the system and the personnel will need new computers. New complex systems will require extensive computing capability to accommodate on-board recorded data for various disciplines. Therefore no matter how simple, there will be some computing time added to the O&S costs.

4. Maintenance Cost: Costs to conduct routine maintenance, at whatever level, including compatibility using Automated Maintenance scenario tools and resources.

5. Test and Support Equipment Cost: Costs associated with developing and acquiring diagnostic equipment and tools required for the new system how to use and maintain the new system.

6. Training Cost: All systems require some level of costs to train users and maintainers on hand how to use system

7. Supply Support Cost: Costs associated with shipping spare parts, returning faulty parts to the depot for repair, etc.

8. Retirement and Disposal/Recycling Cost: Eventually the new system will reach the end of its useful life and must be appropriately discarded

9. Technical Data Cost: Developing a library of technical data is vital for any complex system and there will be costs associate with collecting, maintaining, and assessing this tech info

10. In-Service Engineering and Logistics Cost: The cost associated with the management and execution of the service life requirements.
　

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Top 10 Team Training Strategies Define Agent Interaction Models Focus Simulation Programme Goals

10/1/2018

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Site Visit Executive must continually assess Marine Corps approaches to systems training/engineering, including use of agent models, simulation results, artificial intelligence techniques, and tools that support training process so it is possible to stay ahead of demands for new and upgraded weapons systems.

Using agent models is not a new concept; however, digital engineering will address long-standing challenges associated with complexity, uncertainty, and rapid change in deploying defense systems. By providing for more agile and responsive development, digital training/engineering supports engineering excellence and provides a foundation for mission success in the future.

Realising end-to-end digital enterprises, automating tasks and processes, and making smarter, faster decisions all require next frontier of technologies to transform the way agents and machines interact. Advances in artificial intelligence have given rise to behavioural technologies capable of performing tasks that traditionally required intelligence of commanders in the field.

While live training will always remain the standard against which Marine unit readiness is measured, even live training has its limits. It costs a lot of money to ship Marines out to Twentynine Palms or other areas. It costs money to fire munitions. Some of those munitions can’t be fired in most areas.

The Marines want simulators in which commanders can lead virtual troops.

Some of the advanced weapons can’t be demonstrated where just anyone can see them in action, thus revealing our tech to adversaries.

And that is where simulations can help bridge the gap.

But first, there’s a list of things that must come to fruition.

Machines are now able to build knowledge, continuously learn, understand language and interact with agents better than traditional systems. Site Visit Executive vision expects agents to interact with machines to make faster information-driven decisions and help exploit information more effectively than commanders could on their own and develop awareness of these technologies, evaluating opportunities to pilot test, and demonstrating options for creating operational value.

Readiness block tasks show real-time agent behaviour for distributed sequence cues formation of interactions in mission/function constraint space.

We present the following framework for the representational system of a distributed artificial intelligence task for solving constraint problems by individual agents. This framework serves as a guide for our product demonstration report. In the process of addressing its requirements, project developed some new concepts that hold promise for broader application to distributed constraint optimisation.

Agents sponsor product support activities case study to delineate any limitations, constraints or boundary conditions so obstacles to executing coordinated field-level operations are reflected.

Much of what needs to happen is in areas of applications and bandwidth, basically getting better versions of terrains and simulations that are more realistic and can accommodate as much as a division’s worth of players and an equally complex, simulated adversary.

But some items are smaller and more hands-on, like better virtual reality and augmented reality headsets.

Those headsets are key since the Marines want them to work not as they do now, with pounds of cabling in bulky indoor shooting simulators but light with long-lasting batteries that can be taken in the field and on deployment.

Application problems in distributed artificial intelligence are concerned with finding a consistent combination of agent actions to be formalised as distributed constraint satisfaction problems involved in effort to find consistent assignment of values to variables distributed among multiple automated agents.

Motivated by the fact that components with different costs and failure time distributions from different agents can be available for the design of the same subsystem in practice, state-of-the-art is advanced by presenting a solution sequence to determine combined optimal design configuration and optimal operation of different standby series/parallel systems.

High-level programming techniques have been created for next generation sequence alignment tools for both productivity and well-defined performance. Sequences are lists of tasks that changes according to some pattern. Pattern-based programming framework provides agents with high-level parallel patterns.

There is the problem of parallel alignment so you must review how popular alignment tools function in single high-level parallel strategy. By using a high-level approach, you don't need to be concerned with complex aspects of parallel programming, such as linking task scheduling, so you can achieve seamless performance tuning.

