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Top 10 Multi-Domain Operations Command Building Team of Experts Forecast Trends to Prep for Conflict

7/20/2020

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Multi-Domain Operations Wargaming Exercise Team scans the technological horizon for upcoming advances in electronics, artificial intelligence and more. Its forecasts, informed by data and machine learning, are intended to help the Army arm, organize, and train itself for conflicts around 2040 to 2050.
 
We have industry infused into concept development as we do now and that’s all the Team effort.  “We’re not just writing concepts that say, ‘Hey, we need to do this. Industry go build me this thing’.”
 
Team is surveying the tech landscape, seeing how some breakthroughs will lead to others, and then create scenarios and concepts for how those technologies will shape not just what the Army does but what adversaries might do as well.
 
So we are saying--  if this was possible. Would you change the way you write your Multi-Domain concept?” … That conversation was the purpose or intention of Wargaming Team.”
 
The job of technology forecasting has changed dramatically over the past few decades, thanks largely to the exponential growth of computing power. For example, artificial intelligence can help predict which new Wargame Exercises will be most reproducible so we will be able to get clues on the likely direction of future technological development and suggest the most profitable R&D investments.
 
Team takes a similar approach to understanding what breakthroughs are going to shift Wargaming investment, research, and development in the years ahead. But the team also connects those insights to what the Army is actually doing, using a “Multi-Domain Decision Tree” to apply data and analytics to see how one breakthrough will set the field to allow another breakthrough to help the military determine both how to invest and how to train.
 
“The goal of the Multi-Domain Decision Tree is to provide a pathway from Wargaming projects to operational advantage. “Whenever we take an idea, that idea is usually good in a wargame exercise, but then we have to figure out, how do we put that into a robust, less controlled environment? That’s a lot of what we do in tech development efforts.”
 
We have to figure out how we integrate into a Multi-Domain system that can actually be procured and bought and delivered and how to have an acquisition system to make that sourcing…efficient.”
 
“Any particular discovery has to be matured, moved, iterated on, in order to actually deliver something that the Army wants and it is that pathway out that the Multi-Domain Decision Trees are trying to build.”
 
Understanding those interconnections among advancing experimental fields is creating new insights into future war, allowing the team to build out scenarios and ultimately recommendations for new concepts of operation.
 
One upcoming report will focus on moving forces around the battlefield. “Maneuver has changed. “We’re drilling down into the character of maneuver. We’re considering things like cognitive maneuver that we really haven’t considered before.
 
What happens in the information environment, for example, it can have measurable impacts in terms of your freedom of action. You can improve yours and limit your adversaries in terms of cognitive maneuver.”
 
Emerging technology, and the possibility of better integrating Multi-Domain information into attack plans, is also changing the Army’s thinking on standoff attacks — attacking a target from a safe distance. Traditionally, that has meant lobbing missiles into enemy territory. But the advent of information warfare and autonomous armed drones is changing the fundamentals of overwhelming an adversary from a distance.
 
“In the past, massing meant getting all your guns pointed at the same target and you pound it with as much artillery as you can. You have enough in a small area eventually the probability of hitting the target will allow you to achieve the effect you want to achieve.
 
But because of the nature of either the non-kinetic effects you are trying to employ…and the ability to layer different types of intelligence” — signals intelligence, open-source intelligence, satellite photos, etc. — “if they’re all connected, they can give you a precision that we haven’t had before.”
 
The ability to much better collect intelligence from the battlefield and then deliver massive effects of various forms to any target is ultimately how the U.S. would prevail in a major conflict — or at least, that’s what the current concepts indicate.
 
“We have the ability to mass in multiple domains, not just the kinetic, physical surface to surface domains. And we have this ability to mass with precision. That’s new and different. That’s what makes up convergence, this idea that you can mass with precision, in depth, as in well into enemy territory, to achieve overwhelming cognitive effects. Your adversary is now limited in his field of action and you have increased your field of action to maneuver to an area of relative advantage.
 
In a massive simulated Multi-Domain conflict, the players adapted rapidly to futuristic technologies and tactics. But their command-and-control networks couldn't keep up.
 
Robotic mini-tanks, High-speed scout aircraft, High-powered jammers and Long-range artillery, more than 16,000 simulated troops and 13 locations were all part of the recent Unified Challenge wargame modeling a host of current future Army weapons, but the 400 human players found one thing painfully lacking: a real-time digital picture that could track their fast-moving, far-flung forces over the land, air and the airwaves.
 
As the Army hastens to turn its emerging Multi-Domain Operations concept for future conflict , it urgently needs a command system that can keep up with the complexity. It was Air Force that figured this out first: They’ve been focused on Multi-Domain Command & Control (MDC2) as the critical piece of the problem from the start.
 
The problem is that Multi-Domain Command & Control isn’t even a formal development program yet, let alone a working system you can try out in an exercise. That means, so far, “we’re using current mission command systems for future weapons systems. We need a more sophisticated and powerful Common Operational Picture (COP) that can show commanders and their staffs what’s happening in real time over longer distances, at a faster pace, and in more domains.
 
“There’s just too much going on and it’s happening too fast. But the fix isn’t just new network tools.  It will take new thinking. “Leaders must have a cognitive understanding of the operational environment. It’s not just seeing something on a display. “It needs to be in your head rather than on a screen in front of you.”
 
“We need to take a hard look at…how we train leaders to plan and execute…multi-domain operations. “It was a learning process. The speed, the agility at which they moved and operated was very different. The commanders and the staffs that we had here were really impressive. “They rapidly learned how to plan, coordinate, synchronize, all the different tools that we provided.”
 
“By probably the second week, halfway through the exercise “they had created their own tools, digital products that we kept” for future use. But those improvised, short-term network fixes are no substitute for a new command-and-control system purpose-built for the new way of war.
 
Ultimately, the military is looking at artificial intelligence (AI) to help commanders and staffs make sense of masses of information quickly — but that wasn’t ready to go in this simulation, It is extremely difficult to simulate AI without the AI itself.”
 
Unified Challenge Multi-Domain Operations Simulation was a massive and expensive endeavor that took a year of planning. Unified Challenge was so labor-intensive, in fact, the Army isn’t currently planning any further wargames with so many human players and so much detailed simulation, instead turning to a series of smaller and more focused experiments.
 
The two weeks of wargaming, plus a week of prep time for participants, involved 400 human players at 13 locations across the country. The troops took on the roles of commanders and staffs at the division, brigade, battalion, and company level, directing over 16,000 simulated soldiers — four brigades — whose weapons and vehicles were modeled in detail.
 
The simulation was sufficiently detailed to output reports on exactly how many rounds were fired and how much fuel had to be provided. The Army wouldn’t divulge the scenario, but we can make some guesses. Without Navy or Marine Corps participation, the simulated war zone was, in the words of stray remark by one briefer that the simulated combat zone was cramped — “this a pretty tight area to operate in.”
 
For all this detail, however, there was one major omission: Troop behaviour. While a “will to fight” model is in development, it wasn’t ready for Unified Challenge, and determining when troops are likely to break from casualties, exhaustion, or shock is highly subjective. So the simulated troops performed far more consistently than real humans do in combat.
 
That said, Unified Challenge did go a long way to replicate the stress, confusion, and adrenaline at command posts as the human players directed their virtual forces for two weeks of warfare. It’s the complexity at those command posts which the wargame really was wrestling with — and which will prove a daunting challenge in the future.
 
Why is the new concept, Multi-Domain Operations, so complicated to command and control? To understand the future, you need to understand the past.
 
For decades, US military planners have used a rigidly step-by-step approach to reduce the chaos of conflict to manageable tasks. First, US forces deploy by train, truck, plane and ship. Then Air Force, Navy, and Marine Corps airpower decimates enemy defenses. Finally, ground troops roll in. US forces are assumed to have unlimited access to the sea, the air, and the electromagnetic spectrum, allowing them to move forces, supplies and data unopposed.
 
After years of study, the Army and the Air Force decided the best way to fight back was to fight in all domains at once. The Navy and Marines remain skeptical. Instead of the rigid old-school sequence, the US would simultaneously attack via land, sea, air, space, and the electromagnetic spectrum.
 
But such a symphony of violence is extremely complicated to coordinate. For example, the traditional system would divide up the map, leaving distant areas for Air Force strikes while reserving targets closer to the frontline for Army artillery.
 
But in Multi-Domain Operations, what forces can hit what targets may change moment to moment. Hacking or jamming an enemy radar, for instance, might briefly open a corridor for aircraft, only to have it close again as the enemy adapts.
 
So how do you decide, in each fleeting instance, whether to use an F-35, the Army’s new long-range artillery, or something entirely different, say a network attack that can shut down the enemy without risking lives?
 
Before you can make that decision, how do you combine the data from all your different forces — satellites, fighters, drones, ground robots, human soldiers with AI-assisted goggles — to form a single coherent picture of what’s happening? And how do you share that picture when enemy hacking and jamming may cut your communications to any given unit at any time?
 
Network electronic warfare proved a vital tool in this wargame. “If you’re not dominating the electromagnetic spectrum, at least in places… then you’re going to have a very difficult time.  But these so-called non-lethal or non-kinetic “effects” weren’t necessarily decisive at the down-and-dirty tactical level of the brigade. Old-fashioned physical fighting is still essential.
 
So is old-fashioned initiative. Micromanaging your far-flung subordinates or asking your superior for authorization becomes impossible when communications can be cut off at any time. That puts a premium on what the Army calls “mission command,” in which superiors give subordinates a clear objective but also provide wide discretion in how to achieve it.
 
Mission command “becomes even more important on the future battlefield…when you can have a brigade operating on its own without communications with higher echelons.
 
The challenge is creating a command-and-control system that can intelligibly display all the data that pours in when the network is working — but then keep on fighting when that digital eye goes blind.
 
1. Combining highly capable, multifunction aircraft with additive, disaggregated systems
 
Collaboratively teaming disaggregated capabilities and highly capable aircraft could greatly enhance mission effectiveness. The loss of a disaggregated platform will not jeopardize the functionality of an entire system.
 
 2. Empower collaborative teaming operations that diminish the vulnerability of military architectures. 

Although highly capable systems now in the force perform certain functions exceedingly well, their limited numbers constrain a commander’s strategic options. Moreover, the loss a handful of systems, can have a high impact on operations.
 
3. Disaggregated platforms, even those with advanced capability, will likely be more affordable and can be procured in greater numbers than highly capable platforms. 

Sensors and systems integration represent a growing percentage of the cost of major new capabilities. Decreasing the quantity of sensors on future platforms could help decrease their size, weight, complexity, and overall unit cost. Lower program costs will allow DoD to buy more new systems and grow its force capacity.
 
4. Augmenting highly capable aircraft with disaggregated platforms could accelerate the development, testing, and fielding of a future force design. 

The more complex a weapon system, the more time it takes to develop, test, and field it. Shifting toward procuring more disaggregated platforms could help reduce the time needed for DoD to create a force design derived from an overarching operational concept that overcomes deficiencies that competitors can target. needed to support overall strategy. 

5. Creating a mixed force of highly capable and disaggregated platforms capable of operating in dynamic, collaborative ways so commanders can tailor task forces to meet operational needs across the conflict spectrum. 

A more modular force structure would allow operational commanders to configure task forces better to achieve desired outcomes and help ensure that highly capable systems are not overtaxed supporting low-end missions. If a commander can compose the force that will make up a warfighting system near the time of conflict, then the uncertainty of anticipating the far future and its consequences on the requirements and acquisitions process is lessened.

6. Services must grow its force structure so it can provide the degree of domain control and density of attacks needed to maintain the initiative and prevent an adversary from adapting to its operations. 

Services must increase quality and quantity of high-end highly capable platforms, disaggregated systems, and resilient enablers that will connect them in the future battlespace.

7. Services must be able to rapidly field a force composition that surprises future adversaries and denies them the ability to predict and prepare for its military operations. 

 Surprise cannot be realized by a force that requires months to attain the degree of connectivity needed to ensure its full functionality. Quickly composing disaggregated capabilities into forces that surprise adversaries will require every element of the future force to be highly interoperable.

8. Services networks and information architectures must be flexible, adaptive, and resilient. 

This does not mean more hardened and denser. Instead, future architectures should push information to specific forces and capabilities when and where needed, rather than everything to everything and all the time. This degree of flexibility will require the capability to maneuver information across the network and around threats when necessary.

9. Services future force must be able to withstand virtual or actual combat attrition 

No platform can be a single point of failure whose loss has a disproportionately negative impact on the force’s operational effectiveness.

​10. Force design must provide decision superiority despite the attempts of an adversary to disrupt OODA cycles at all levels of operations. 
 
An operational and information architecture that can both outpace adversary information operations and withstand attempts to degrade Observe–Orient–Decide–Act OODA decision-making cycles will be critical to prevailing in future conflicts.
 
