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Top 50 Market Agent Design Groups Establish Product Configuration Choice Available to Customers

7/22/2018

Configuration Item Number Selection Criteria Process Requires Systems Engineering Trade-Offs. Selected items of system characterised by acquisition activity has configuration administrative concern, are designated as Configuration Items .

Configuration Items vary widely in complexity, size and type, from an aircraft, ship, tank, or electronic system to a test meter or a round of ammunition. Regardless of form, size or complexity, the configuration of an item is documented and controlled. Configuration Item selection separates system components into identifiable subsets for the purpose of further development.

For each item, associated configuration documentation ranges from a performance specification to a detailed drawing to a commercial item description. Configuration status update changes will be controlled, accounted, maintained and performance verified.

To define and control the performance of a system or Configuration Item does not mean all components must be designated as Configuration Items, nor does it mean that the performance requirements for the non-Configuration Item components must be under DoD control.

The requirements to be met by a lower-level component not designated as a Configuration Item are established and controlled via the Contractors design and engineering release process. DoD control occurs only when changes to the lower level components impact the baselined performance specification for the Configuration Item

Initial Configuration Item selection should reflect an optimum administrative level during early acquisition. Initially, for Engineering and Manufacturing Development, Configuration Items usually are the deliverable, and separately installable units of the system and other items requiring significant attention at Buyer/Seller interfaces.

During Production, Fielding/Deployment and Operational Support, individual items required for logistics support and designated for separate procurement are also Configuration Items The view of what is designated a Configuration Item may depend on where in the contracting network the view originates. When DoD acquires a system using detail, rather than performance specifications, the DoD view may eventually include all Configuration Items.

Typically the top tier of Configuration Items directly relate to the line items of a contract and the work breakdown structure. The determination of the need to designate them as Configuration Items is normally simple and straight forward. However, there are many cases in which other lower-level items should also be selected based on requirements of the programme.

Although the initial Configuration Item selection generally occurs early in the acquisition process, its consequences are lasting and affect many aspects of program team activities, systems engineering, acquisition logistics, and configuration management. Configuration Item selection establishes the level of DoD configuration control throughout the system life cycle.

Selecting Configuration Items separates a system into individually identified components for the purpose of development and support. DoD Configuration Item designation should reflect the optimum level for both acquisition and support. During acquisition, this is the level at which a contracting activity specifies, contracts for, and accepts individual components of a system, and at which the logistics activities organise, assign responsibility and report modification and maintenance actions during support.

During the concept exploration and the programme definition and risk reduction phases, the system architecture is established, the program work breakdown structure is developed, and major Configuration Items are selected. These activities provide the basis for the Supportability Plan for the program, which, in turn, dictates the selection of lower-level Configuration Items. Development, acquisition, retrofit, and interfaces are all affected by breakout of the key system elements into Configuration Items during early stages of development efforts.

Many engineering requirements or considerations can influence the selection of Configuration Items. Throughout development and support, the allocation of engineering effort and organisation are rooted in the selection of Configuration Items. Developing contractors should participate in the selection process and provide recommendations based upon engineering or other technical considerations.

Configuration Items selection criteria are applied to contractor recommendations to decide on the items under review by DoD. Decisions to designate specific candidates as Configuration Items and decisions on the time when they will come under DoD control normally involve an integrated team of acquisition programme administration, systems engineering, and acquisition logistics. In addition, the contractor determines those items in the system that are not DoD Configuration Items, but which will be subject to lower tier lower tier configuration .
　
Typical example for multi-agent package supplier problem is the configuration of telecommunication switches. In this scenario, the final product for the customer—a large-scale telephone switching system—consists of a configurable main switch but also of subcomponents, provided by different suppliers and are themselves configurable.

Many techniques of distributed problem solving have been used e.g., on distributed constraint satisfaction, multi-agent planning or agent-based simulation, but there are not many specifically aiming at developing formulas for solving distributed configuration problems.
　
New challenges arise for the problem solving phase. Often, the configurators in supply networks are organised in sequential manner. So finding a solution to the overall configuration problem requires not only the definition of communication and agent exchange protocols but also advanced reasoning techniques.

Before trying a value assignment in the search process, each local connection first checks if the variable “belongs” to one of the supplier systems. In such a case, it contacts the supplier configurator and asks for a value. If no value can be found, local backtracking is initiated.

After a variable assignment, the system checks if one of the suppliers has to be informed of the value change. If the new value is not accepted by the supplying system, again backtracking has to take place. Client-server style instructions are in general relatively easy to implement and have—at least in the sketched domains—a good correspondence to the real-world problem setting.

But there are limitations due to their sequential and unfocused backtracking behaviour, which can lead to a high number of messages to be exchanged among the configurators. There are requirements and challenges of modeling and solving distributed configuration problems capability for distributed backtracking in constraint-based approaches.

“Twin” distributed problem solving rules for two application scenarios are used. In both cases, the solution architecture is based on having main configurator that coordinates multiple supplier configurators implementing a defined interface and share parts of their configuration model. One technique developed for the multi-agent market telecommunication switch scenario, is based on forward checking and backtracking.

Must create infrastructure to model and solve a variety of problems from the area of Multi-agent Systems and distributed Artificial Intelligence including distributed resource allocation, scheduling or verification maintenance. Modeling and solving distributed configuration problems, in which several agents jointly and in a loosely coupled, non-parallel manner cooperate in the problem solving process.