You'll need to differentiate between sequence numbers and unique sortable identifiers by a specific criteria typically generation time. True sequence numbers imply knowledge of what all other agents have done, so a shared state is required. It is virtually impossible to do this in a distributed, high-scale manner.

There is an increasingly pressing need, by several applications in multiple distinct domains, for creating techniques able to index and mine very large collections of sequences summed into series.

We present our goals for the future in big sequence administration and mining. More efforts should concentrate on parallel/distributed solutions, which have received little attention.

Many Commanders confuse the distinct concepts of parallelism and distribution. Parallel Search refers to the distribution of the search space and Distributed Unlinked Search to the distribution of mission/function constraint problems solved by agents.

A certain amount of parallelism exists in any Distributed Unlinked Search and it increases with stronger association. However, in comparison to Parallel Search, the parallel effort in Distributed Unlinked Search can be characterised by redundant mission performance tasks.

Moreover, agents in Unlinked Search can have periods of inactivity which are less frequent in Parallel Search. Since Distributed Search is the only solution for certain classes of classic mission-oriented distributed problems, we show here how one can integrate the idea of Parallel Search in Distributed Unlinked Search.

Distributed artificial intelligence is concerned with interaction, especially coordination between agents exhibiting auto behaviour. Since distributed network solution strategies are spreading very rapidly due to tech advances, commanders have pressing needs for distributed techniques in mission readiness determination.

Agents are grouped to form clusters of similar agents and these clusters are considered as new agents in the process, establishing groups of optimal similar product configurations which to enable parts of the product configuration to be identified and create a range of products or just chosen among several proposals.

When a commander finishes the fight, they should be able to query the virtual enemy and figure out why it did what it did, how it gained a certain advantage.

And it shouldn’t take a programmer to “talk” with the simulation. Units communicate via voice and chat. That’s how simulations users must be able to talk with their simulated allies and enemies, in plain language.

These pursuits are not happening in a vacuum. They were done at a battalion level with a short prep time, far different than the large-scale Marine Expeditionary Unit or Marine Expeditionary Brigade-sized training that is typical.

That is part of a larger effort to create a “plug-and-play” type of training module that any battalion, and later smaller units, can use at home station or on deployment to conduct complex, coordinated training.

What made that work new was pairing legacy systems with a variety of operating systems between them.

That’s another example of what needs to be fixed.

Solution agents must be evaluated. A rating is assigned to each of them depending on their consistency with the requirements imposed by the customer, the constraints determined by the experts and the functions the product must perform.

Each solution agent determines the optimal configuration for the product concerned based on its local point of view. Then the configurations are evaluated considering elements of agent-based systems.

Both agents and mission space can be either simulated or real-world entities. The distinction is important since an agent-based system can be purely a simulation, a collection of realistic agents living in the mission space, or a hybrid e.g., real-world agents living in simulated mission space.

Any comprehensive proposed architecture not only must accommodate the possible types of agent-based systems but also transition from one to another.

We have proposed some fundamental requirements for modeling and simulation of agent-based system and provide categories based on support for 1) architectural integrity, 2) modeling agents and their mission space and 3) computational foundation.

Several important issues must be dealt with in order to build agents capable of footprint in their intended scenarios. Of particular importance here are the following issues: accounting for agent and mission space complexities e.g., assumptions such as complete and error-free information about the mission space an agent's complete knowledge about its mission space, an agent's capability to fully achieve its goals, providing a well-defined model of time, supporting multiple agents, well-defined interfaces between the agents and mission space, and exogenous events.

Marines and other services are, in many cases, using systems that were designed decades apart and creating a patchwork methods to get the hardware to work together when it wasn’t built for that type of operation.

The new systems must be open architecture so that new tech, new weapons and new terrain can be added on the fly. But also secure enough to operate across networks and not be spied upon by those who would want a peek at our tactics.

We have included these issues within the set of requirements for architectural support of agent-based system development:

Architecture should encourage reuse, allow a layer to be exchanged with another using well-defined interfaces, and if necessary only loosely implementation dependent, supporting procedural, and declarative knowledge representation.

Support for reuse can range from component level to layers of the proposed architectures. At the component level, a sensor or its model may be made reusable. More challenging is the ability to reuse a layer or a combination of layers. To achieve reuse for layers, as it is required at the component level, well-defined interfaces are needed. Realisation of interfaces, however, is considerably more difficult.