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Top 10 Decision Structure Contributes to Analysis Standards Solutions Utilise Info/Task Execution Tech

7/20/2020

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During disasters or attacks do commanders have the ability to alter their decisions towards creating and implementing policies? If so, how? Problem Solving using probabilities tech would  alter policy choices amid crises, and  Navy needs to learn how.

In the latest Budget, Navy/Marines have both placed initiatives and a larger share of their emphasis  on learning. Senior leadership has recognized that if the Services are truly going to transition into a more distributed force, their Sailors and Marines need to be better decision makers.

There is a varying need and depth of decision-making instruction based on an individual’s rank, position within their community, and their operational environment. Because of this demand signal, leaders have called for implementation of a new component for strategy, decision science.

But isn’t decision-making already a part of our job description? What is this “decision science” how does it help the Navy and Marine Corps team? With this overarching question in mind, the Commandant’s new learning could not be a more timely, relevant, and essential doctrine for the Navy and Marine Corps to adapt to this new challenge.

The Chief of Naval Operations has called for incorporating “decision science” training into leadership development programs throughout the Navy to improve the service's understanding of human judgment and decision-making—such decision science training has only been experienced at the highest Captain and flag-levels.

Improved decision-making is a decisive advantage in stressful conditions and enables successful mission command, for example reacting to factors contributing to the decision in tactical operation. Much of it has to do with how quickly the decision has to be made, along with how much information is needed to make the decision.

If commanding officers received this lucrative "flag-level" training, one thing is certain the tools of decision science would be a beneficial tool for their judgments. So how can decision science aid decision-makers?

There is still much to be discovered, but it’s best to start with bringing structure to what decision science could mean and answering how the Navy got here.

Decision science focuses predominantly on choices in highly uncertain environments-- over arching themes cam be broken down into a collection of three core elements:

Analysis: how decisions ought to be made.

Description: how decisions actually are made.

Interventions: efforts to try and change the two

Decision science is not a combination of decision making operations research, and data science. It’s a fundamental shift in how to approach problems with probability tech.

And it is definitely not equal to data science alone. Data science is “the ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it.” While the Navy and Marine Corps are heavily investing in operations research and data science, decision science has not experienced such prominent support and investments to date.

In addition to prescribed number crunching frameworks for decision making, leaders who are well-versed in decision science can structure decision environments to achieve better judgments. This method involves carefully examining how choices are structured, what incentive and feedback structures are in place, how value judgments are made and distinguished from scientific judgments, how uncertainty is expressed, and what types of path dependencies exist.

Though the curricula may need to be left with outside experts, it will be essential for both civilians and military members to work together to form frameworks to help implement decision science in the Navy.

What Is a Decision Science Framework?

Consider the following two problems:

Problem 1: Imagine an aircraft carrier has just completed a port visit in country where a new bug has been spreading. Several days after the visit, 600 Sailors catch the bug and are expected to be lost. There are two alternative treatment programs. If Program A is adopted, 200 Sailors will be saved. If Program B is adopted, there is a one-third probability that all 600 Sailors will be saved and a two-thirds probability that no Sailors will be saved. Which do you prefer, Program A or Program B?

Problem 2: Imagine an aircraft carrier has just completed a port visit in country where a bug has been spreading. Several days after the visit, 600 Sailors catch the bug and are expected to be lost. There are two alternative treatment programs. If Program C is adopted, 400 Sailors will be lost. If Program D is adopted, there is a one-third probability that nobody will be lost and a two-thirds probability that 600 Sailors will be lost. Which do you prefer, Program C or Program D?

This decision-making experiment has been replicated dozens of times. Most individuals responding to Problem 1 preferred Program A (the certain outcome of saving 200 Sailors) and most responding to Problem 2 preferred Program D (the gamble). However, Program A/C and B/D have the same outcomes.

In applying the decision science framework to this case, you can immediately see that making an accurate and informed decision requires reliable data on the expected lethality of the virus, and the probabilities of survival of the different treatment programs.  Obviously, in the current environment, it is nearly impossible to know "expected values” of every situation.

However, applying decision science concepts enables leaders to critically and methodically work through decision-making situations in ways that mitigate the influence of biasing factors such as the framing of the information.

This is just one foundational way that decision science can be applied, so how does it apply to leaders within the Navy?

Despite dramatic technological gains the Navy has recently experienced numerous operational and administrative decision-making failures. While politics influenced these situations immensely, a number of problems were exacerbated by confirmation and sunk cost biases that hindered sound decision-making by members of the fleet.

But before we begin to implement or talk about AI, data science, or technology in assisting decision-making, service members need to recognize biases in our own decision-making process. Technology may have changed, but the way we approach decision making has relatively stayed the same – this is the value add with decision science.

Whether it’s a commander using probability tech-- what is the chance a desired outcome will materialize, on the bridge of the ship or a Marine leader operating in combat, the Navy and Marine Corps need to be more proactive at adopting the concepts of decision science to better equip their Sailors and Marines. The Marine Corps does teach decision-making to its officers at The Basic School and Infantry Officer’s Course, but overall there needs to be more reinforcement.

What do recent Navy Instructions reveal to the rest of the service? It was the first of its kind to bridge the applicability of decision science techniques to topics the Navy cares about. Several components of the document referencing decision making include:

Understanding the rise of global information systems, especially the role of data in decision making, is one of the forces that continues to shape our modern security environment

Establishing data-driven decisions as a foundation for achieving readiness in the warfighting enterprises by developing and maintaining authoritative and accessible data for decision-quality information.

Using quantitative techniques, data-driven analysis, and other research to catalyze Navy leadership development by the end of 2020 and using science-based practices and training to support leader development and better decision making.

The report states:

“In the Decision Science Environment, where leaders have to deal not only with incomplete data but also with analysis and decision making in a world that involves overwhelming data, essential elements of future success include: ability to evaluate information, reason strategically, act decisively, possess good judgment, creativity, and excellent analytic and problem-solving skills.

Navy force must be more proficient by improving strategic thinking, increasing geopolitical awareness, building key technical and professional capabilities, and deepening our understanding of the conditions in which military force can be used effectively.

With these goals articulated and underpinned by the right measures, the Navy is on the right track. Updating training programs to leverage recent advances in the field or decision science will be key in preparing Sailors and Marines for combat in the future. 

Decision Making Science is Essential for Distributed Military Operations where informed decisions requires foundational understanding of the human influence in decision making. Advances in weapons systems, Command, Control, Communications, Computers, ISR, and Targeting, data analytics, machine learning, and artificial intelligence have accelerated the pace of warfare, forcing humans to make rapid decisions under conditions of risk and uncertainty.

In order to maintain an edge in decision speed and quality, we will need to augment human cognition with machine driven analysis. The return to great power competition has necessitated the rapid development and evolution of the methods and tools by which war is conducted, and at the same time has re-emphasized the importance for understanding the timeless nature of war.

Despite technological advances, modern equipment relies on dated and vulnerable infrastructure that can be compromised by forms of enemy interference – potentially leaving operating forces in an environment denied of GPS data, communications, situational awareness, or command and control capabilities.

An operating environment that is uncertain, complex, disorderly, and fluid requires Commanding Officers and their subordinates to make sound decisions, act independently, and conduct combat operations within the commander’s mission and vision – working in a dynamic risk environment without the ability to seek advice and guidance from superiors.

The ability of each Sailor and Marine to be critical, reason strategically, and exercise good judgment and decision-making under conditions of risk and uncertainty is a common strand uniting both the conduct of naval operations on the leading edge of technology and in a technology-compromised environment.

“So What”? Is Every Marine Rifleman going to be a Decision Scientist? Every Sailor firefighter a Decision Scientist?

While all individuals benefit from understanding the concepts of decision science, not everyone needs to be a decision scientist—much can be left to  experts. However, the Navy needs to train more than just flag officers, it must train the rest of the force on such a critical piece of a Sailor and Marine’s job description, decision-making.

Expert supervision will be required to develop and initially administer training force wide. Leaders need to understand enough to require a thorough analysis of decisions and ask the right questions – especially in distributed maritime operations.

 Navy does have the skill to provide this analysis – they just do not presently have a structure to make it work. The demand signal is growing but it will take time to develop the required expertise at the unit level, the sooner this happens the better.

There currently is not a clear pathway to implementation of these concepts in both the Navy and the Marine Corps and it remains to be seen how leadership will incorporate the field of decision science into the force.

 Leaders must incorporate decision science into their organizations to meet this demand, and more importantly, enable access to the tools to be better decision-makers.
​
Summary of the Intelligence Community’s Analytic Tradecraft Standards
 
1. Sourcing
 
Provide at least basic descriptions of the sources of information that support each analytic conclusion e.g., “according to a senior official with firsthand access, ; identify key sources that are most important for each analytic conclusion; be transparent about the quality of available sources.
 
2. Uncertainty
 
Explain the level of uncertainty for each analytic conclusion; use approved terms e.g., “likely” or “very likely” to express the likelihood that the assessed event or outcome will occur; express a confidence level based on the quality of the overall analytic argument.
 
3. Distinctions
 
Distinguish between underlying evidence, assumptions, and analytic conclusions; consistently use “signaling language” to alert decision-makers as to the type of information they are reading; be transparent about key assumptions that underpin each analytic conclusion.
 
4. Alternatives
 
Identify at least one plausible alternative for every major analytic conclusion to mitigate surprise or alert decision-makers of low-probability/high-impact situations; identify indicators that, if detected, would alert decision-makers that an alternative conclusion is becoming more likely.
 
5. Relevance
 
Ensure analytic products are tailored to the needs of decision-makers; provide deeper insights to decision-makers by addressing second- and third-order impacts; conduct opportunity analysis as appropriate.
 
6. Argumentation
 
Prominently present a main analytic conclusion up front; subordinate analytic conclusions should support the main conclusion; skillfully combine evidence, logic, assumptions, and information gaps to support analytic conclusions.
 
7. Analytic Line
 
Be transparent about how analytic conclusions are consistent with or different from previously published analysis; alert decision-makers if there are significant analytic differences between two or more intelligence organizations.
 
8. Accuracy
 
Ensure clarity of message in all analytic products; do not avoid difficult analytic conclusions in order to minimize the risk of being wrong
 
9. Express absolute, rather than relative, probabilities
 
Many Reports contain language for example, “likely” instead of “more likely”; the agency also requires its analysts to assess events, actions, or behaviors instead of cognitive states or beliefs.
 
10. Visualization
 
Use visual information to clarify, complement, or enhance the presentation of analysis.
 
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Top 10 Analytic Tradecraft Scenarios Approach with Common Framework for Critical Intelligence Sourcing

7/20/2020

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Army has not adopted standards for all-source intelligence, leading to an analytic workforce that is less proficient in applying tradecraft than industry counterparts.

The root cause of this failure is in concluding that analytic tradecraft standards are applicable only at the strategic level.

At higher levels, the value of analytic tradecraft is more obvious because intelligence analysts are focused on supporting senior decision-makers who often approach problems deliberately and address longer-term issues.
Some say analytic tradecraft is incompatible with the rapid pace of operations at lower echelons, in which commanders are focused on preparing for local battles and operations.

This misconception is preventing the Army from recognizing an opportunity to help its intelligence analysts overcome the limits of intuition and ensure rigor in their analytic products.
​
Analytic tradecraft standards are based on universal principles for critical and creative thinking that can be applied in any environment.
 
One of the primary goals of analytic tradecraft is to mitigate cognitive biases, an inherent weakness of intuition that occurs when pre-existing behavioual models influence how people perceive their environment.
 
Cognitive biases can cause analysts to view complex problems through the narrow filter of their individual experiences and subconsciously ignore ideas that are inconsistent with pre-existing models.
 
Cognitive biases are a universal problem because they can occur in any situation involving human processing or perception. In the realm of military intelligence, they are particularly prevalent at lower echelons because analysts tend to default to familiar frameworks when faced with the pressures of a battlefield.
 
So analytic tradecraft standards have wide utility beyond the strategic-level organizations — such as national intelligence agencies and combatant commands — that have already implemented them.
 
It is important to distinguish between analytic tradecraft standards which have widespread value and the manner in which they are applied and enforced, which varies by organization.
 
The failure to make this distinction is behind the tendency to view analytic tradecraft as being relevant only at the strategic level.
 
The intelligence community’s analytic tradecraft standards are broad and reflect universal principles that can be used even outside of an intelligence context. However, these standards have gained acceptance only among national intelligence agencies and the military’s combatant commands, reinforcing the misconception that analytic tradecraft is useful only at the strategic level.
 
Furthermore, many of these organizations employ deliberate processes to apply and enforce standards, such as structured analytic techniques and layered reviews of analytic products.
 
As a result, some may incorrectly conclude that the Army must employ these same deliberate processes if adopting tradecraft standards. This misconception exists because of a failure to visualize the different ways that analytic tradecraft can be tailored and employed at all levels throughout the Army.
 
The following scenarios  illustrate how analytic tradecraft standards can improve all-source intelligence analysis at lower echelons just as much as they can at the national level.
 
These standards have universal value because they are broad and allow each organization to apply and enforce them in a tailored manner.
 