Decentralised, event-driven distributed simulation is particularly suitable for modeling systems with inherent uncoupled parallelism, such as agent based systems. However the efﬁcient simulation of multi-agent systems presents particular challenges which are not addressed by standard parallel discrete event simulation models and techniques.

Product configuration can be defined as the task of tailoring a product according to the specific needs of a customer. Due to the inherent complexity of this task, for example includes the consideration of complex constraints or the automatic completion of partial configurations.

Artificial Intelligence techniques have been explored for a long time to tackle such configuration problems. Most of the existing approaches adopt a single-site, centralised approach. In modern supply chain settings, however, the components of a customisable product may themselves be configurable, thus requiring a multi-site, distributed approach.

We have identified challenges of modeling and solving such distributed configuration problems and propose an approach based on Distributed Constraint Satisfaction. In particular, we advocate the use of Generative Constraint Satisfaction for knowledge modeling and show in an experimental evaluation that the use of generic constraints is particularly advantageous also in the distributed problem solving phase.

We present market models for a well-defined class of distributed configuration design problems. Given a design problem, the model defines a computational market to allocate basic resources to agents participating in the design. The result of running these “design markets” constitutes the exchange solution to the original problem.

After defining the configuration design framework, the mapping to computational markets is described. For some simple examples, the system can produce good designs relatively quickly. However, a closer look shows that the design markets are not guaranteed to find optimal designs, and we identify and discuss some of the major pitfalls. Despite known shortcomings and limited explorations thus far, the market model offers a useful conceptual viewpoint for assessments of distributed design problems.

Many conﬁguration systems are centralised and do not allow manufacturers to collaborate on networks for offer-generation or sales-conﬁguration activities. But the integration of conﬁgurable products into the supply-chain of a business requires the cooperation of the various manufacturers’ conﬁguration systems to jointly offer valuable solutions to customers.

As a consequence, there is a need for methods that enable independent specialised agents to compute such conﬁgurations. Several approaches to centralised conﬁguration are based on constraint satisfaction problem solving. Most of them extend traditional constraint satisfaction problem approaches in order to comply to the speciﬁc expressions and hard-to-track requirements of conﬁguration and similar integration of tasks.

The distributed generative constraint satisfaction problem framework proposed here builds on a constraint satisfaction problem construct that encompasses the generative aspect of variable creation and extensible domains of problem variables. It also builds on the distributed constraint satisfaction problem framework, supporting conﬁguration tasks where knowledge is distributed over a set of agents.

Notably, the notions of constraint and service providers are usually generalised, adding an additional level of extending inferences to types of variables. An example application of the new framework describes modiﬁcations to the market signals and our evaluation indicates that the distributed constraint satisfaction problem framework works pretty well.
　
1. Designating a system component as a Configuration Items increases visibility and control throughout the development and support phases.

2. For system critical or high technical risk components, added visibility can help in meeting specified requirements and maintaining schedules.

3. For each contract, there should be at least one Configuration Items designated for complex systems

4. Major functional design components are usually designated as Configuration Items.

5. The initial selection is normally limited to the major component level of the work breakdown structure.

6. As system design changes during development and complex items are further subdivided into their components, additional Configuration Items may be identified.

7. Developing contractors should be given maximum latitude to design below the system level.

8. Changing system architecture or the reallocation of functions after a baseline has been established by DoD is best avoided

9. Each Configuration Item should represent a separable entity that implements at least one end use function.

10. The selection of Configuration Items should reflect a high degree of independence among items at the same level.

11. Subordinate components are recommended as Configuration Items during the detail design process, should all be functionally interrelated.

12. The complexity of Configuration Item interfaces in a system should be minimised.

13. Complexity of Configuration Item often results in increased risk and cost.

14. All subassemblies of a Configuration Item should have common mission, installation and deployment requirements.

15. For systems with common components, subsystems, or support equipment, each common item should be separately designated as a Configuration Item at an assembly level common to both systems.

16. A unique component specific to only one of multiple similar systems should be identified as a separate Configuration Item of that system.

17. Factors to consider include the extent of the modification; the criticality of the modified Configuration Item to the mission of the system

18. Extent of ownership, Configuration Item documentation required and available to DoD

19. Would Configuration Item designation enhance the required level of control and verification of these capabilities?

20. Will the Configuration Item require development of a new design or a significant modification to an existing design?

21. Does Configuration Item have a separate interface with item developed under another contract?

22. Does the Configuration Item have a separate interface with an item controlled by another design activity?

23. Will it be necessary to have an accurate record of Configuration Item exact configuration and the status of changes to it during its life cycle?

24. Can or must the Configuration Item be independently tested?

25. Is Configuration Item required for logistics support?

26. Does Configuration Item have the potential to be designated for separate procurement?

27. Have different activities have been identified to provide logistics support different parts of the system?

28. Does Configuration Item have separate mission, training, test, maintenance and support functions, or require separately designated versions for such purposes?

29. Do all subassemblies of the Configuration Item have common mission, installation and deployment requirements, common testing and DoD acceptance?

30. Are performance or design verification demonstration, system integration and testing, activities usually accomplished for each of the selected Configuration Item ?