Architecture should treat modeling and simulation/execution as distinct layers. The separation of modeling and simulation activities has big impact on reusability and portability in integrated concurrent engineering. Existing commercial/research tools tend to support either depth in modeling of decision behaviors or depth in traditional simulation concerns such as production facilities, output assessments, etc.

However, few tools attempt to support constructing models with decision agent behaviour that can be simulated in realistic mission space and with the full power of traditional simulation systems. Such tools tend to tightly bind their modeling and simulation facilities so that models developed can only be executed by the simulation engine provided by the tool. So despite being capable of modeling agent behaviours, the models so developed cannot be tested in realistic simulation mission space.

The Marine Corps Warfighting Lab just finished a rapid capability assessment of a pair of goggles equipped with augmented reality that allow artillery maintainers to work on three-dimensional digital models of M777 155mm howitzers.

Marines like it ... you can tell what's missing, what's broken, what's cracked. "It can't do much for us right now, but when Marines were back at the schoolhouse, this would have helped out a lot to actually see parts in the howitzer. Some Marines are very visual learners; looking at a schematic doesn't help us much."

"Within training, it runs the spectrum. It can be maintainer training, it can be infantry training, it can be gun-drill training. We were talking to some snipers earlier. This could be used on a sniper training range, where you have the snipers crawling through the grass trying to get within shot range and not be observed while they are doing so.

"Currently, how are they being observed -- through a telescope. You can augment that telescope, which uses the human eyeball, with the laser range finding that the goggles are capable of, to pick up variances in the terrain in order to better detect those snipers, which will make them better snipers because now they've got to beat technology.

The modeling and simulation subsets should be fully integrated, i.e., based on the same structural context for their modeling constructs. Separation of models from simulators also has an important secondary benefit. This is the possibility it opens up to replace the simulation engine with an execution mission space so models are executed in real-time as well as logical time.

This would make it easier to migrate agent models from simulation to actual operation after fully testing their logistics capacity. Transition of models from the design phase to the implementation phase is a key feature of Simulation-based acquisition efforts.

Modular model structure supports development and testing of complex agent architectures. To avoid the pitfalls of huge models, it is necessary to adopt a modular model representation scheme. Modular construction enables verification and validation at every stage of a decomposition ordered by multiple levels.

Systematic model selection and composition based on generalisation and granularity Constraints ie, multi-resolution should be supported. Since model designers are generally faced with alternative choices -- specialisation and multiple-level decomposition for a given model, it is important to be able to represent a family of models in an exact structure.

Such model representation schemes allow model designers to compose many variations of models using a set of well-defined operations choosing one model variation vs. another, putting together a large model using alternative sets of model components.

It is key to specify early attempts at modeling constructs and model components. To support the flexibility demanded by any agent-architecture, its modeling environment should provide basic modeling constructs as well as modeling components.

Generic modeling constructs are early types which can be employed to represent varying levels of model components. Such components can range from generic to highly domain specific. For example, lower-level model components might be different kinds of generic queues, and higher-level domain-specific model components might be processors servicing time-critical commands of a robot. The model components ie, agents are "canned" components with well-defined input/output interfaces and behaviour.

Must support realistic virtual environments in which agent behaviours can be tested. The architecture should support construction of very responsive physical and behavioural mission space and stand in for the challenging real world counterparts in which agents are designed to function. This is a particular strength of an architecture that incorporates state-of-the-art simulation capabilities.

Accounting for executing the modeled behavior of agents and mission space is dependent on the classification of the agent-based system and support for collaborative model development and model repositories. Collaborative modeling enables dispersed modelers to develop modular model levels both coupled and uncoupled.

In such application based cooperative working scene, model repositories are essential to support efficient and systematic model reuse and integration. Such repositories offer many benefits for maintaining and using models. Repositories can be built from widely employed relational systems to be scaleable and provide standard queries for access to and from model content.

But many challenges remain to support collaborative development of levels based modular models and components within distributed and networked mission space. For example, a lot of work is required to develop workable schemes to assign ownership rights of enterprises and within enterprises and functional teams. participating in a model development effort.

On deployment, Marines can’t rely on a cadre of contractors back home to run their hardware. To that end, the Corps has stood up Simulation Professional Course and the Simulations Specialist Course.

Both give Marines in infantry units experience setting up simulations and running the games for their units. They input training objectives and can understand and put together training for the unit staff or just for their fire team back in the barracks.

Real-time distributed and parallel execution should be supported to enable execution of simulated agents and deal with model complexity, effective use of distributed, heterogeneous computing platforms, and to facilitate assessments of large systems. The simulation architecture should enable distribution of the model composed of several modules on nodes within network.