The prevailing view that tradecraft standards are applicable only at the strategic level requires challenges. In fact, cognitive biases — one of the primary reasons for adopting analytic tradecraft standards — are arguably most prevalent at lower echelons.
 
As analysts encounter unexpected and time-sensitive events on the battlefield, they must be guided by a common framework for critical and creative thinking that increases the chances of suppressing cognitive biases.
 
Otherwise, their assessments will be undisciplined reactions to chaotic circumstances based solely on their individual intuition.
 
The intelligence community’s analytic tradecraft standards provide a proven mechanism to ensure all-source intelligence analysis is conducted with a level of rigor that commanders expect and deserve.
 
Once these standards are adopted, the Army can immediately begin improving how it develops all-source intelligence analysts without significant disruptions to existing training programs.
 
Tradecraft training does not require specialized equipment or facilities. Furthermore, the Army can leverage its organizational relationships throughout the intelligence community to solicit advice and expertise. The easiest way to initiate improvements to training would involve adjusting evaluation standards to be consistent with the intelligence community’s analytic tradecraft standards.
 
For example, during mock briefings to commanders, instructors can ask trainees to explain the confidence level associated with their assessments and evaluate how well trainees understand the components of an analytic argument.
 
Some tradecraft standards have direct parallels with Army doctrine and may already be employed as best practices at lower echelons. However, they are not formal standards that are routinely enforced across the Army, leading to inconsistent or incorrect application.
 
The Army has an opportunity to be a leader among the military services by being the first to implement analytic tradecraft standards and enhance collaboration with the rest of the intelligence community.
 
An outside report concluded uniformed analysts assigned to combatant commands are not as proficient in applying analytic tradecraft as their civilian counterparts.
 
This disparity in tradecraft proficiency has exacerbated existing interoperability issues within the all-source analytic community. Army analysts are providing assessments to commanders without using the same framework for critical and creative thinking as combatant commands.
 
This situation creates problems when decision-makers at different levels interact to address common national security issues, each operating based on intelligence assessments developed using different standards, or no standards in some cases.
 
Each military service will require its own approach to implementing analytic tradecraft standards. The first hurdle to overcome is to ensure shared awareness of how the Army can benefit from implementing such standards.
 
What follows are example scenarios that illustrate the benefits of analytic tradecraft standards at all levels, and the consequences of not having such standards.
 
1. Defending an analytic argument
 
An Army battalion commander disagrees with the unit intelligence officer’s assessment that the enemy main attack will occur in a particular area and asks, “How did you arrive at your analytic conclusion?” The intelligence officer’s familiarity with tradecraft standards makes him well postured to explain the analytic argument to the commander. There are multiple components of an argument: analytic conclusions, evidence or raw reporting from intelligence collectors, logic that links evidence to analytic conclusions, assumptions, and information gaps.
 
2. Examine components in an integrated manner
 
Close examination mitigates cognitive biases and logical false conclusions. More importantly, the intelligence officer understands how the commander likes to receive information and provides a concise explanation of the reasoning behind the original assessment. The Army’s adoption of a common framework for critical and creative thinking will ensure that intelligence officers across the force are not relying purely on their individual intuition when having these types of conversations.
 
3. Common framework for analytic collaboration
 
The commander for a deployed Army brigade combat team asks the intelligence staff for a deep-dive briefing on an emerging issue. It is already 7:00 p.m. and the commander wants the briefing at 6:00 a.m. tomorrow morning. The brigade intelligence staff reviews assessments written by subordinate units. Many of these assessments contain declarative statements without common signaling language to distinguish raw intelligence reporting from an analyst’s assumptions or application of judgement. For example, one subordinate unit writes that “the enemy will be unable to operate its tanks for the next 48 hours due to fuel shortages.” Brigade analysts cannot determine whether this sentence is an assumption, raw reporting from a single source, or an analytic conclusion based on multiple sources, making it difficult to evaluate its importance in the overall intelligence picture. This problem grows exponentially as this brigade collaborates with other units.
 
4. Graphically displaying enemy courses of action
 
Intelligence analysts in an Army brigade combat team are creating a situation template, a graphical depiction of an enemy’s most likely course of action on a battlefield. The brigade’s analysts realize that sourcing tradecraft standards requires them to describe the sources used in their products. However, it may not be possible to describe every source used in the situation template. As a result, the analysts prioritize and describe only the three most important sources.
 
5. Adhere to  tradecraft standards to identify hierarchy for assessments
 
The main analytic conclusion is that the enemy will likely conduct a mobile defense. Analysts also include two subordinate analytic conclusions that characterize the doctrinal components of a mobile defense: a fixing force that will prevent the opposing side from escaping the area and a striking force that will destroy the opposition. In this example, analytic tradecraft enabled the underlying critical thinking process and helped analysts organize their thoughts before creating the situation template.
 
6. Being open to alternative analytic conclusions
 
 
The commanding general of a deployed Army division asks the intelligence staff for an assessment on a complex issue. In their search for plausible answers, the division’s analysts rely on their intuition as experienced military intelligence experts. While valuable, intuition also has pitfalls that must be acknowledged and mitigated. Division analysts rely on their past experiences to help frame their assessments on the current problem, that leads to cognitive biases in which intuition, over time, causes analysts to perceive patterns based only on what they are familiar with, instead of what is actually occurring. The division’s analysts fail to employ structured analytic techniques to determine plausible alternatives to their main assessment. Furthermore, they do not identify specific indicators that would alert the division commander that their analytic conclusion may be incorrect, missing an opportunity to provide a complete picture of the uncertainty inherent in the situation.
 
7. Transparency about key assumptions
 
An Army corps preparing for large-scale combat operations is monitoring the adversary’s elite armored divisions. The adversary upgraded some of its tanks, but they were issued only to the elite divisions. Corps analysts make an assumption that this practice will continue. Collectors in the field detect unique signatures consistent with four upgraded tanks as part of a larger movement of forces by the adversary. As a result, corps analysts assess that the adversary is beginning to deploy one of its elite armored divisions into the area, alarming the commander. However, this assessment turns out to be false: The four upgraded tanks are part of a conventional division. The adversary recently began fielding small numbers of upgraded tanks in conventional divisions as infantry support. Corps analysts were not transparent with their logic and did not conduct periodic checks of key assumptions, missing opportunities to employ collectors to confirm or deny the initial assumption.
 
8. Professional standards for intelligence analysis
 
An Army corps deploys overseas as the core of a joint task force in anticipation of armed conflict as tensions escalate with an adversary nation. The joint task force commander is predominately focused on operational matters, but there are significant national policy implications. Disagreements emerge between the joint task force and policy advocates over how to define the key issues of the crisis. The commander makes public statements that contradict the views of  policy advocates and stating that intelligence analysts are better postured to understand the crisis. In order for this reassurance to have credibility, the Army must have uniform standards for critical and creative thinking for its intelligence analysts. The Army has its own analytic processes — such as intelligence preparation of the battlefield — but currently has no formal standards to ensure rigor as analysts navigate through these processes. Analysts are largely left to rely on their intuition.
 
9. Interoperability with the intelligence community
 
The same Army corps from the previous scenario continues serving as the core of a deployed joint task force. What started out as a purely military problem for the joint task force has now become part of a tense national debate involving policymakers and Congress. Given the increased stakes, joint task force intelligence officers begin collaborating with senior analysts from national intelligence agencies. Joint task force analysts do not have prior experience with analytic tradecraft, making it difficult for them to adjudicate disagreements with their national-level counterparts. Many deployed analysts, for example, use anecdotes and assessments from lower-echelon commanders as building blocks in their analytic products. While valuable, battlefield anecdotes are not processed with the same rigor and standardization as raw reporting from national-level intelligence collectors. The lack of common standards for intelligence analysis makes it difficult to produce a unified view of the crisis across the entire chain of command.
 
10. Analytic tradecraft standards during time-sensitive operations
 
New candidate is assigned as the senior intelligence officer  for a brigade combat team after a tour at the Defense Intelligence Agency. The candidate intends to adopt some of the agency’s processes and implement them throughout the brigade intelligence staff, relying specifically on recalling how the agency applies and enforces tradecraft standards in time-sensitive and crisis environments.  For example, agency analysts still adhere to tradecraft standards when producing the Defense Intelligence Digest Note, which is typically one paragraph and is designed to rapidly alert policymakers of new developments without assessing what will occur. Army analysts conduct similar tasks when they rapidly disseminate targeting or force-protection information to commanders. Additionally, the Defense Intelligence Agency relaxes its enforcement of some tradecraft standards when operating a crisis cell, but the underlying standards remain the same. Similarly, the candidate intends to adopt broad analytic tradecraft standards, while remaining flexible on how leaders apply and enforce these standards under time-sensitive circumstances.
 
 
 
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Top 10 Condition Based Maintenance Strategy Established with Tech/Process Enable Improved Practices

7/10/2020

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Condition Based Maintenance Plus CBM+ is the application and integration of appropriate processes, technologies, and knowledge-based capabilities to improve the reliability and maintenance effectiveness of DoD systems and components
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At its core, CBM+ is maintenance performed based on evidence of need provided by Reliability Centered Maintenance RCM analysis and other enabling processes and technologies.

CBM+ uses a systems engineering approach to collect data, enable analysis, and support the decision-making processes for system acquisition, sustainment, and operations.

DoD has identified warfighter expectations and made an effort to conduct support operations in a more effective as well as fiscally responsible manner. Under the umbrella of Total Life Cycle System Management TLCSM, the sustainment of a weapon system receives increased attention from Service leadership and program managers.

TLCSM establishes clear responsibilities and accountability for meeting warfighter expectations. It sets goals, tracks progress and status, and balances resources to accomplish desired material readiness.

CBM+, in concert with the other TLCSM tools, Continuous Process Improvement CPI, cause-and-effect predictive modeling and simulation M&S, and desired outcomes achieved through Performance Based Logistics PBL, will enhance materiel readiness.

CBM is an established approach to identifying and scheduling maintenance tasks. It employs continuous or periodic assessment of weapon system condition using sensors or external tests and measurements through first-hand observation or portable equipment.

The goal of CBM is to perform maintenance only when there is evidence of need. Integrating the enabling CBM+ capabilities builds upon the foundation of CBM. CBM+ continues to evolve from this original concept into the maintenance improvement strategy.

CBM+ includes a conscious effort to shift equipment maintenance from an unscheduled, reactive approach at the time of failure to a more proactive and predictive approach that is driven by condition sensing and integrated, analysis-based decisions.

CBM+ focuses on inserting technologies that improve maintenance capabilities and processes into both new and legacy weapon systems and integrates the support elements to enable enhanced maintenance-centric logistics system responses.

With more accurate predictions of impending failures based on real-time condition data, coupled with more timely and effective repairs, moving toward CBM+ will result in dramatic savings—in time and money—and improved weapon system availability and performance.

CBM+ uses modern maintenance tools, technologies, and processes to detect the early indications of a fault or impending failure to allow time for maintenance and supply channels to react and minimize the impact on system operational readiness and life-cycle costs.

CBM+ provides a means of optimizing the approach to maintenance, and is a vehicle to reduce scheduled maintenance requirements. The flexibility and optimization of maintenance tasks with CBM+ also reduces requirements for maintenance manpower, facilities, equipment, and other maintenance resources.

CBM+ is not a single process in itself. It is a comprehensive strategy to select, integrate, and focus a number of process improvement capabilities, thereby enabling maintenance managers and their customers to attain the desired levels of system and equipment readiness in the most cost-effective manner across the total life cycle of the weapon system.

CBM+ includes a variety of interrelated and independent capabilities and initiatives—some procedural and some technical— that can enhance basic maintenance tasks. At its core, CBM+ is maintenance performed upon evidence of need provided by RCM analysis and other enabling processes and technologies

To satisfy the requirements of a changing Defense Strategy, maintenance managers are challenged to apply CPI concepts and tools to improve maintenance agility and responsiveness. The goal is to increase operational availability and readiness and to reduce life-cycle total ownership costs by performing only the required repairs at the optimum time, and by reducing stocks of spares and repair parts to support maintenance operations.

CBM+ supports these objectives by encouraging the Services to employ condition monitoring technology and reliability analysis, such as RCM, to optimize operations and supportability of major systems

More effective maintenance requires a change in the culture of the maintenance community from a primarily reactive maintenance approach to a proactive, planned maintenance approach.
In this sense, initiatives like CBM+ must adopt a dynamic approach for evolving a set of capabilities, as opposed to perfect planning, development of comprehensive requirements, or comprehensive reengineering.

CBM+ initiatives include fully developed technologies and processes that can be implemented now as well as yet-to-be developed capabilities. CBM+ also uses proof-of-concept and prototype activity that can be applied incrementally, not waiting for a single solution package. To maintain consistency, CBM+ development should be based on a broad architecture and an enterprise framework that is open to modification and can be easily adjusted.