31. Technical reviews and budget allocations activities usually accomplished for each of Configuration Items selected.

32. The number of Configuration Item selected will determine the number of separate meetings related to the overall activity

33. Number of Configuration Item may lead to delays in completing critical development and support milestones.

34. Existing Configuration Item available from inventory may be modified and designated as a separate and different configuration of that item to save time and money.

35. Factors to be traded off include complexity, the use of new materials, processes, and the insertion of new technology.

36. There are no rules to dictate the optimum number of Configuration Item for a given system, but the fewer items, the better. Selecting too many items increases development and support costs.

37. Each Configuration Item to be developed comes with an associated set of technical reviews, performance or design verification demonstrations, formal unit and integration tests, and documentation requirements.

38. Activities adds an increment of development cost and also adds costs for storage and upkeep of information related to the activities

39. Many Configuration Item interfaces to be defined-- if they are all baselined early to limit contractor freedom to develop design solution, solve problems expeditiously, and implement advantageous changes without contractual consequences.

40. Configuration Item functionality defined at too low a level or including unnecessary design constraints requires formal test, and technical reviews, beyond what is required achieve reasonable assurance of system performance.

41. Problems may arise if performance specifications for the lower-level Configuration Item are baselined too early

42. Increased overall number of requirements in the documentation disproportionate to the unique technical content of the requirements

43. Excessive Configuration Item fragmentation decreases visibility of system performance and increases the overall volume of requirements

44. Configuration Item fragmentation complicates update review, approval, and control process.

45. Consequences of having too few Configuration Items include Increased complexity of each item resulting in decreased insight and ability to assess progress

46. Where the lowest level designated Configuration Item is a complex item implementing unrelated functions, potential for reuse of the item/portions is diminished

47. Re-procurement of Configuration Item and components is complicated with few sources are limited making testing of critical capabilities more difficult.

48. The inability to account for the deployment of a Configuration Item , whose component parts are disbursed to different locations

49. Difficulty in addressing the efficacy of changes and retrofit actions when different Configuration Item quantities or separately deliverable components

50. Increased complexity in accounting for common assemblies Configuration Item and components by the contractor

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Top 10 Basic Reliability "Digital Twin" Simulation Approach Provide Agent Structure Design Mission Space Value

7/9/2018

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Most “Digital Twin” Simulation Experts say the terms component, parameter and assembly indicate configuration design mainly applies to the configuration of physical objects, but the components can also represent other things, e.g. activities.

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

Each solution agent determines the optimal configuration for the product concerned based on its local point of view. Then the configurations are evaluated considering all the points viewed in the previous steps.

Consensus contains one or more agents which are quite similar regarding the constraints imposed by the different experts of domains and the customer. These solutions allow the customer to choose among several product configurations which best fit the imposed requirements.

Simulation constraints differ from requirements in that requirements must be satisfied, while constraints must not be violated. For example, a requirement could be that field-level unit should have an outlet for smoke from fire. Such a requirement could be satisfied by some contraption that fulfills this function.

An example of a constraint would be that the field-level position should not have an outlet higher than an upper boundary. This constraint does not say that there should be a outlet, but that if there is to be one, it should not exceed a certain upper boundary.

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

Multi-Agent Set-based design constructs can replace point based design construction with design discovery; it allows more of the Reliability Simulation effort to proceed concurrently and defers detailed specifications until mission space tradeoffs are more fully understood.

Process involves facilitated negotiation between agents created to help design teams take into account product characteristics across different functions and all stages of product life cycle.

Multi agent process discovers and corrects errors and still make sets wide enough that process was able to move forward and reach a converged solution without major rework. In a point-based design approach the team would need to start the design over.

Hybrid system of design agents and intermediate digital agents exhibits promise as a means of achieving effective conceptual set-based design of blocks by a cross-functional design team.

Negotiation across the network provides effective way to balance interests of the design team members. Converged marketplace can assess the interaction and design value of different parameters

Previous interface allowed only one-on-one negotiation even though many agents had critical interests in some parameters.

Hybrid agent approach can provide means to address potentially limiting design communication and negotiation process in advanced cross-functional team design, even if it is virtually linked across the network.

Mission Reliability Digital Twin Simulation must be constructed to depict the intended utilisation of elements to achieve mission success. Elements of the item intended for redundant or Alternate modes of operation must be modeled in a parallel configuration or similar Lego Block Construct appropriate to the mission phase and mission application.

Rapid diffusion of Digital Twins calls for open source entry level models of subcomponent units.. Once system of system with unit parts serves as Lego Block Construct or baseline unit to be created and built.

Pervious build efforts stopped at the physical unit representation , but Digital Twins call on the source of the physical unit to contribute to status update deposit complete with engineering characteristics of operational reliability functions.

Building Lego Blocks required for Digital Twin movement are quite similar to building blocks required to implement use of blockchain with trusted status updates of connected instances.

To deliver value, connections must span wide broad macro system. Implementation of connections must not be tied to distinct established steps or location, but must be time sensitive to maximise transmission and minimise with respect to sense/response between the edge and core.

Have we encountered Block and Connection concepts elsewhere?

Well, we have. Multi-Agent Systems are present in Lego Block Constructs, with each Agent representing one block component viewed a baseline unit contribution to Digital Twin Model.