Distribution should be automated and distribution policies could take into account load balancing requirements, mobility of agents, and other state-dependent factors. Moreover, the architecture should provide for both logical-time and real-time execution of models to accommodate the types of simulated and real agent-based systems and their interoperation.

Support for information distribution comprises the set of services that attempt to reduce the message interchange traffic without impacting the accuracy of the simulation. Service sets include message filtering and when subscribers declare their interest in receiving from a subset of status posters. To the extent information mitigates growth in capacity requirements for large numbers of entities, it is a critical function.

Agent roles/responsible are defined by organisations and expected to translate action into performance for current task demands. Approach introduced into artificial intelligence typically considered distributed systems where each individual in such systems possesses potential for action based on events.

With such capabilities, individual agents in an organisation have capacity to make reasonable local decisions about what they should do given what they know about their tasks and mission space, as well as what they know about what others are likely to be doing.

Marines can create their own terrain maps and fight the simulated fight in the areas they’ll really be operating in.

But one step further is key: The enemy has to talk back.

It is precisely this last bit of knowledge--about what others are likely to be doing--that is available thanks to knowing the organisational structure. That is, if a participant knows the roles and responsibilities of others, it can make more informed decisions about what to do locally and how to interact with them.

And those video feeds that are now on every ISR platform in the real world? Simulations need them too, to be realistic. That means game designers have to have human-like activity going on in areas.

When a commander wants to zoom in on a tactical frame in the game, they’ll be able to do it just like in theater.

Which brings it to one of the more ambitious items beyond terrain and hardware: getting simulations to act more like humans.

As it works now, unit commanders set up their forces, work their mission sets and then the virtual “forces” collide and often a scripted scenario plays out.

Not too realistic.

What’s needed is simulations to act like populations might act in the real world and the same for the enemy, taking advantages, fighting and withdrawing.

So scenario in turn means agents should abide by their designated roles, so each agent must be able to focus its local decisions toward fulfilling its responsibilities.

Computational representations for organisations have been developed in terms of interest areas for agents. Individual agent interest areas would indicate what kinds of info processing tasks it was willing and able to tackle, and to what degree.

Faced with a variety of possible actions to take, agent would be influenced to a degree of possible modification by an experimenter by how well those actions fit within its most preferred areas of interest.

Because each agent knows the interest areas of the others, each could identify processing tasks, or information, that would be potentially of interest to them, focusing communication among them to eventually converge to a state where all the most important tasks were accomplished in a focused distributed manner.

Smart design of agent interest areas is of primary importance to the success of this approach. Interest areas that are too narrow could mean that processing tasks became unevenly distributed among the agents, leading to longer delays until overall task completion.

Moreover, if a subset of the agents failed to participate in the instance a network connecting them crashed, then some tasks would be left unaccomplished and the overall task would fail to be completed.

On the other hand, if interest areas were broadly defined so as to increase reliability and the chances that every agent would have something useful to do, then the situation could quickly deteriorate with agents duplicating effort and working at cross purposes.

In addition, by making every agent more of a “generalist,” communication among agents would explode because everyone would potentially be interested in everything.
Marine Corps and other services are focused on finding ways to use augmented reality in training.

"It seems unlikely that it's going to go away. We have Marine Corps Systems Command, interested in augmented reality ... and we have all been talking about these systems and what they are capable of."

Potential performance measures to be initially considered:

1. Response Time is the total time taken to accomplish a task. It is also called the turnaround time.

2. Throughput is the number of tasks accomplished per unit time. Without a definition of a unit task this measure is not defined well

3. System Utilisation is the fraction of the total system capacity being used at any given time. For a given resource, it is the fraction of time the resource is busy.

4. Communication Cost is the cost of transmitting a number of bits across the channel. If time is used as the cost, it may include the connection time plus the time to transmit a number of messages across the channel.

5. Sometimes number of bits or message packets transmitted across the communication channel may be used as a measure for communication cost.

6. Reliability refers to the probability system or a component under consideration does not experience any failures in a given time interval used to describe systems that cannot be repaired or where the operation of the system is so critical that no downtime for repair can be tolerated.

7. When system is composed of multiple subsystems and/or components, the reliability of each component can be used to evaluate the reliability of the total system. By using redundant components, the system reliability can be improved.

8. Availability refers to the probability that the system is operational according to its specification at a given point in time.

9. Yardsitcks can be used as some measure of systems suitability potential to be repaired and which can be out of service for short periods of time during repair.

10. Solution Quality refers to some objective measure of the quality of task results defined for particular task domains.

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