CBM+ represents a continuous development of maintenance processes and procedures that improve capabilities, practices, and technologies. CBM+ is a part of the transformation of maintenance practices from the Industrial Age to the Information Age through the appropriate use of emerging technologies to analyze near-real-time and historical weapon systems data to provide a predictive maintenance capability.

The challenge of CBM+ is to provide tangible effects to DoD operations across all categories of equipment. CBM+ is an opportunity to improve business processes, with the principal objective being improved maintenance performance across a broad range of benefits, including greater productivity, shorter maintenance cycles, lower costs, increased quality of the process, better availability, and enhanced reliability of materiel resources

All desired readiness improvement technology enhancement, readiness, or new process improvements must be developed or acquired. This includes the use of resources that are always limited.

Even with a policy that requires its implementation, CBM+ has to “buy its way” into the program.

Service leadership and the program and support managers want to do the right thing for the warfighter, but a return on the investment must be identified and justified. In the long run, any Service effort to develop and deploy CBM+ should be leveraged by other platforms and programs.

Guidebook describes the actions necessary to integrate these component elements into an operational capability for more effective and efficient support of the operational customer— the warfighter. The benefits to the warfighter can best be described within the context of three levels: tactical, operational, and strategic.

At the tactical level, CBM+ may mean new tools, test equipment, and embedded onboard diagnostics. These tools take advantage of current and emerging commercial and diagnostic technologies that translate system condition data such as temperature, vibration, cycle-time in combination with environmental factors like desert, arctic, and high humidity into proactive maintenance actions that are performed only when there is evidence of actual need.

With CBM+, maintainers can convert weapon system or equipment condition data into proactive maintenance actions. Scheduled inspections are supplemented or replaced because maintainers will have analytical data that describe the condition of the weapon system and its components.

To the commander at the operational level, CBM+ brings the ability to meet mission requirements and increase weapon system availability. CBM+ provides commanders, mission planners, and logistics providers with information that enables better maintenance decision making and mission assignment. CBM+ supports Focused Logistics by enhancing command situational awareness at the weapon system level.

While some CBM+ features are installed at individual platform level, the benefits of CBM+ are most effectively achieved when an entire fleet is incorporated and the information is leveraged. At the strategic level, CBM+ identifies maintenance actions based on a near-real-time assessment of equipment status from diagnostic sensors and equipment.

Data collected from embedded sensors, such as usage monitoring systems are then translated into predictive trends or metrics that anticipate when component failures will occur and identifies components that may require redesign or replacement to reduce high-failure rates.

Common use of items and data among the Services on like-systems will greatly reduce logistics footprints and costs/directives to ensure implementation in organic i.e., DoD in-house maintenance capabilities and operations as well as in commercially supported DoD systems and programs for both new and legacy weapon systems.

Institutionalization of the CBM+ strategy in relevant regulatory publications is the first step toward attaining the ultimate end state. The envisioned CBM+ operational environment will occur from the individual component to the platform level, in training courses, and the deployed environment.

Initially, Defense Acquisition Programs will exploit CBM+ opportunities as elements of system performance requirements during the design and development phase and throughout the life cycle. Once implemented, CBM+ will be the primary reliability driver in DoD’s TLCSM supportability strategy.
In concert with the other TLCSM enablers like CPI, cause-and-effect predictive modeling, and desired outcomes achieved through PBL, the implemented CBM+ strategy will help optimize key performance measures of materiel readiness—MA, MR, MDT, and OC.

Ideally, the desired CBM+ end state is a trained force of maintainers from the tactical field technician to the strategic system analyst working in an interoperable environment to maintain complex systems through the use of CBM+ processes and technologies.

Fully implemented CBM+ improves maintenance decisions and helps integrate all functional aspects of life-cycle management processes like acquisition, distribution, supply chain management, and system engineering.

The life of equipment will be extended if proactive maintenance is performed on weapon systems, equipment, and components as the designer envisioned. Proactive maintenance, like lubrication and filter changes, or even more extensive replacement of failure causing parts, will generally allow the equipment to run more efficiently and last longer, resulting in savings and greater readiness.

While it will not prevent all catastrophic end item failures, proactive maintenance will decrease the number of failures and overall equipment downtime. Minimizing these failures translates into savings in both maintenance and future capital equipment replacement costs.

Because of the inherent randomness of individual item failures, proactive maintenance cannot eliminate all failures. When failure does occur, corrective maintenance will be required.

1. How will readiness, availability, ready for tasking, down time (parts or maintenance), and/or unscheduled down time be affected?

Identify specific MOEs and metrics that are critical to support the customer expectations. Ensure that definitions are provided within assumptions and appropriate measures identified for analysis. Minimize the number of metrics being evaluated to ensure reasonable amount of effort is required to obtain and analyze data to arrive at fair and reasonable conclusions and recommendations. Impact should be assessed using the primary CBM+ metrics ‐ Operational availability, material readiness, total ownership cost, and mean downtime.

2. How does this initiative improve the overall awareness of equipment condition at the tactical and strategic levels?

Identify and define any potential systems interfaces, data exchange, decision processes, planned integration, and customer expectation in the key assumptions. Address incremental capability improvements that may impact the CBM+ ROI as new increments become available or are integrated into the overall maintenance and logistics processes. Ensure that relevant CBM+ functionality areas (fault detection, isolation, prediction, reporting, assessment, analysis, decision‐support execution, and recovery, both on and off‐board) at the operational/ tactical command and strategic levels are assessed and addressed in the conclusions and recommendations.

3. How does this initiative increase the accuracy in failure prediction and situational awareness?

Identify specific system/sub‐system/component and existing performance levels (failure rate, etc.) that the CBM+ capability is targeted to support. Define and analyze related the CBM+ functionality areas of fault detection, isolation, prediction, reporting, assessment, analysis, decision‐support execution and recovery, both on and off‐board.

4. What is the projected impact on system/component level replacement frequency?

A CBM+ capability can provide the source data and analytical capability to determine projected Remaining Useful Life (RUL), repair/replace decisions, maintenance task frequency, etc. In defining the scope of the BCA ensure that any Reliability Centered Maintenance (RCM) and diagnostic/trending data is used to define assumptions and establish a system/component maintenance/replacement MOEs baseline from which the overall CBM+ capability cost and benefit can be assessed.

5. What cost, schedule, and performance risk is projected based on proposed technology for procurement, implementation, and sustainment?

The CBM+ BCA should provide a conclusion and recommendation regarding the level of technology maturity and risk associated with the technology, including a sensitivity analysis regarding cost, schedule, and performance. Are there any contract alternatives (strategies) that will impact cost and schedule? Ensure that any known or pending contracts that may impact implementing a CBM+ capability or that may benefit from a CBM+ capability are considered when defining the scope of the CBM+ BCA. The impact on and from related CBM+ contracts should be addressed in the risk assessment and sensitivity analysis portion of the CBM+ BCA.

6. What maintenance tasks or functions can be eliminated or reduced?

The CBM+ BCA should identify potential functions, tasks, or systems/components that will be impacted by a CBM+. The level of detail that the CBM+ BCA can generate will be based on the existing system, whether an RCM analysis has been done, and what level of maintenance data is available. To the maximum extent possible identify the proposed capability in terms of the CBM+ functionality areas of fault detection, isolation, prediction, reporting, assessment, analysis, decision‐support execution, and recovery, both on and off‐board.

7. How can data analysis and decision making be automated to reduce support costs?

Ensure that your specific logistic or maintenance process(es) which will utilize an analytical CBM+ tools/capabilities, such as trending, diagnostics and/or prognostics, are defined and that any potential CBM+ tasks, functions, and measures of effectives/metrics that will be affected by those tools are understood. What data needs to be collected to measure the costs/benefits of the CBM+? Early Planning for the data collection will be necessary and should examine each element and metric as to the source of data and what factors will bear on its accuracy. While collection of all elements is beneficial, those response elements that are discriminators should be the focus of the CBM+ metrics planning approach. This is best accomplished by engaging the User community in that discussion as early as possible in the acquisition life cycle. What are the data sources and limitations for the data that needs to be collected? The authoritative source for each data element needs to be established and a determination of whether the data is available should be established early in the CBM+ BCA planning process.

8. Does the CBM+ initiative improve our ability (schedule/cost/technical) to modify/improve current systems or design new systems?

Identify any “system” specific capability that the proposed CBM+ capability will help improve for the existing system or for projected future increments. Identify specific incremental capabilities and external systems interfaces that the CBM+ enhances, such as connectivity to near real time/real time weapon system health.

9. What is the TOC impact?

If you are conducting a CBM+ BCA with a primarily focus on reducing TOC, ensure that you identify the specific elements of TOC within the CBM+ BCA assumptions and MOEs. Also, properly define any analysis factors for the risk and sensitivity analysis to ensure conclusions and recommendations are fairly and comprehensively reached.

10. What is the projected ROI?

Ensure that you define ROI as well as an accurate estimate of the exiting sunk cost of your existing CBM+ capability. Consider the overall life cycle of your system to properly scope the proposed CBM+ capability and define any incremental increases planned over the system’s life cycle. Also recognize that other interfacing or connected systems may make a significant ROI contribution greater depending on the application, access, and use of CBM+ data.
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Top 10 Condition Based Maintenance Implement Activities Require Elements Executed in Integrated Effort

7/10/2020

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​CBM+ must incorporate key components of the total Defense Strategy. This section describes the basic elements of CBM+ in a structured way and attempts to convey the relationships and interactions among these elements.

CBM+ elements can be categorized into two primary categories—business/management and technical subgroups within these two categories. All the CBM+ elements contribute to the development of the maintenance plan across the whole life cycle of the weapon system or platform.

DoD maintenance of Materiel policy requires minimizing requirements for support equipment, including test, measurement, and diagnostic equipment. Maintenance programs for military materiel must utilize diagnostics, prognostics, and usage management techniques in embedded and off-equipment applications when feasible and cost effective.

Maintenance programs must provide the organic maintenance workforce with the range of technological tools necessary to enhance capabilities e.g., interactive technical manuals, portable maintenance aids, access to technical information, and serial item management, to properly equip the workforce, and to provide adequate technical and administrative training
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DoD is in the process of publishing a formal policy for institutionalizing the CBM+ strategy as an element of the CPI initiative. CBM+ is a strategy to apply and integrate appropriate processes, technologies, and knowledge-based capabilities to increase operational availability and reduce total life-cycle costs by improving maintenance effectiveness and responsiveness.

CBM+ is based on performing maintenance only when there is evidence of need obtained from real-time assessments, embedded sensors, or external measurements.

CBM+ uses a system engineering approach to collect data and feed the decision-making process for operations and weapon system acquisition and sustainment.

DoD activities must establish a CBM+ environment for the maintenance and support of weapon systems by establishing appropriate processes, procedures, technological capabilities, information systems, and logistics concept.

The implementation of the CBM+ strategy in DoD maintenance organizations should not be construed as primarily the application of new methods and technologies. The basis for CBM+ is more precisely a focus on improving the business process of maintenance with the principal objective being improved operational performance as a result of increased maintenance effectiveness in terms of greater productivity, shorter maintenance cycles, increased quality of the process, and better use of resources.

DoD instructions require PMs to optimize operational readiness through affordable, integrated, embedded diagnostics and prognostics, and embedded training and testing; serialized item management; automatic identification technology AIT) and iterative technology refreshment.
In support of these requirements the TLCSM concept should be used as a vehicle for ensuring the elements of CBM+ are fully considered as early as possible in the acquisition life cycle of a weapon system or equipment.

CBM+ should be viewed as an element of TLCSM, emphasizing an early focus on sustainment within the system life cycle and part of a comprehensive view of all logistics activities associated with the fielding, sustainment, and disposal of a DoD weapon system or equipment across its life cycle.

There is a close relationship between CBM+ and Reliability Centered Maintenance RCM. RCM analysis to determine the criticality of equipment failures relative to equipment availability and the importance of the equipment to accomplishing the organization’s mission.

RCM also provides rules for determining evidence of need for CBM. Recent advances in technology, such as sensing hardware, electromechanical interfaces, data accumulation, modeling and simulation, wireless communications, and equipment health monitoring systems, can significantly improve system safety, reliability, and affordability. When implemented effectively in an integrated fashion, these and other CBM+ capabilities can improve maintenance performance and reduce funding and personnel requirements.

RCM is a logical, structured process for determining the optimal failure management strategies for any system, based upon system reliability characteristics and the intended operating context. RCM defines what must be done for a system to achieve the desired levels of safety, environmental soundness, and operational readiness at the best cost.

Specifically, RCM identifies the concepts and methods needed to select technically appropriate maintenance actions, such as predictive and preventive tasks that will prevent failure. RCM also identifies default strategies, such as failure finding tasks, engineering redesigns, and changes to operating procedures.

“If maintenance is ensuring that physical assets continue to do what their users want them to do; then, RCM is a way to determine what must be done to ensure that any asset continues to do what.

For example, the Naval Air Systems Command NAVAIR defines RCM as “an analytical process to determine the appropriate failure management strategies to ensure safe operations and cost-wise readiness.”