The convergence of Digital Twins and blockchain is evident. Enterprises dissociated by modular structures and associated by function in operational sequences presents series of steps subdivided into blocks -- not only things/objects but also multi agent models, unit of work, process, verification decisions, outliers, feedback, metrics etc.

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

Component Sequence Builds make it easy to represent objects, processes, and decision outcomes. Connected blocks may simulation agents networks joined by common Digital Twins. For example, alignment concepts described in previous reports specific to appropriate blocks can lead to useful platforms.

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

Block units and subunits can be configured to create Digital Twin of machine. Condition instances and unit of status update represent blocks constitute Digital Twin model.

Not completely restricted configuration cases are apparent where a skeleton arrangement is given, but the specific arrangement still has to be determined. The other extreme case is where the space of possible arrangements is not limited in any way by the specification of the problem.

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

Some variants of configuration assume the requirements to be functional, in which case some relation between the arrangement of components and the required function must be determined.

In the Lego Block Construct problem, the requirements are not directly related to the components themselves, but to geometric properties of the final assembly. Testing the requirements against a possible solution will involve some aggregation over the properties of the individual components.

As an Example, consider scheduling a meeting. Using a point-based process for scheduling, the scheduler might send out an announcement that a meeting is necessary and propose to schedule it at a time suitable to him/her, e.g., for 10 am on Monday morning.

As the meeting attendees read the announcement, schedule conflicts will likely be revealed, causing back-and-forth communication and causing the meeting time to shift many times until a meeting time is reached that is agreeable to many if not all.

In contrast, using a set-based process for scheduling, the scheduler could announce that a meeting is necessary and send out all his/her available time and times currently booked but that might be rescheduled.

Then, each of the meeting attendees could compare their own availability with that of others and negotiate which meetings are best rescheduled until a meeting time manifests itself out of the attendees’ constraints. The set-based process eliminates unnecessary back-and-forth communication and expedites the meeting time selection.

Operational stability increasingly dominate general officer debate. Tech innovations have changed the way weapons systems operate. Specifically, traditional models of mission costing agencies construct fail to capture crucial processes.

Current controls by command centres have limited influence in global, highly interconnected and tech mediated networked systems. For example, the behaviour of high frequency computational agents on one exchange can have rapid knock-on consequences globally.

New kinds of decentralised self-organising collective action such as disagreements on mission requirements are possible using multi-agent platforms. At the same time centralised institutions find it increasingly difficult to control information and events leading to mission accountability crises.

Intent of the process is to couple the benefits of Multi-Agent Tradespace exploration in conceptual design with the benefits offered by the survivability design principles and survivability metrics.

In particular, multi-agent tradespace for survivability is a value driven process in which the designs under consideration are directly traced to the value proposition, and the measures of-effectiveness reflect the preferences of the decision maker during nominal and disrupted scenario states.

By following a parametric modeling approach, broad exploration of the tradespace is enabled in which the decision-maker gains an understanding of how value proposition maps onto a large number of alternative system concepts.

By emphasising breadth rather than depth, promising areas of the tradespace may be selected with confidence for future assessments, and sensitivities between survivability design variables and disturbance outcomes may be explored.

One implication of value thresholds changing as a function of scenarios is that definition and scale of the utility axis will vary across nominal and disrupted scenario states. A general response to this implication is to elicit applicable multi-attribute utility functions across all potential scenarios from the decision-maker.

However, depending on the particular system under purview of decision-maker, it may be possible to assume that the attributes comprising the utility functions are constant- with variation only on in terms of acceptability ranges and scaling of the single-attribute utility functions.

So must inquire whether the lower bounds of attribute acceptability may be temporarily broadened in the presence of finite-duration disturbances and, if so, the magnitudes associated with that extension

The concept generation phase of tradespace exploration is concerned with the mapping of form to function. Working way through solutions for how the attributes might be acquired, the designer inspects the attributes and proposes various design variables and associated ranges and enumerations.

Design variables are designer-controlled quantitative parameters that reflect an aspect of a concept, which taken together as a set uniquely define a system architecture. Each combination of design variables constitutes a unique design vector, and the set of all possible design vectors constitutes the design-space.

In the process of proposing design variables, tension exists between including more variables to assess larger tradespaces and limits on evaluating a larger set of designs.

Some models are not accredited for operational use because certain models contain deficiencies, such as optimistic representations of performance and simplistic representations of scenarios. In these cases, while data was initially supplied, the model performance failed to meet the criteria for accreditation.

Subsequently, supporting rationale to explain these failures was not provided, or to explain how the modeling issues skewed the overall performance results. For example, modeled sensor tracking data used in recent tests was compared to real-world sensor tracking data and found that the models representing some systems performed better than the real-world system

These modeling deficiencies can affect other elements that rely on sensor data and can artificially inflate performance. In one case, launch-on-remote capabilities were over-estimated. As a result, the models were not accredited, so there was no verification that test results supporting tested capabilities are credible and reliable.

Additionally, some models used in operational assessments are overly simplistic. For example, modeled representations of the battle scene in moments after intercept do not display the resulting complex scene that is caused by the large quantity of interceptor debris. This deficiency limits insight into how well it will perform during realistic attacks

Efforts to develop digital models can help in this area, by providing more processing power and great scalability for engagement complexity; however, the capability is not expected to be mature for some time.

