Marine Magnet Dispatch Service Centre

Top 10 Product Visualisation Types Select Agent Behaviour Cooperation Determine Virtual Reality Design

6/7/2018

Virtual Reality interactive 3D visualisation help Marines better understand the product design features. Due to the many possible ways to configure a customised product, the Virtual Reality model of a customised product can not be pre-defined. It has to be dynamically generated during customisation.

Previous research on Virtual Reality-based visualisation of customised products only consider geometry and appearance; the behaviour is seldom considered. Here we propose an approach to dynamically generate behavior-included Virtual Reality models for customised products.

First the customisation strategy and the behaviour programming strategy are discussed. Then a variant approach for dynamic generation of behaviour-included Virtual Reality model is described. Finally, the process to construct the Virtual Reality model template and to dynamically modify the template during run-time simulation is described.

"The capability that a 3D printer brings to us on scene saves the Marine Corps time and money by providing same-day replacements if needed. "It makes us faster than our peer adversaries because we can design whatever we need right when we need it, instead of ordering a replacement part and waiting for it to ship."

“As a commander, my most important commodity is time,” Although our supply personnel and logisticians do an outstanding job getting us parts, being able to rapidly make our own parts is a huge advantage.”

Marine Corps used the 3D printer as part of a process otherwise known as additive manufacturing. Without a 3D printing capability, an entire assembly would have needed to be replaced, a more expensive and more time-consuming repair. Rather than waiting weeks for a replacement the new part was printed, approved and installed within a few days.

The repair demonstrates the value that additive manufacturing technology brings to forward-deployed units. “I think 3D printing is definitely the future ― it’s absolutely the direction the Marine Corps needs to be going,”

The Marines aren't the only ones working on 3D printing. The Navy is using it to make submersibles, and the Air Force was looking at 3D printing to produce replacement parts.

But the Marine Corps has expressed particular interest in the technology and unit commands broad permission to use 3D printing to build parts for their equipment. The force now relies on it to make products that are too small for the conventional supply chain, like specialised tools, radio components, or items that would otherwise require larger, much more expensive repairs to replace.

Product customisation is one of most important enterprise goals must satisfy Marines requirements to offer reliable 3D product suitable for particular battalions. Product customisation is necessary to increase enterprise competitiveness.

Quality and costs goals create requirements to meet product configuration standards with well known product core and redesign of only chosen product components.

Product adaptation to the new application is a way of product development which assures product quality in regard to manufacture and fiscal determinants. Product planning needs information related to customer expectation and product characteristic enabled by Quality Function Deployment.

Problems arise in application of 3D technique supported decisions in early phase of product development so meeting Marines requirements is the most important task of product development in context of product customisation.

The link between Marines expectation and product characteristic is the crucial point in product planning. Marine needs are divided into two categories: revealed as related to product trade features satisfied in proportion like low price, fast delivery and products technical characteristics to include utility and functions.

The design problem includes, among others the problem of product decomposition where 3D configuration issue needs information related to product functions and components that implement the function. Product physical elements named components assembled together are accomplishing product functions.

Common solution is to present the visualisation just at the end of the configuration process, once the process has been finished. Better, however, is to present the user a continuous visual representation of the resulting product during the configuration process, guiding user through every single configuration step by an on-point visual representation of the recent state of specification.

Visualization is one of the strongest instruments to create trust and reduce the risk perceived of the user - and to increase the willingness to purchase. There are different ways of how visualisation can be technological implemented.

The presentation of pre produced pictures is a common and of course a good possibility to show the product linked to the configuration solutions. But also simple drafts are seen quite often. The big problem with this kind of visualisation is that each variation has to be produced in first. For offerings with a large number of variations this becomes very soon a problem and causes a lot of cost.

Compound Pictures visualisation involves pictures of the product a put together out of single components. Just like a box of bricks the product picture is set together out of the different pictures of components. This has the advantage that not all possible configurations have to be produced and only the visible parts must be indicated.

Rendered pictures is a more advanced way of producing a picture of a product and is some distance to the way of taking photos. Rendered pictures need vector graphics of the product or the components.

But these vector graphics don’t give a real product view. The surfaces first have to be coated by a texture and then are illuminated by the computer. A lot of advantages and possibilities are with technique convertible. Different views, colors, textures, illuminations can be shown without existing in the real world at all.

The most advanced technique of visualisation is building of 3D models. Although the structure is close to that of the rendered pictures the effort is much higher. The 3D models can normally be free rotated and sometimes even has some of the products functionality integrated.

The computing capacity and the complexity of the programmes you need to generate such models are very high and expensive. But it gives the customer the closest visual feeling of the real product. And the next step in visualisation is already on the way.

3D visualisations of system behaviour over time generally reailise benefits to include quick and easy ways to grasp overview of the quality of solutions. After all, a picture is worth a thousand words. 3D visualisations of system behaviour within its Marines operational space make solution exploration even more tangible for developers.