RCM analysis considers the failure process and related reliabilities of equipment, the severity of the related consequences of failures, and the cost effectiveness of various options to deal with failure.
In the context of RCM, there are essentially two types of maintenance: proactive and corrective. These have been presented using different terminology over the years.

Essentially, proactive maintenance actions are taken to preserve functionality often protecting safety or reducing the cost of repair and reduce unplanned downtime or impacts to mission performance. It should be noted that proactive actions by their nature require some level of investment such as to analyze, inspect, refurbish, and replace above just the correction of the failures.

The RCM process evaluates the trade-off between this investment and the overall cost. Corrective maintenance, on the other hand, responds to failures after they occur.

This may be the most effective approach for many types of equipment when the consequences of failures are acceptable or unpredictable. In a “failure management strategy,” RCM determines the proper balance between these planned and unplanned activities.

DoD’s efforts to transition from the current reactive and time-driven strategies for equipment maintenance account for current approaches have become both cost prohibitive and less than optimal in meeting today’s operational availability needs.

RCM identifies actions that, when taken, will reduce the probability of failure and are the most cost effective. One option of RCM is to choose to execute CBM actions. Once a possibility of failure is identified, it can be analyzed to determine if CBM is technically appropriate and effective.

Many types of equipment will show detectable signs of impending failure before the equipment actually fails. If an inspection of some kind can discover the deterioration between the time it is first detectable and the time when functional failure occurs , then there is an opportunity to avoid the failure.

Must establish interval to determine how often a CBM task is performed and when action must be taken to correct the impending failure. By employing CBM+ capabilities, system operators and their maintenance support team are made aware of pending failures in advance, so they are able to accomplish appropriate actions to prevent the loss of use and cost related to experiencing the actual equipment failure. It is this predictive aspect of CBM+ that clearly distinguishes this strategy from traditional approaches to maintenance in the DoD.

Successful, long-term reliance on the CBM strategy is greatly enhanced through implementation of CBM+ initiatives for improving weapon system and equipment maintenance. If CBM+ is implemented, there must be a high degree of confidence on the part of users and customers that this effort will reliably produce maximum equipment availability at a reduced cost.

The predictive capabilities instituted under CBM+ must consistently and accurately result in fewer unplanned failures, generate fewer unnecessary maintenance actions, and reduce overall costs as compared to the more traditional strategies.

As weapon systems and equipment have become more complex, the patterns of failure and the difficulty of predicting failures have also become more complex. The need to prevent or predict failures, particularly when human safety is involved, has prompted maintenance and operational managers to look for new types of failure management, particularly in the area of predictive assessment.

In some cases, it is possible to identify the potential failure condition and associated interval relatively easily when subject matter experts are asked the right questions. The focus on predicting rather than waiting for failure is based on the idea that many failures give some type of warning or show some detectable characteristic prior to the actual failure event.

CBM is used to address the capability to detect or predict deterioration or failure in advance of the actual event and to take appropriate action once there is reasonable certainty that the degradation is likely to occur in a particular time frame. RCM provides a structured and easily understandable process for determining if maintenance actions should be undertaken and when such actions are technically appropriate.

The RCM analytical approach helps the maintenance manager in identifying potential failures and supporting the selection of viable courses-of-action.

RCM tools help define the optimal failure management strategies and provide the inputs to construct the business case for implementation of the designated CBM+ strategy.

CBM+ builds on the foundation of RCM, but complements and expands on RCM by applying a broad spectrum of procedures, capabilities, and tools to improve execution of the maintenance analysis process.

CBM+ is not a process; it is a comprehensive strategy to select, integrate, and focus a number of process improvement capabilities, thereby enabling maintenance managers and their customers to attain the desired levels of system and equipment readiness in the most cost-effective manner.

CBM+ strategy includes a number of capabilities and initiatives, some procedural and some technical, that can enhance the basic RCM tasks. In this way, CBM+ enables a more effective RCM analysis.

If the RCM analysis suggests revision of maintenance tasks, then the maintenance manager should accomplish an assessment of how CBM+ capabilities may be applied to support the revised maintenance task procedures. Often, the revised tasks require fundamental changes to the maintenance strategy such as transition from time cycle repair intervals to CBM.

In other cases, application of sensor capability or diagnostic digital tools may be in order. If the proposed revisions are significant in terms of procedural changes or cost, a formal BCA may be necessary to justify the increased resource or time investment.

CBM solutions are selected based on the frequency and impact of the failure modes; the ability to employ some form of automated status sensors or other CBM+ technologies; and the expected performance, safety, or cost benefit of investing in

CBM+ capabilities ensure maintainers can identify and respond to deteriorating equipment conditions more effectively, without having to wait for a failure. CBM+ not only emphasizes a different approach, it also allows a net reduction in the amount of maintenance performed, which affects all the associated logistics elements, including parts and other footprint factors.

Clearly RCM and CBM+ have a mutually beneficial relationship. From a weapon system or equipment perspective, operational utility management of equipment without RCM analysis becomes technology insertion without a justified functionality. Conversely, collection of aggregated or platform-centric operational data without an understanding of which failure modes are consequential, and which ones are not, and the most effective course-of-action, can lead to wasted effort and unnecessary expenditure of resource

1. What is the impact on the following areas?

A CBM+ capability can provide the source data and analytical capability to determine projected RUL, repair/replace decisions, maintenance task frequency, etc. In defining the scope of the BCA ensure that any RCM and diagnostic/trending data is used to define assumptions and establish a system/component maintenance/replacement MOEs baseline from which the overall CBM+ capability cost and benefit can be assessed. For each of the following areas identify specific MOEs and metrics that are appropriate to the proposed CBM+ capability: Maintenance Planning; Manpower and Personnel; Supply Support; Support Equipment; Computer Resources Support; Facilities; Packaging, Handling, Storage, and Transportation; Design Interface; and Disposal.

2. What is the impact on total life cycle cost, including disposal?

The CBM+ BCA cost element structure should ensure that the desired costs and levels of detail are defined and analyzed to support the proposed CBM+ capability. Cost drivers should be clearly defined and will vary depending on the CBM+ capability. Hardware and software costs are primary elements regardless of the life cycle phase and will vary in scope depending on the CBM+ capability being considered (e.g., sensors, diagnostics, prognostics, etc.) . Provide a suggested cost element structure and definitions, as well as related references for use in defining your cost element structure.

3. How will fuel conservation be affected?

If the primary CBM+ capability is focused on energy conservation or fuel management, your CBM+ capability should be evaluated considering areas such as: fuel sensors/monitoring; real time fuel status; accuracy of fuel data; data transfer; fuel supply management; and system interfaces. The CBM+ BCA should identify the potential change to fuel usage and fuel management at all levels of the operational and logistics chain. Also consider possible operational benefits for improved fuel management, distribution, manning impacts, and system performance Impacts.

4. Will use of analytic techniques to predict failure or reduced performance levels affect scheduled maintenance and major replacement strategies?

Identify specific analytical tools, their projected accuracy, and their specific implementation (incremental). Utilize existing analyses, RCM studies, and historical data/information (e.g., failure data from VAMOSC) to establish a baseline for the analysis.
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5. Are there incremental performance levels?

Identify the planned CBM+ capability acquisition strategy and define how it will fit with the acquisition strategy of weapon system it supports. Define the CBM+ increments as clearly as possible and ensure boundaries and interfaces with existing logistics, Command and Control, and/or weapons systems are adequately described in relationship to the CBM+ MOEs and metrics.

6. What changes will be required for operator and maintenance personnel? And systems?

Identify known impacts to the CBM+ capability, and its parent system, to ensure that the appropriate qualitative as well as quantitative MOEs are included. These should include defined impacts to the system’s operation and maintenance, policy, changes to tactics, techniques and procedures and personnel.

7. How will the repair/replace decision be affected?

When the BCA is focused on a specific system/sub‐system or component, ensure that the scope, cost elements, and MOEs are tailored accordingly. Utilize existing RCM, cost and historical data, projected RUL estimates, any phased CBM+ capability increments, and planned system/subsystem or component enhancements, wherever possible.

8. Will the system/equipment modernization plan be affected and if so how?

Identify those system/sub‐system and/or components where the projected CBM+ capability will have a direct or indirect affect on a planned modernization improvement.

9. How will the CBM+ capability impact integration with other DoD systems?

The CBM+ BCA should identify the specific systems for which the CBM+ capability will have a direct interface or integration requirement. These areas should be clearly defined in the assumptions and include the type of interface (hardware or software), timing for the connection and all related investment and sunk costs associated with the integration. In cases where an interfacing system has been fielded, ensure that the investment costs are adequately addressed in assumptions to either include them in the analysis or if they are unknown, note that they are not included.

10. How will the CBM+ capability impact service life margins?

In cases where the primary purpose of the CBM+ BCA is to determine the effect on a weapon system’s service life, ensure that the system is properly defined and all RCM and historical data/information (e.g., Performance and failure data from Visibility and Management of Operating and Support Costs (VAMOSC). VAMOSC is utilized to define baseline MOEs and related costs.
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Top 10 Condition Based Maintenance Sensors Monitor Physical Characteristics for Signs of Impending Failure

7/10/2020

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Sensors are physical devices that monitor, record, or transmit equipment or component operating parameters or conditions. They can be permanently embedded on equipment, temporarily connected to equipment, or electronically connected in a wired or wireless mode.

Sensors may range from relatively simple single-function units to multipurpose testing equipment with embedded analytic capability. Sensors are often positioned on or near the equipment being monitored.

Equipment can be monitored using sophisticated instrumentation, such as vibration analysis and infrared thermography. When instrumentation is used, parameters can be imposed to trigger maintenance response.

Condition monitoring converts an output from the sensor to a digital parameter representing a quantifiable physical condition and related information such as the time calibration, data quality, data collector utilized, or sensor configuration.

Condition monitoring provides the link between the sensor device and the health assessment analysis capability.

Health assessment is the capability to use the inputs from condition monitoring of system behavior machine condition and to provide to the operator and support management an assessment of the equipment’s operational condition i.e., assessment based upon current measurements and related data.
Health assessments based on condition monitoring are accomplished on the platform or operating equipment in real-time.

An “on-system” health assessment includes sensor signal analysis, produces meaningful condition descriptors, and derives useable data from the raw sensor measurements i.e., model-based reasoning combined with on-system real-time analysis of correlated sensor outputs.

Health assessment facilitates the creation and maintenance of normal baseline “profiles” and identifies abnormalities when new data are acquired, and determines in which assessment category, if any, the data belong e.g., “alert” or “alarm”.

Digital Health assessment diagnoses of component faults rates the current health of the equipment or process, considering such inputs as sensor output information, technical specifications, configuration data, operating history, and historical condition data.

Equipment health assessment may also be conducted in proximity to the system—”at-system” assessments using a portable maintenance aid PMA that interfaces to the equipment indirectly through an equipment access panel or directly to line replaceable units.

The PMA is then used to update “off-system” databases for real-time or future health assessment. Systems information from inspections and non-destructive evaluations NDE are also important sources of equipment health assessments.

The long-term health assessment goal is to provide managers with predictions about the remaining useful life of the machine before maintenance is required. There are two fundamental aspects to employing CBM+ health assessment capabilities.

The first relates to on-system processing and predictive maintenance to the extent a platform is enabled with those capabilities. Generally, on-system assessment data processing is automated, and analysis is performed through the use of embedded processors.

The second aspect of health assessment is the off-system processing of collected sensor data from data storage and management.

Off-system analysis uses communications networks, databases, and health analysis software applications that make up the enterpriselevel capability for CBM+ data collection and analysis.

Communication of condition-related data, other technical information such as configuration data, technical descriptive data, maintenance procedures, and management information is critical to an effective CBM+ implementation.

The sharing of maintenance information and other data among all elements of a CBM+ environment should be possible, regardless of the data storage location. An open architecture, commercial, or DoD-recognized data standard should be used to facilitate the sharing of data outside a single system and to provide for future updates and upgrades.

On-system data should be accessible to other on-system components using hardware data buses or collocated data repositories. Similarly, at- and off-system applications may require connectivity to required data sources using database access or interchange of transactions
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Digital logbooks, message management tools, and database management software should be implemented to ensure needed communications capabilities. As the CBM+ environment becomes more complex and extensive, the expanded use of multiple communications mechanisms will occur.

The CBM+ implementer should plan for the maximum application of data communications standards to facilitate the various data exchange requirements.

Data management is central to implementation, consisting of acquiring data e.g., through sensors or other acquisition techniques, manipulating data into meaningful form e.g., converting analog to digital data, storing data electronically in digital form, transmitting data through electronic means, accessing data as a basis for analysis, and providing data information to decision makers.

In support of CBM+, data are held in two ways: on-system in small amounts to support embedded health assessment and reporting, or off-system in a larger electronic storage media sometimes referred to as a data warehouse. A data warehouse is a computer database that collects, integrates, and stores an organization’s computer data with the aim of maintaining and providing accurate and timely management information and supporting data analysis.