Threat Models Cannot Be Traced Back to Underlying Threat Assessments: The value of ground test-generated data is dependent on the quality of the threat model that stimulates the test. However, the threat models have never been been accredited before operational testing, and in some cases, after testing.

As is the case with other models, in some cases data needed to accredit the models was not received in a timely manner. Additionally, the threat model used in testing was not traced to the threat model developed based on the intelligence threat assessment.

For example, during a past test event, a model representing an important element rejected the intended threat model and instead ran its own internal threat model. As a result, the test did not reflect real world conditions where the entire system would be exposed to the same threat stimulus.

Test architecture is not designed to generate the data needed to confirm that all elements are reacting to the same model during testing, meaning that testers were not aware that other elements could also reject the approved threat model during testing.

These deficiencies introduce ambiguity into the test results including the extent to which the system operated as an integrated system of systems against a common threat set. Officials are currently working on a pathfinder activity to help understand and rectify the traceability issue.

Although the warfighter and other decision makers rely on models to provide information about system effectiveness, capability delivery documentation does not include information about the quality of modeling data.

Specifically, memos and change packages describing technical capabilities delivered to the warfighter and their limitations, do not discuss the extent to which the models used to assess the new capability are verified, validated, and accredited for assessment, or how test results were affected by model limitations. As a result, decision makers do not have complete information about the validity of the capability assertions in these documents and how much confidence should be placed in reported performance.

Decision makers need access to reliable and timely information to make operational decisions. Additionally, in cases where models and simulations cannot be validated and accredited, any modeling results should be balanced with a clear explanation of which areas of performance assessment could be affected by the lack of accreditation. Lack of such information could lead to miscalculations about how best to employ the system or uninformed decisions about where to focus future capability development and investment.

While officials have recently begun to brief some combatant commands on how modeling limitations impact the warfighters understanding of delivered capabilities, these briefings are not readily available to other stakeholders and decision makers.

“Digital Twin” Simulations are at last matching reality—and producing surprising insights into Real-World Mission Space. Site Visit Executive likes to challenge General Officers. Simulating the formation of real-world mission space, some briefings start by projecting images of creations made by a team of scientists next to photos of real mission results and defies the audience to tell them apart. "We can even trick General Officers. "Of course, it's not a guarantee that the models are accurate, but it's sort of a gut check that you're on the right track."

For decades, scientists have tried to simulate how the thousands pieces of equipment in the observable mission space interact together. But in the past few years, thanks to faster computers, the simulations have begun to produce results that accurately capture both the details of individual fleet components and their overall distribution of parts shapes. "The whole thing has reached this little golden age where progress is coming faster and faster.”

As the fake simulations improve, their role also is changing. For decades, information flowed one way: from the scientists studying real missions to the modelers trying to simulate them. Now, insight is flowing the other way, too, with the models helping guide DoD Leaders. "In the past the simulations were always trying to keep up with the observations. Now we can predict things that we haven’t directly observed.”

The simulations also sound a cautionary note. Some scientists hope mission space formation will ultimately turn out to be a relatively simple process, governed by a few basic rules. However, modelers say their test results suggest mission space is unpredictable. "It's clear from everything that we've done that the physics of the mission space formation is incredibly messy."

Some simulations focus on individual components. Before you can cook up mission space simulations, you need to know the ingredients. Scientists also know the recipe's basic steps. Computer simulations helped develop that theory. As the theory grew more refined, so did the simulations. Recently the Simulation produced a rendering of the mission space web whose structure closely matched how the mission space are strewn through space in digital clusters, threads, and sheets.

Similar simulations suffered from a fundamental shortcoming, however. They modeled the interactions of some components alone, which are easy to simulate. Only once formed did the programs insert components of various sizes and shapes, following certain rules. In such simulations, "The fundamental assumption is that components don't do anything to each other. The interaction is all one way."

Now, modelers include the interactions of ordinary parts with itself and with other components—processes that are far harder to capture. The life stages of fleet components has developed hand in hand with the large-scale structure of mission space.

In general, modelers attack the problem by breaking it into millions of bits, either by dividing space into a 3D grid of subvolumes or by parceling the mass of types of components into swarms of particles. The simulation then tracks the interactions among those elements while ticking through time in, say, multi-mission steps. The computations strain even the most powerful supercomputers.

The simulations are far from perfect. They cannot come close to modeling individual components—even though the simulations point to the importance of feedback effects on that scale. Researchers then employ "subgrid" rules to describe how all that materiel behaves on average. "It's like you're looking through foggy glasses and trying to describe this shape that you cannot see perfectly.”

It’s clear from everything that we’ve done that the physics of mission space formation is incredibly messy. Those rules include dozens of parameters that researchers tune to reproduce known features so tuning raises the question of whether the models explain reality or merely mimic it, like a virtual representation.

But scientists say the models should be reliable as long as they avoid predictions that depend strongly on the tuning. "We're not going to get away from subgrid prescriptions, there's no way. But this is not some kind of magic. It's still physics."

The models have already overturned some long-held assumptions. The usual explanation of what determines mission space size has been knocked down. The models predict other subtle phenomena that observers can try to spot.

Some models operate at huge scales, whereas others generate individual, realistic-looking mission space. They divide space into volume elements or model matter as swarms of particles, then trace their interactions.