The data may be distributed; that is, located at multiple organizational and locations. One issue relating to the CBM+ database concerns data access and sharing. For example, if the CBM+ database comprises the single physical repository for condition, performance, trending history, and other data categories, then each database user including DoD and contract activities will require access to pertinent portions of the database.

Any effective CBM+ database should have well-established procedures for granting access to qualified users, and should apply available data format standards and definitions to ensure viable information exchange and a consistent data product for each using function.

Collection and aggregation of CBM+ data is a common concept and a good model for the composite or “virtual” database structure. CBM+ implementers may tailor this structure based on organizational or process requirements and the availability of an effective communications capability.

Digital Analytics tools are one of the most essential parts of a CBM+ strategy. For this Guidebook, analytics is defined as the off-system aspect of condition-based health assessment. Depending on the architectural approach used for CBM+ implementation, the analytic capability will need to acquire data from all sources within the architecture using different techniques, such as data mining.

The primary function of the analytic element is to determine the current health state of equipment and project this assessment into the future, taking into account estimates of future usage profiles. Root-cause analysis and tailored analytic algorithms may support this function.

Effective use of prognostic assessment or “prognostics” can be the ultimate goal of predictive maintenance. A prognostic module must be flexible enough to accept many different sources of information to adequately and accurately predict the remaining useful life.

By predicting the remaining useful life, the prognostic capability assists the operators and managers in actively managing their maintenance resources and determining appropriate maintenance actions.

Decision Support is critical to completing CBM+ capability includes the ability to make maintenance and related support decisions based upon the available condition data.

This involves using decision-support tools to assess equipment operating reliability and availability, identify needed changes in planned maintenance requirements and equipment modifications, and track equipment operating performance for individual components, equipment or groupings of equipment.

The objective of Decision Support Tools is to predict problems or failures in time to take remedial action. Decision support includes analytic and decision-support tools to help managers at all levels identify adverse trends and assist in maintenance planning. It may also include the use of data by other sustainment providers in such areas as supply, transportation, or engineering to ensure required support is available where and when it is needed by the operating forces.

The decision-support capability acquires data from the diagnostic and prognostics analytic elements. The primary function of decision support is to recommend maintenance or engineering actions and alternatives and to understand the implications of each recommended action.

Recommendations include establishing maintenance action schedules, modifying the operational configuration of equipment to accomplish mission objectives, or modifying mission profiles to allow mission completion. Decision logic needs to take into account such factors as operational history including usage and maintenance, current and future mission profiles, high-level unit objectives, and resource constraints.

An accurate forecast of an asset’s future use needs to match the other systems planning horizon to be effective. Output from the decision-support capability should be in the form of automated notices,
computer-to-computer transactions, alerts and alarms, or other advisory generations, including health and prognostic assessments.

Human Interfaces layer may access data from any of the other layers within the architecture, such as the decision-support component. Typically, status or recommendations for health assessments, prognostic assessments, or decision recommendations and alerts would be produced and displayed to human users by the decision tools, with the ability to drill down when anomalies are reported or additional information is required.

In many cases, the human interface capability will have multiple layers of access to data across the CBM+ environment, depending on the information needs of the user. This capability may also be implemented as an integrated multiple-user interface that accounts for the information needs of users other than maintainers. The goal of the human interface is to provide operators with actionable information regarding maintenance or operations that suggest or support management or technical decisions.

CBM architecture is the fundamental organization of a system or process embodied in its components, their relationships to each other and to the environment, and the principles guiding its design and evolution.

The framework is intended to ensure design descriptions and interfaces can be compared and related throughout the product or process life cycle across organizational and functional, and joint command boundaries.

At the operational or tactical level, equipment heath assessments help operational commanders gauge the operating capabilities of weapons and equipment under their control. It also assists in maintenance decision making regarding appropriate repair actions and future equipment availability.

1. What is the impact on Maintenance Down Time (MDT)?

To adequately assess the impact of MDT, ensure the MDT of the existing system is defined, as well as the primary MDT drivers (e.g., Mean Time To Repair (MTTR), logistics downtime, etc.). The primary drivers should be key MOEs and analyzed in the sensitivity analysis.

2. How will this CBM+ system/sub‐system affect operator usability?

Identify known impacts to the CBM+ capability, and its parent system, to ensure that the appropriate qualitative as well as quantitative MOEs are included. These should include defined impacts to the system’s operation and maintenance, policy, changes to tactics, techniques and procedures and personnel.

3. How will platform health monitoring affect system performance?

In cases where the primary purpose of the CBM+ BCA is to determine the effect of a health monitoring system, ensure that the system and mission performance MOEs, metrics and investment costs are adequately defined. To the extent possible utilized available historical data/information (e.g., Operational Availability, Mean Down Time, Material Availability, etc.). Select the factors that can be defined, measured, and evaluated within your CBM+ BCA framework to ensure conclusions and recommendations are based on a fair comparison and sensitivity analysis.

4. Does the system provide any increased prognostic/diagnostic capability?

Identify MOEs and metrics (related to failure prediction, RUL estimates, spare part management, warehouse management, etc.) that can be assessed in terms of timeliness, accuracy and relevance of prognostic and diagnostic analytical tools. Also, consider any risks associated with source data, data transfer, and systems processing data, as well as with the analytical tools themselves.

5. What affect does the CBM+ capability have available combat power, system readiness and availability?

The CBM+ BCA should clearly define combat power, operational availability, and material availability for the weapon system which the CBM+ capability is being proposed and also address any unknowns or areas that could not be addressed in quantitative terms. Assumptions should include a defined set of mission reliability MOEs and explain how the unknown areas will be treated in the analysis. The CBM+ BCA conclusions and recommendations should address the quantitative and qualitative costs and benefits as well as risks associated with expected unknown areas which have not been quantified.

6. What maintenance and acquisition processes will be affected and how will they be impacted in terms of data collection, transmission, and manpower costs associated with analysis and decision making?

Identify and define functions, tasks, and related activities for maintenance, acquisition, and logistics processes (e.g., Total Life Cycle Systems Management, PBL, Focused Logistics, Joint Capabilities Integration, and
Development System, Functional Needs Analysis, Functional Areas Analysis, etc.) that is affected by or provides information about the proposed CBM+ capability.

7. How will your overall supply chain be impacted by the CBM+ Initiative?

Identify the supply system process(es) that may be affected and specific MOEs/metrics that can be used for the analysis. Utilize existing logistics and historical data/information (e.g., failure data from VAMOSC) is utilized to define baseline MOEs and related costs.

8. Will CBM+ change the way you buy and provision parts?

Identify the purchasing processes that may be affected and specific MOEs/metrics that can be used for the analysis. Utilize existing RCM and historical data/information (e.g., failure data from VAMOSC) to define baseline MOEs and related costs.

9. Can any service, DoD, Defense Logistics Agency (DLA), other infrastructure be reduced as a result of the proposed CBM+ initiative?

Identify processes, functions and staffing related to the existing and proposed CBM+ capability and utilize any RCM, maintenance or logistics analyses that maybe available as a source to define an existing system baseline. Define specific MOEs (e.g., maintenance tasks, warehousing functions, inventory management, etc.) that can be reasonably analyzed.

10. How will the various COAs or alternatives be executed i.e., acquisition strategy and what is the associated cost/risk of each course of action?

Ensure that the ability to execute and implement alternatives have been addressed in the risk assessment and sensitivity analysis. Identify and define implementation related factors in the assumptions.
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Top 10 Depot Review Determine Lessons Learned Identify Action Status to Improve Maintenance Strategy

7/1/2020

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​Surface Team One compiles lessons learned that the individual RMCs recommend and reviews the implementation and status of actions to address those lessons learned.

Performance to Plan (P2P) is a data-centric, analytical approach the Navy uses for a variety of improvement initiatives, including ship maintenance, to clearly characterize availability performance goals and develop solutions to improve availability duration outcomes.

Fleet maintenance is a critical business function with an imperative to develop innovative solutions so process efficiency is improved without compromising safety and quality.

This case study shows, in order to improve a highly complex fleet maintenance system, it is necessary to develop a comprehensive and valid model of the operational system, which represents not just what is goal targets to happen, but what normally happens.

This model provides the backdrop against which to change or improve the system. A performance report, the Blocker Report, specific to fleet maintenance and related to the model was developed gathering data on anything that ‘blocks’ task or check performance.

A Blocker Resolution Process was designed to resolve blockers and improve the current check system to be rolled out across all fleet hangars of the enterprise.

Approved maintenance schedule puts out the mandatory maintenance programme, and is broken down into checks at various intervals, designated as either line checks, overnight checks and the heaviest checks to empower crews to conduct both routine and non-routine maintenance of the aircraft.

This maintenance includes scheduling the repair of known problems, replacing items after a certain flight time, number of cycles or calendar time, repairing defects discovered from reports logged by pilots and crews or items deferred from previous maintenance and performing scheduled repairs or inspections.

Once maintenance and inspection are scheduled for a fleet component, the plans are translated into, first, a check ‘work pack’ and then into a set of ‘task cards’ giving the instructions for the maintenance personnel to carry out the different tasks on the aircraft.

A major check may have thousands of task cards. Each task card will include a description of the task and contain information pertaining to the type of fleet component. Accomplishment of the intent of the task card initially comes from within the aircraft manufacturer's maintenance manuals used while performing maintenance on any part of the fleet. The task card is a tool that when properly executed provides ‘proof’ of work accomplishment and it exacts accountability from inspectors signing off the card.

Overall, the improvement initiative has been successful leadership was happy with the results. The mix of the different levels of intervention was an important aspect of designing the improvement system.

The improvements taking place at the hangar level helped to show staff that management were committed and serious about the initiative and willing to invest in them and their working conditions.

Once this commitment had been demonstrated, crews responded well when given responsibility to take charge of designing the improvement initiative, of investigating and resolving blockers, of improving the check and meeting customer requirements showing the initiative to meet the challenge.

Data the crews had not seen before were put on the high visibility notice boards in relation to overall check performance, combining some of the performance/quality indicators. The crews involved in, not just identifying problems and possible areas for improvement but became empowered and given a budget to resolve them.

The crew’s work was recognised and supported in the organisation and they were given adequate time to carry out the improvement work. In the beginning, some of crew did not have training for the automatic logistics system. At the end of the first trial they were ‘firing off’ messages to different departments requesting status updates on the resolution of certain blockers.

The work on mapping and modelling the current check process and identifying blockers to task performance based on taking a systems perspective on the location, effect and impact of those blockers led to new levels of work performed on checks.

Time given to the Improvement Team allowed for participants to ask questions of each other and about each other's work. At a cross-departmental level this was not happening. There was an underlying, inadequate assumption that each area knew what the other did and how they all fit together in the organisation and worked together to fulfil the overall goals of the organisation.

New initiative has lead to more insightful diagnosing, planning and taking action. In an initiative of this scale where so much time and energy is invested, along with the internal reviews and milestones, the following questions require ongoing evaluations.

Unplanned Work

One potential source of delays is unplanned work, which consists of both growth work and new work. The Navy defines growth work as additional work that is identified or authorized after contract award that is related to a work item included in the original contract. We previously found that growth work contributed to cost and schedule increases, and it remains a contributing factor. As an example, one official stated that they cannot fully inspect ballast tanks and accurately write work specifications for their repair until the ship is at the repair yard and the availability has begun. Negotiating change orders for unplanned work under MAC-MO is more difficult and time consuming than under the prior MSMO strategy because the Navy can no longer direct the contractor to continue to work without agreeing on the cost.

New Work

Navy defines new work as any additional work that is identified or authorized after contract award that is not related to a work item included in the original contract. Maintenance team officials stated that new work can originate when an item that needs repair breaks or the maintenance team first discovers it after the Navy awards the contract. The Navy can also add new work to an availability whenever it sees fit.

.Growth Work

Availability had 60 instances of growth work that the Navy considered unidentifiable prior to the start of the availability, including welding for the fuel tanks and repair to the bulkheads. Officials stated that the Navy used unilateral modifications to direct the contractor to execute growth work items and avoid further schedule.

Change Orders

Navy officials stated that negotiating change orders for unplanned work under MAC-MO is more difficult and time consuming than under the prior MSMO strategy because the Navy can no longer direct the contractor to continue to work without agreeing on the cost. In one of our case study availabilities.

Contract Provisions

The Navy recognizes the negative schedule outcomes it currently faces with MAC-MO strategy implementation and has worked to mitigate them. It has implemented new contracting provisions and is moving key availability milestones to earlier in the process in an effort to better plan availabilities and facilitate their on-time completion.

LOE to Completion

LOE to Completion allows the Navy to obligate funding for labor-hours and material costs for estimated growth work at the time of award, rather than having to obtain appropriate funds after repair work begins. The Navy can then use those labor-hours and materials for individual growth work items over the course of the availability. While noting the potentially positive effects of shifting award date to 120 days before the availability begins, Navy officials also raised some challenges. They said that locking ship repair requirements almost a full year before an availability actually begins means that the Navy could finalize a ship’s upcoming availability work specifications before a ship even begins its next deployment.

During this deployment, equipment breakages or other deficiencies not anticipated and subsequently not included in the work package could arise on the ship, all of which would likely become growth work during the availability included in the work package could arise on the ship, all of which would likely become growth work during the availability.

Specification Writing

According to third-party planning contractor representatives, they monitor contract changes involving growth work, assess whether that growth is due to planning deficiencies or other causes, and then identify lessons learned, which they use to improve their specification writing process.

For example, contractor representatives stated that they used lessons learned during Destroyer availability to create a template for a section of the forecastle deck plate. This template could be used on future availabilities for ships of the same destroyer class, providing potential cost savings to future availabilities.

Upward Obligation Approval

In 2019, legislation was approved responsive to the Navy concerns relating to the process of approving upward obligations more than $4 million in its MAC-MO availabilities. In the Fiscal Year 2020 Consolidated Appropriations Act,

Congress established a pilot program that allows the Navy to use the Other Procurement, Navy (OPN) account to fund Pacific fleet surface ship repair availabilities for 2020.

Our review of Navy budget documentation shows that the Navy plans to execute 16 pilot availabilities using fiscal year 2020 OPN funds, and it has requested funding for another 26 pilot availabilities in fiscal year 2021. Unlike the Operations and Maintenance, Navy account, which the Navy typically uses to fund ship repair availabilities in 1-year increments, the OPN account provides the Navy with funding that will not expire for 3 years.

Consequently, for availabilities the Navy funds through the pilot program, any growth work that necessitates an availability stretching into a second or even third year will avoid upward obligations and the related approval processes, provided sufficient funding remains in the OPN appropriation to cover the work.

Bundling Contracts

The Navy has recently begun implementing two new contractual approaches—horizontal and vertical contract bundling—within its MACMO strategy, but has not yet had sufficient time to collect or assess results.

These approaches are intended to increase contractors’ visibility into and confidence regarding future ship repair workloads. Navy leadership officials stated that by awarding multiple availabilities, industry receives a body of work that creates confidence in hiring and retaining a skilled workforce and investment in infrastructure.

These approaches provide for contractors to propose on multiple ship repair availabilities that the Navy has bundled within a single request for proposal. Horizontal bundling helps them decide where to direct ship repair and maintenance work, especially as a means to not surpass capacity at a given port.

Contractor anticipate positive effects from horizontal bundling to include being awarded two availabilities from one proposal process and guarantees of work for a longer period than one availability. Vertical Contract Bundling approach has the potential to allow contractors to increase their workload through only one proposal process.

Leveling Port Workloads

Through its P2P initiative, the Navy intends to use historical timelines from recent availabilities to more accurately plan and forecast future availability time frames. This effort is using computer modeling to avoid either underutilizing or exceeding the available port loading capacity of the industrial base in any given timeframe. On average, NAVSEA leadership stated that they intend to lengthen planned availability timeframes by 56 days to more accurately reflect completion times. The officials assessed that this strategy will help ship repair contractors better manage their workforce planning.. If contractors have increased visibility in port loading, they will be more likely to hire an increased number of permanent staff in key ship repair trades and allow for increased workload capacity at a given port, so workers will become more skilled over time and therefore would require less on-the-job training.

1. Assess organisational readiness to change and identify key areas to be addressed with staff workshop

2. Execute initial communication sessions with all staff explaining rationale for and objectives of change.

3. Establish a hangar improvement team to run with the change process and training.

4. Engagement with an iteratively developed meeting schedule to facilitate improvement and resolve blockers.

5. Communicating the status of blocker reports to staff through the use of high visibility notice boards in the hangar and designing the new ‘to be’ process.

6. Assess the needs of the hangar from a staff perspective and create improvement plan based on assessment.

7. Establish relationships with people from other departments involved in the check process e.g. planning and commercial, engineering

8. Explore relationships between the new blocker report and existing network systems to gather data on different aspects of check performance
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9. Establish a systematic approach to the oversight of key performance indicators KPIs in relation to the overall base maintenance process and check process
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10. Strengthen relationship with the customer, including having daily meetings, post check ‘wash up’ meetings, post check customer surveys and analysis
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Top 10 Case Study Activities Improve Operational Process to Check Current Maintenance System Functions

7/1/2020

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.​Case study developed new performance reporting and management procedure allow leaders to identify and resolving issues relating to performance.

Crew involved in shaping aspects such as organisational architecture, the use and sharing of knowledge, process measurement and redesign and network support.

Crew involved in the checks from the hangar chief working on the different aircraft zones (landing gears, wings, engine, cabin, etc)

These staff were supported on a daily basis by the support planner, the materials coordinator and the commercial officer.

We have staked out territory in the hangar where the checks took place and all the departments involved in the upkeep of the hangar, for example, facilities supplying tools, equipment repair, etc.

This area oversees the running of the checks, including any work carried out in related workshops and the resourcing of the checks from a personnel point of view. The base maintenance department operates within a broader aircraft services structure of planning and commercial, engineering, quality, supply chain, personnel resources and networks.

Systems team manages overall development and implementation of the initiative. The steps in the improvement initiative were developed over time and were based on a review of current best practices in relation to ongoing work changes and time spent understanding and working with other continuous improvement initiatives in the enterprise.

NAVSEA also beefed up the Supervisor of Shipbuilding (SUPSHIP) at the yard and connected service providor with former project superintendents from the public yards who could help assist in the planning process.

The NAVSEA 07 submarine lifecycle management organization is also spending quite a bit of time helping the yard apply a contracting and planning model used on carrier RCOHs where each work item is broken up into the resources and cost needed, and the Navy and contractor agree to those along the way to reach a final contract that is as realistic as possible.

“All they had to do was ask, but we didn’t recognize until they started to do the work that there was a basic fundamental – like I said, blocking and tackling – that they lacked. So some of this was just, we didn’t realize they needed the help. It was never on our side any intention of not providing the help, and as soon as they said they needed the help in this particular area, we opened up everything we had.”

The are commonalities in the challenges yard has faced. The three primary challenges were reconstituting our submarine maintenance capabilities that had been idle for a decade (this work greatly differs from new construction), the need to grow additional and effectively balance engineering and production resources being split between maintenance availabilities that are being planned and executed concurrently, and the greater than anticipated hull-specific new growth work.

“We have addressed these issues and are making good progress on this set of availabilities
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The shipyard has demonstrated considerable learning and continuous improvement since reconstituting the submarine fleet support product line, and is committed to growing and building the workforce needed to support our submarine maintenance capabilities, and will continue to work with the Navy to keep pace with their current and forecasted volume of shipbuilding and maintenance needs.

The Navy’s ultimate vision based on recent lessons learned – would be that the yard always has one submarine in planning and one in execution, but never more than one in each phase, lined up heel to toe.

And the private yard might cease working on the Los Angeles-class SSNs and instead only do Virginia-class work. The Virginia subs are newer and the workforce is more familiar with the design since that’s what they’ve been building at the yard.

“We’re looking for a plan that makes everybody as successful as we can, so that’s certainly something we’re thinking about.”

The Navy and industry team used the time when there was not enough room in the yard to do inspections and get a good idea of the ship’s condition and the scope of work that will have to be done during the upcoming overhaul.

“We’ve at least learned the hard lessons and we’ve needed the time to get in and inspect the material condition of the boat, and we have taken lessons learned from the other overhauls.

So the work package we have coming in pretty complete, and we’re going to have some things that will allow us to get in and look at some of the things you couldn’t look at waterborne, some of the ballast tanks and things, but we’ve got a pretty detailed history on Los Angeles-class submarines, so we have a pretty good idea with a high degree of confidence what work is out there.”

A key lesson learned is that the work package should be pretty well defined before a contract is signed – something that’s pretty fundamental to ship repair, but hadn’t been executed well as SSN availabilities were delayed and moved around over and over.

Before, we said, let’s get it in there, let’s get started, and as we get growth we’ll manage it as we go. That’s always a strategy that doesn’t work well, in my book. You’re always going to have some growth work, but the better you can define the work that you have to do up front, the better you’re going to be, for a couple reasons.

One, you know what the cost and schedule are likely to be, you’re not going to be surprised. Two, if you really have a better idea of what the scope is looking like, then you know whether you’ve got the capacity to match that scope of work. Capacity applies to both the maintenance workforce to do the repairs and also the engineering workforce to handle the SUBSAFE requirements.

The bulk of the Navy’s problems in recent years was that its four public shipyards, tasked with maintaining nuclear-powered submarines and aircraft carriers, did not have the capacity to keep up with demand
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The workforce across the yards dropped after sequestration and budget controls wracked the Navy maintenance budget, with many of the workers left at the yards having less experience than those who retired and weren’t replaced in recent years.

Beyond the sheer number of people doing the work, “basically, the two big yards, the carrier yards, haven’t been doing SSN maintenance. … They’ve been just focused on SSBN refueling.
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“And as we build more Virginia-class submarines, we’ll eventually start bringing more submarine work back in. And the fact that you don’t have SSBN refueling overhauls to work on means that, in terms of the priority at the naval shipyards, we shouldn’t see the SSNs taking a backseat.

Remember, a lot of the reason they took the backseat is because we just didn’t have the capacity at the naval shipyards to begin with. Now we have the workforce capacity to do all the work that’s assigned to us, and that’s going to reflect in on-time delivery across the board, whether it’s carrier work or SSNs.”

“The SSNs are going to be the ones that gain the most benefit of adding capacity at the shipyards.” SSN maintenance is wrapping up on time more and more as capacity at the public yards grows.

We are confident NAVSEA was in a good position on SSN maintenance because a whole set of improvements had been made in tandem in recent years: not only was the workforce now up to its goal, but an effort to create better business practices is underway and the first projects in a 20-year Shipyard Infrastructure Optimization Plan (SIOP) program are already hitting the waterfront.

Navy has kicked off it’s Naval Sustainment System-Shipyards initiative to look at the business practices that support ship maintenance, modeled after a very successful NSS-Aviation effort that helped Naval Air Forces reach 80-percent readiness rates and higher in the fighter jet fleet.

And though the SIOP is a long-term plan that will require about $21 billion in funding over 20 years, an early project to replace a Los Angeles-class dry dock with a new one for modern Virginia-class subs – as well as a production facility on the waterfront that will move all shops and engineering spaces closer to the dry dock where repairs take place – will create a “dramatic improvement” in productivity there
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“We’re trying to get out of the mentality of setting priorities within naval shipyards, because the experience has been, if you make something priority three or four, all that means is it’s going to be late.

We set priorities in a time when we just didn’t have capacity to work on everything. The Navy is changing that approach. On-time delivery of ships and submarines has been mission priority number-one for several years and we’ve grown the capacity at the naval shipyards now, we’ve done a number of things in the shipyards to improve productivity.

We’ve working through this Naval Sustainment Shipyard to bring in some help to go look at how we can transform the business processes at the naval shipyards. All the work we’ve done on SIOP means you can have the right numbers of workers, but if you really want to take that next step to being more productive and delivering everything on time, you’ve got to make the needed investments in the infrastructure to support that.

You can’t look at the Jobs individually, you have to go look at them in totality. You have to do all that work.op
Top 10 Condition Based Maintenance Questions Empowers Systems Engineers to Make Smart Decisions Increase System Availability and Readiness

1. What is CBM+?

CBM+ is the application/integration of appropriate processes ,technologies,and knowledge-based capabilities to improve reliability and maintenance effectiveness of DoD systems and components
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2. When is CBM+Used?

CBM+ensures timely,cost effective maintenance implementations in new acquisition programs across sustainment life cycle for fielded DoD weaponsystems., isused to support maintenance decision-making processes during system acquisition, sustainment, and operations
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3. Why do CBM+?

CBM+ isused in concert with other total lifecycle management tools to enhance materiel readiness and, improves maintenance decisions and integration of all aspects of life-cycle management processes.

4. Who is involved in CBM+?

CBM+ is focused on maintainer effectiveness and weapon system reliability to be implemented by Services, policymakers,p rogram managers ,system engineers, logisticians ,and maintenance managers.

5. How does CBM+ affect maintenance?

CBM+provides strategy and guidance for implementation of enabling technologies and procedures to improve business processes and maintenance performance to enable greater productivity, lower costs, better availability ,and enhanced reliability of materiel resources.

6. What are CBM Scorecard Factors? ,

CBM+ is condition based maintenance based on evidence of need provided by Reliability Centered Maintenance analysis and other enabling processes and technologies.

7. How do CBM processes give feedback?

CBM+ encourages systems engineering approach to collect data and enable analysis to allow for continuous development of maintenance processes and procedures to improve capabilities, practices and technologies

8. How does CMB inform policy?

Development of CBM+ across the Services involve collaborative effort activities include policy revision, Service plan review,project coordination, and sharing of information..teams established for short-term projects/studies,include current efforts in Reliability Centered Maintenance and business case analysis.