By comparing real and simulated mission space, scientists can test key assumptions. But mix in the ordinary components makes predictions change. Perhaps the simulations' single biggest lesson so far is not that scientists need to revise their overarching theory, but instead that problems lurk in their understanding of interactions at smaller scales.

Simulators hope to replace such crude assumptions with models based more solidly on physics. To do that, they're hoping to enlist the help of scientists working on much more finely resolved models that simulate origins of mission space.

Scientists are trying to help put mission space simulations on a sounder footing. “Our interest in this is to replace the tuning with some physics and say, ‘OK, this is what it is, no tuning allowed.“ The goal is to string together results from different size scales in a way that minimises the need for fudge factors. "What you want is a picture that's coherently stitching together across the entire range of scales.”

Ultimately, through observations and simulations, some scientists still hope to develop a unified narrative that can explain how any mission space gets its shape and properties. But many mission space modelers believe the recipes will always be complicated and uncertain. Mission space formation may be like the weather, which keeps precise predictions forever out of reach because of its chaotic nature.

“We’re quite concerned that we'll understand the big picture but never understand the details. In that case, the increasing realism of mission space simulations may serve only to underscore a fundamental complexity of real-world missions.

1. Formulate mission statement and quantify decision-maker value requirements during nominal and emergency states

2. Develop concept-neutral system models of disturbances in operational scenario of proposed systems.

3. Set out survivability principles by incorporating susceptibility reduction, vulnerability reduction, and resilience enhancement strategies into design alternatives.

4. Model/Simulate baseline system performance of design alternatives

5. Gain an understanding of how decision-maker needs are met in a nominal operational scenario

6. Model/Simulate impact of disturbances on lifecycle design performance of alternatives across representative sample of disturbance encounters

7. Provide examples of how decision-maker needs are met in disrupted scenarios

8. Apply time-weighted survivability metrics like utility loss and threshold availability for each design alternative

9. Provide summary statistics for system performance across representative operational service life

10. Explore trades and perform integrated cost, performance and survivability trades across design space to identify alternatives

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Top 10 Depot Sustainment Team Questions Baseline Product Support Timelines Drive Readiness Levels

7/1/2018

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Marines are actively pursuing advanced manufacturing, integrating a number of cutting edge technologies including robotics, artificial intelligence, machine learning, and additive manufacturing to improve products or processes and revolutionise the way depots maintain, repair, and recapitalise equipment. With new capabilities coming on line, we will be able to quickly replicate difficult to obtain parts, translating to reduced down time and higher operational readiness rates.

New technologies like automation and robotics, accompanied by upgrades to facilities and infrastructure, have enhanced productivity at Marine Corps Depots. As productivity and efficiency increase we are seeing corresponding decreases in labour, maintenance, and operational costs.

The depot readiness enterprise recently transitioned to business systems that use standard, industry recognised processes. The Logistics Modernisation Program is built on off-the-shelf tools for Resource Planning and shop floor integration.

These tools give us complete visibility on manufacturing and service operations, a capability we now have for the first time. These applications also help us improve the accuracy of our work orders; engage in more efficient production scheduling; enable interaction with our diverse vendor supply chain and reduce delays for parts.

These capabilities are increasing the speed at which materiel reaches the warfighter, and provides Marines with true “factory to foxhole” asset visibility/tracking. Depot enterprise is executing a number of supply chain initiatives to improve its effectiveness, including improving demand forecasting accuracy and imposing tougher performance standards on suppliers. These efforts create ability to purchase, manufacturer, and repair critical parts required to support warfighting equipment.

Maintaining good equipment condition is particularly important given the current high pace of operations for equipment units, as well as the potential for a further increase in operational requirements. However, DoD reset process has often delivered equipment to units late, affecting units’ ability to schedule and execute training as they prepare for their next mission.

DoD is aware of challenges in completing maintenance and returning reset equipment to units, and has identified several factors that contribute to delays, but has not assessed how much each of the factors contribute to delays.

Unless DoD conducts a comprehensive assessment of the relative importance of the factors affecting equipment reset timeliness and develops and implements appropriate corrective actions to address the results of the assessment, it will not be positioned to target its efforts most effectively to take corrective actions.

Equipment units have utilised a series of actions to mitigate the impact of delays in equipment receipt after maintenance, but such mitigation actions are sometimes not feasible or optimal. For example, officials said DoD shares equipment between battalions that are collocated on the same installation, but at different points in the readiness building timeline.

Specifically, when one battalion turns in equipment for reset, certain pieces of equipment from another battalion on the same installation, if available, might be borrowed to conduct training. Battalion officials noted, however, that this measure may not always be feasible.

Leadership from two battalions, for example, cited instances where their units were unable to train during their reset periods and could not borrow equipment from other battalions located on the same installation because those battalions were deployed.

In addition, units use simulators to conduct individual-level training to give personnel experience with new system upgrades, though brigade officials noted this is a stopgap measure while units are without equipment and does not allow for collective training.

Units can—once delayed equipment arrives or via borrowing equipment—conduct some collective training for extended hours each day while at their home station, but a battalion official noted that doing so is also not optimal for unit morale.

Supply chain problems impact challenges in obtaining needed repair parts and Internal depot quality controls identify depot work or parts deficiencies that require additional time to correct Equipment transportation Time equipment spends in transportation to and from the depot reduces available time for depot work .

According to officials, unit leadership of some deployed battalions do not emphasise preventive maintenance. As a result, equipment may not be properly maintained to adequate standards and can create additional work tasks for depot personnel when they receive it, such as conducting additional or more detailed inspections.

Officials cited some instances where equipment sent to the depot arrives in worse than expected condition, either due to damage incurred during transport or because unit personnel did not accurately report the condition of the equipment prior to turning it in.

For example, officials said a launcher was returned to the depot with unexpected severe corrosion on power cables, and certain equipment items, such as generators, were completely inoperable.

Officials cited another instance where a radar was pressure-washed prior to its return to the depot, causing extensive damage. These kinds of unexpected conditions result in greater repair work than anticipated for depot employees.

Supply chain challenges include inconsistent forecasts for parts orders but some depots are taking steps to improve its own forecasting. An official also noted that problems can arise if sole-source suppliers for critical parts go out of business, or if they have to order parts that are no longer regularly produced by vendors. For example, a radio is no longer in production so programme office is working with headquarters officials to identify a solution.

Depot quality controls impacted time spent correcting maintenance errors and quality defects—such as incorrect assemblies, defective parts, or improper painting during depot operations—contributing to the depot’s timeliness challenges.

For complex systems, some maintenance tasks can be challenging because it can be difficult to isolate equipment faults. For example, if system is composed of thousands of elements work requires extensive testing to ensure that each element is operational.

Officials said processes are designed to ensure that finished products meet operational standards, and that doing so sometimes takes longer than expected. DoD uses a series of metrics and reporting methods, such as internal tracking of defects and surveys and reports from customers, to monitor, document, and correct quality defects during maintenance process to ensure that any maintenance errors or defects are identified before the equipment is returned to units.

Equipment transportation time is included in policy for returning equipment from reset to units, and it often takes a significant amount of time before equipment is transported to the depot from theater. So depot can be left with less time to complete reset work before it has to return equipment back to units if it is to meet requirements.

Quality defects that may affect timeliness can still arise so DoD must establish target for hours spent at the depot correcting quality defects that arise during maintenance, which are then tracked and used as indicators of the overall quality of the maintenance process. As tracked by the depot, time spent correcting quality defects varies, when averaged across each time period.

Officials said depot is in early stages of adopting cost and schedule performance index metrics, with potential to improve depot forecasting and better inform decision making.

DoD uses a series of measures to mitigate parts availability issues, such as having the depot utilise its own equipment to fabricate some items on short notice and by taking parts from incoming equipment and using them for equipment nearing completion of maintenance.

Depot has received authorisation to purchase critical “long-lead” parts for specific items in advance of anticipated need, but usually depot is not allowed to purchase items without funding in place so cases exist where teams are unable to acquire critical parts, or lack the funds to do so delays occur.

DoD must place emphasis on importance of transportation of equipment and its effects on timeliness. While there is ongoing work to identify and correct issues as they arise, efforts to correct these issues are conducted in isolation from one another and not compiled and compared to enable DoD to identify their relative importance in terms of effect of each factors effect on timeliness.

DoD has options to increase the pace of availability recapitalisation, but each of these options poses challenges. One option is to reduce the amount of equipment available for ongoing commitments and recapitalise it at the depot. Officials said one way DoD could increase the pace of recapitalisation would be to reduce the amount of equipment available for ongoing commitments, but that this is not feasible given the current high pace of operations. Further, DoD does not anticipate that operational requirements will lessen under projected security scenarios.

The near-term schedule assumes that ongoing operational commitments is not likely to change and is designed to line up recapitalisation with currently scheduled operational deployments and training. Officials responsible for coordinating the near-term schedule told us that the near-term schedule has little flexibility given DoD limited force structure.

Another option is to procure additional equipment to provide to units turning in equipment for recapitalisation. Officials said DoD could buy extra equipment to provide to additional units turning in their equipment for recapitalisation to accelerate the recapitalisation pace.

Officials said if DoD were to adjust the pace to recapitalise more battalions, it would require buying more equipment to ensure that any additional units undergoing recapitalisation would not be left without equipment.

DoD has reviewed its options and the associated challenges related to increasing the pace of recapitalisation and has decided the best path forward based on its review is to continue recapitalising battalion equipment at same rate although this pace of recapitalisation includes some risk—as identified by DoD officials—and will likely create challenges in meeting long-term goals for equipment systems

1. Can contracts vehicles enabling modern maintenance processes be made more efficient for determination of condition/function reporting, transit, work load assign?

Maintenance process flow diagram should be created to show the different steps that an unserviceable asset experiences until it is fully repaired. When examining the maintenance process, product support directorate should consider the average number of maintenance days required per unit, and the period demand rate for maintenance.

Another consideration is how many of the candidate assets are in inventory and are subject to sustainment financial obligation. Assets with a larger number of units in inventory typically present a greater opportunity for cost savings. Any inefficiency that could potentially be eliminated by introducing performance-based incentives must be identified.

2. Are there any substantial delays in the repair process?

The team should review the current maintenance and repair processes and identify any delays, issues, or opportunities for improvement that could be addressed by introducing a performance-based arrangement.