9. What are CBM+Goals?

The ultimate goal of CBM+ is to increase combat power, expressed in terms of operational and materiel availability and readiness ,throughout weapon systems lifecycle.

10. How are CBM+ efforts sustained?
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CBM supports long term DoD goals of improving maintenance technologies and providing timely joint logistics support to meet warfighter needs by optimizing schedules of maintenance depot availabilties.
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Top 50 Questions Execute Design Approach SupportĀ  Condition Based Maintenance Business Case Assessment

7/1/2020

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Condition Based Maintenance CBM is application and integration of appropriate processes, technologies, and knowledge-based capabilities to achieve the target availability, reliability, and operation and support costs of DoD systems and components across their life cycle.

At its core, CBM+ is maintenance performed based on evidence of need, integrating RCM analysis with those enabling processes, technologies, and capabilities that enhance the readiness and maintenance effectiveness of DoD systems and components.

CBM+ uses a systems engineering approach to collect data, enable analysis, and support the decision-making processes for system acquisition, modernization, sustainment, and operations.

CBM integrates all functional aspects of life cycle management processes for materiel requirements, such as systems engineering, development, acquisition, distribution, supply chain management, sustainment, and modernization.

Implement an optimum mix of maintenance technologies e.g., condition monitoring, diagnostics, and prognostics, best practices, RCM-based processes, and enablers (e.g., total asset visibility within the integrated total life cycle framework.

Minimize mean downtime by providing timely condition information, precise failure mode identification, and accurate technical data to expedite repair and support processes.

CBM+ is pursued through the examination, evaluation, and implementation of enabling technologies, tools, and process improvements Used as a principal consideration in the selection of maintenance concepts, technologies, and processes for all new weapon systems, equipment, and materiel programs based on readiness requirements, life cycle cost goals, and reliability centered maintenance (RCM)-based function.

DoD policy requires CBM+ be implemented for maintenance and logistics support of Service weapon systems where cost effective. The scope of CBM+ includes maintenance related processes, procedures, technological capabilities, information systems, and other logistics concepts that apply to both legacy systems and new acquisition programs.

Require Program Managers PM design, develop, demonstrate, deploy, and sustain equipment in accordance with CBM+ policy and guidance to achieve required materiel readiness at best value.

PM Architecture Framework is fundamental organization of a system or process embodied in its components, their relationships to each other and to the environment, and the principles guiding its design and evolution.
PM Architectural Framework defines a common approach for architecture description development, presentation, and integration for both DoD warfighting operations and for business operations and processes.
PM Framework is intended to ensure design descriptions and interfaces can be compared and related throughout the product or process life cycle across organizational and functional boundaries
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CBM+ initiatives reflect universally popular objectives, but can lose support when faced with competing operational priorities. Continued research into emerging technologies and business practices provides programs with the latest information for selecting optimum maintenance solutions.

Sharing the information between programs and Services will stimulate forward progress in CBM+ development and implementation. Regular progress reviews will ensure that new personnel and programs will be included into the CBM+ environment so CBM+ strategic plans stay on track.

Here we provide an overall Condition-based Maintenance CBM Business Case Approach BCA process, common set of cost elements, measures of effectiveness, a notional BCA framework, and factors to consider when assessing and subsequently conducting a CBM BCA to shape an understanding of the areas that CBM capabilities might benefit a program/system, in order to support a go/no‐go decision and subsequent investment decisions with justifiable information.

CBM is the application and integration of appropriate processes, technologies, and knowledge-based capabilities to improve the reliability and maintenance effectiveness of DoD systems and components. At its core, CBM is maintenance performed based on evidence of need provided by Reliability Centered Maintenance RCM analysis and other enabling processes and technologies.

CBM uses a systems engineering approach to collect data, enable analysis, and support the decision‐making processes for system acquisition, operations, and sustainment. In evaluating potential CBM capabilities, whether they are technologies, maintenance processes, or information/data knowledge applications, a BCA needs to address these areas in a comprehensive and consistent manner, particularly when an incremental acquisition or fielding strategy is being considered.

Although the basic concept and purpose of BCAs are generally understood throughout DoD, many interpretations exist regarding assessment of CBM capabilities to ensure appropriate and accurate considerations are given to CBM capabilities, costs, and benefits.

So, what is a BCA? A BCA is a decision support approach that identifies alternatives and presents convincing business, economic, risk, and technical arguments for selection and implementation to achieve stated organizational objectives/imperatives.

A BCA does not replace the judgment of a decision maker, but rather provides an analytic and uniform foundation upon which sound investment decisions can be made. The subject of a BCA may include any significant investment decision that leadership is contemplating.

For example, a BCA may be used to substantiate the case to invest in a new weapons system, but not at the same level as a Capabilities Based Assessment; transform business operations; develop a web‐based training curriculum; or retire an asset.

In general, BCAs are designed to answer the following question: What are the likely operational/business consequences if we execute this investment decision or this action? The possibility exists that any projected savings or cost reductions identified in the BCA could be viewed as an asset available for reallocation in the budgeting process.

In evaluating the potential application of a CBM capability, it is important to understand the desired end state from a CBM metrics perspective and key assumptions that may impact the system or CBM capability.

Must define the need for a BCA, understand and define the problem, and define the desired end state. This approach focuses on As‐Is system trends, evaluating Measures of Effectiveness MOE and their cost drivers, key CBM metrics, determining if CBM is a viable solution and if so, what CBM capabilities are applicable, and then defining feasible solutions.

CBM Guidebook outlines measureable objectives for maintenance in a CBM+ environment and five relevant CBM+ operating metrics: material availability, material reliability, ownership costs, and mean down time; and logistics footprint.

When defining metrics for your BCA, select a set of metrics, considering Systems Operational Effectiveness (SOEs) metrics, that fairly represent the potential costs and MOEs that you expect to be able to capture, or is available.

Other metrics may also be appropriate when considering predictive capabilities such as advanced diagnostics or prognostics that enable accurate and timely prediction of Remaining Useful Life (RUL).

Potential MOEs for Prognostics Health Management (PHM) systems could include advanced warning of failures; increased availability through an extension of maintenance cycles and/or timely repair actions; lower life‐cycle costs of equipment from reductions in inspection costs, downtime, inventory, and no‐fault founds; or improved system qualification, design, and logistical support of fielded and future systems

Key assumptions constitute a critical element of the boundaries of the CBM+ BCA. Not everything included in the analysis is known. CBM+ BCAs, like any forecasting analysis, address future periods and conditions and as much as we utilize data to predict future conditions, any future datum or condition is subject to change from forces that could not be predicted when the analysis was conducted.

Assumptions allow us to logically portray reasonable expectations of future circumstances. Tailoring the BCA to fit your case will require adjusting functional areas, weighting factors interfacing systems, sustainment/incremental capability improvements and service life considerations.

Areas to consider in defining assumptions should include: areas of integration with other systems; operating tempo; projected useful service life/remaining useful life; expected funding levels; basis for cost estimates; MOEs and related metrics (throughout the life cycle); technology forecast; CBM+ related logistics processes; and areas not addressed in the BCA.

Considering these areas will help to ensure the CBM+ BCA is well scoped and defined. It is also important to understand how incremental CBM+ capability improvements may impact ROI and ensure adequate assumptions are defined regarding the impact of incremental improvements on ROI. These incremental improvements, as well as improvements to other systems, e.g., Global Combat Support System (GCSS), and maintenance processes, will make contributions to the CBM+ ROI as they come online.

Assumptions regarding timing and capability impact on the overall CBM+ ROI should be clearly stated. The ROI contribution of other systems may be significantly greater than one depending on application, access, and use of CBM+ data.

Define the As‐Is CBM+ configuration in terms of the existing CBM+ capability itself, the platform/weapons system it supports or is integrated into, and the current system’s CBM+ performance measures/metrics.

To the maximum extent possible, describe the As‐Is configuration in terms of the CBM+ functionality (fault detection, isolation, prediction, reporting, assessment, analysis, decision‐support execution and recovery, both on and off‐board); CBM+ business needs; and operating metrics. Where incremental improvements have been
implemented, provide any prior BCA, Economic Analysis (EA), or analytical data related to CBM+ functionality, CBM+ business needs, and metrics.

Measures of Effectiveness. MOEs should clearly answer the question, “What does this investment provide the customer/ organization?” It is important to understand how benefits will be measured to ensure that appropriate data and information is collected and folded into reasonable measures that support CBM+ metrics and can be tied to time‐phased changes in the system being evaluated.

MOEs can be defined as an advantage, profit, or gain attained. They are commonly thought of as an investment return and should describe what the investment enables an agency to accomplish and how the mission is enhanced. Focusing on improved business outcomes rather than the technology is one of the best ways to ensure the expenditure of any resource furthers the agency’s mission.

CBM+ BCA risk analysis should include any areas or processes that may significantly affect your program and provide an assessment of their likelihood and potential impact. For each alternative, identify risks that could adversely affect it, and assess the possibility that the initiative can be successful; specify a risk‐reduction strategy for each risk; and identify key parameters and conditions that impact the investment decision. Present potential contingent actions that could mitigate the uncertainty. Identify how such uncertainties impact the analysis and investment decision.

Prepare Sensitivity analysis by Comparing alternatives and rank according to net present value, risk, ROI, or primary measures/factors such as risks and areas of uncertainty, technical maturity, level of integration risk, and funding.

A sensitivity analysis can answer “What if the assumptions change?” It involves evaluating the variability of an alternative’s cost, benefit, and risk with respect to a change in specific factors. The objective is to determine which factors have the greatest impact (positive or negative) on the evaluation of the alternative.

Here we present some general questions and guidance that may relate to your CBM+ initiative. Answers to these questions are provided as information and an approach to support CBM implementation. As you plan your CBM BCA, the questions may assist in framing your general approach and strategy and ensure your CBM+ BCA is adequately defined and scoped to address key CBM business areas.

1. CBM+ implementation enhance maintenance efficiency and effectiveness

2. Establish integrated, predictive maintenance approaches

3. Minimize unscheduled repairs

4. Eliminate unnecessary maintenance

5. Employ the most cost-effective system condition management processes.

6. Implement data collection and analysis requirements

7. Measure equipment sustainment performance characteristics

8. Collect measures of effectiveness throughout life cycle sustainment.

9. Enhance materiel availability and life cycle system readiness

10. Reduce equipment failures during mission periods

11. Identify best time to perform required maintenance, to increase operational assets.

12. Leverage open architectures and open standards to facilitate the broad application of CBM+ enablers

13. Improve materiel reliability through the disciplined analysis of failure data

14. Create capacity to modify designs and operating practices

15. Ensure equipment meets target performance standards within operational context.

16. Optimize life cycle logistics processes

17. Reduce operation and support costs by eliminating unnecessary maintenance activities

18. Accurately position resources for an effective logistics footprint in support of warfighting requirements.

19. Incorporate CBM+ based on Failure modes, effects and other R&M analysis.

20. Create capacity for RCM analysis in accordance with established standards

21. Continuous administrative process improvement initiatives

22. Serialized item management applications

23. Predictive reliability engineering methods

24. Technology assessments and business case analyses

25. Analysis formulated in a comprehensive reliability and maintainability (R&M) engineering program

26. Document in the program Systems Engineering Plan and Life Cycle Sustainment Plan

27. Assess standards during acquisition process reviews and evaluations

28. Include in the development of mandatory sustainment key performance parameter (KPP) and supporting key system attributes (KSAs)

29. Develop sustainment KPP or sponsor defined sustainment metrics

30. Adequately resource for implementation, to include product development, procurement, and sustainment.

31. Integrate in current weapon systems, equipment, and materiel sustainment programs where it is technically feasible

32. Incorporate as part of maintenance plans and into contracts for systems and programs

33. Review performance-based life cycle product support sustainment arrangements

34. Assess availability metrics of the sustainment KPP: materiel availability and operational availability

35. Consider KSA reliability, operation and support cost

36. Monitor and review the implementation of policies to ensure CBM+

37. Demonstrate effectiveness across maintenance, acquisition, engineering, logistics, and industry groups

38. Ensure CBM+ technologies, processes, and enablers are integrated with program acquisition and technical planning.

39. Consider CBM+ during program support reviews and other oversight reviews.

40..Support identified critical technologies through studies and analyses

41. Review plans and projects to eliminate unpromising or duplicative programs.

42. Guide science and technology programs, advanced component development, and prototypes programs to achieve CBM+ capabilities

43. Incorporate the requirement for CBM+ in appropriate policy and guidance.

44. Develop and establish enterprise level requirements for implementing CBM+

45. Provide resources for CBM+ requirements developed at enterprise and weapon systems levels.

46. Review and monitor programs for CBM+ implementation and outcomes.

47. Use CBM+ solutions to maintain the readiness of new and fielded equipment

48. Integrate common CBM+ technologies, processes, and procedures for similar platforms and components.

49. Require implementation of RCM and other appropriate reliability and maintainability analyses.
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50. Ensure logistics information systems support CBM+ objectives.
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