Bottlenecks in the process step where the duration is the greatest must resolve that issue first. When identifying issues in the repair process, the team should also investigate the root causes to better understand the reason for delays.

Even when Warfighter requirements are being satisfied, it is possible for performance-based logistics to deliver greater efficiency leading to improved process agility and/or reduced cost.

3. Can sustainment planning and demand forecasting be more accurate and efficient through the introduction of performance incentives?

If product support provider is held accountable for an outcome that is impacted by the accuracy of the demand forecast, they will be incentivised to assist directorate with improving this forecast.

If the agreement with product support is for maintenance services, for example, the product support provider may have more detailed information about failure rates and system reliability across the fleet that will improve the demand forecast.

4. Is the supply support strategy satisfying Warfighter requirements?

The team should verify if the Warfighter requirement metrics are being met from a supply perspective. If they are not being met, the team should try to identify the percentage of non-mission capable assets due to supply shortages. This should give the team a starting point to assess opportunities to resolve these shortages through performance-based arrangements.

5. Can supporting supply chains be made more efficient through introduction of performance incentives?

The current state of supply support should also be assessed to find opportunities to increase readiness and reduce cost when pursuing a change in sustainment arrangement. A well-structured performance based logistics agreement would provide incentives for the product support integrator to reduce supply chain inefficiency.

A long-term contract would provide the product support integrator the opportunity to recoup investments in process improvements, lay-in of spare parts, and redesign of components for improved reliability.

Depending on the scope of a potential performance-based logistics, integrator could be responsible for reducing delays and inefficiencies across the entire supply chain. Based on these opportunities, the Programme directorate can determine if the timing and current state of the programme will allow a smooth transition into a performance-based arrangement.

6. Are there any substantial delays in the procurement process for spare parts or new units?

One process that impacts the system’s availability may be the lack of repair parts. For example, delays, deficits in manufacturing, packaging issues, and poor inventory control are potential causes of materiel availability problems. Performance incentives will encourage suppliers to reduce their internal transaction lead time, particularly improving their make and delivery processes to mitigate the shortages of the Warfighter.

7. Are there any significant inventory build-ups at any stage in the supply chain or are parts no longer made available?

Significant inventory build-ups are a sign of supply support inefficiencies, potentially a bottleneck in the process. The process right before may be overproducing, or perhaps the process right after is unable to keep up due to quality issues. In order for materiel to flow smoothly, the entire supply chain must be leveled.

Many programme offices confront issues with parts supply within their supply chain not readily accessible, as technologies change and some sources or materials are no longer available. These issues can be mitigated through active teamwork and monitoring efforts, which should involve the relevant industry participants.

A performance-based arrangement could be structured to hold product support provider responsible for ensuring the availability of parts that are subject to shortage concerns, so product support provider would be required the to actively address these concerns in coordination with programme office.

8. What is the scope of opportunity for repair teams to get access to system technical specs?

A repair part or repairable used on multiple systems or an end item used by more than one military Service provides the opportunity to evaluate an enterprise-wide arrangement. There is a potential to save in terms of maintenance spend and inventory costs by aggregating the requirements and improving supply chain efficiency.

Generally, the larger aggregated requirement improves the negotiating position of the programme directorate during contract discussions. An enterprise-wide performance-based logistics strategy for multiple systems must be pursued whenever doing so will satisfy Warfighter requirements and reduce costs.

If the technical specs packages are not purchased as part of the initial acquisition, limitations can occur for that particular programme. If a lack of technical specs exists, Services will be limited to the removal and installation of units, placing limitations on conducting diagnostic testing and work against in-house or alternate repairs. If contracts with subcontractors exist, restrictions in independently selling technical specs also confines the programme in range of future sustainment options.

9. Does the available contract mechanism not conflict and allow for a long-term performance-based arrangement?

The programme directorate must determine whether a performance-based logistics agreement is feasible under the current funding mechanism used for sustainment, or any alternative funding mechanisms that are available.
In particular, the programme office needs to determine whether the funding mechanism allows for funding of long-term contracts.

Working capital-funded programmes allow for long-term performance arrangements with long-term incentives, and working capital funds have been successfully used for contracts in the past.

Ability to pursue performance-based logistics arrangement may be limited by existing contracts. If there is an existing long-term contract in place that will not expire by the time performance-based arrangement could be established, the programme team must consider postponing the effort. Otherwise, the existing contract must be terminated in addition to negotiating a performance-based logistics arrangement.

10. Is it the right time for a change in sustainment strategy with enough time remaining to benefit from emerging technology and performance-based logistics business model?

Performance-based logistics contracts work best when implementation is possible through a series of long-term contracts, allowing the product support provider enough time to recoup investments in process improvements and product modifications.

Additionally, a series of long-term contracts allows programme directorate to recoup the realised cost savings during the renegotiation phase of each contract cycle. Stable and predictable revenue streams resulting from long-term contracts are desirable to both shareholders and capital markets so result of negotiation is lower costs in exchange for increased contract length.

Assets with longer expected service life in the inventory present the opportunity for greater savings from to performance-based sustainment strategies. The team should consider available technology base for system in terms of potential risks and benefits. Technology insertion/refreshment over the entire service life and the associated challenges, risks, and benefits to supportability should also be addressed, along with the risk associated with achieving performance requirements.
　

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