Moreover, non-technical field-level Marines can much better assess if the system behaviour meets their requirements, when they can actually see the system behaviour compared to when they receive indirect feedback based on unrealistic tests.

Different scenarios can be visualised to clarify questions and evaluate possible solutions together with developers. Consequently, non-technical field-level Marines are more likely to contribute good feedback for further development.

So one big advantage of system behaviour visualisation is the reduction of possible misinterpretations and misunderstandings, which are caused by assumptions to cognitively map indirect feedback into system behaviour.

When visualisation is used together with Mission outcome simulations, flaws, which otherwise might only be determined when tests with real 3D prototypes are conducted, might be found considerable earlier. As a result, visualisation can also help to reduce system development costs and time-to-market.

Visualizations leverage the field-level Marines visual system to support the process of sensemaking, in which large information is collected, organised, and assessed to generate knowledge and inform action.

Even while most of our efforts to date focuses on the interaction between a single user and an interactive display, visual assessments are rarely solitary activities. Marines must share and communicate their findings.

In practice, making sense out of constraints is often a behaviour process involving parallel effort, discussion, and consensus building. So to fully support efforts to make sense of constraints, interactive visualisation should also support behavioural interaction.

However, the most appropriate collaboration mechanisms for supporting this interaction are not immediately clear. Here we present design considerations for disruptions in collaboration of visual assessments under field-level operational constraints, highlighting issues of parallel work, communication, and organisation of Marines units. These considerations provide a guide for the design and evaluation of collaborative visualisation systems.

Some groups of Marines may disagree on how to interpret visual representations contribute contextual knowledge that deepens understanding. As Marines build consensus or make decisions, they learn from their peers. Furthermore, some visual sets are so large that thorough exploration by a single Marine is unlikely.

In assigning critical Marines mission tasks, scenarios include possibility of multiple Marines in the field to form coalition decide not to cooperate with the rest, Removal of this coalition of Marines and their links might disconnect the network making it impossible for all Marines in the field to reach an agreement

Marines must solve gap between unconstrained/constrained consensus problems. An unconstrained consensus problem is simply the alignment problem while in distributed sequence of a function, the state of all has to more or less become equal meaning that the consensus problem is constrained.

Solving the constrained consensus problem is a cooperative task and requires willing participation of all Marines. Suppose a single group decides not to cooperate with the rest of participants and keep its state unchanged. Then, the overall task cannot be performed despite the fact that the rest of groups reach an agreement.

Physical space Marines are operating in exists within the virtual world represented by 3D navigational device. Transformation node at the top of the user space allow the user to position the user space anywhere in the virtual world.

In this representation user is always within the user position space and tracked with respect to the centre of the user space. Tracker values are assigned directly to transformation nodes to maintain correct position within the virtual world.

Product decomposition gives information about physical elements to be selected or designed to perform product function. Product functional decomposition should represent the intended behaviour of products and their parts.

Function of the assembly simulator is to support interactive constraint-based assembly/disassembly operations to support real-time simulation of physical constraints within the virtual space to provide realistic interaction between virtual assembly components.

Example of constraint specification and satisfaction problem involves alignment of a shaft with a cylindrical hole satisfying an axis-alignment constraint. Disassembly operations involve breaking the previously defined constraints by applying an external force.

Constrained rigid body motions of the assembly parts are used to support realistic manipulations of assemblies without breaking the existing assembly constraints by converting the 3D manipulation info from input device into allowable rigid body motions. Manipulation of an assembly model is not allowed if it is not supported by its allowable rigid body motion.

Once the assembly parts are loaded into the scene graph via design interface, attention to inputs allows the user to grab and manipulate objects in the 3D space. During this process, position of the moving object is sampled to identify new constraints between the manipulated/surrounding objects by the assembly simulator.

Such scenarios regularly arise in Marine network intelligence. Consequently, the design of visual technologies could benefit by considering behaviour interaction in addition to perceptual and mission critical processes. So the design of collaborative visualisation tools is a huge challenge.

Business visualisation is becoming increasingly important, Marine Leaders recognise the power of Marines visual intuition in information-rich decision tasks. Nevertheless, despite its promises, 3D visualisations are far less common than one would expect.

Here we describe a case study where we took a conventional visualisation of mission process as a starting point, for which we subsequently provided a 3D virtual reality visualisation. We introduce a small collection of 3D visualisation gadgets and associated behaviours,-- proved to be relatively complete for our case.

For each of these gadgets and behaviours, we discuss requirements and design trade-offs. The case study concerns an actual mission state process of the largest security provider, illustrating the usability of our gadgets and their associated behaviours, which include grouping, and drill down manipulation.

The cooperative behaviour aspects of visualisation has taken on new importance with the rise of modern Marine networks, enabling collaboration between participants acting in different battlespace locations and at different times.

This distributed, style of limited collaboration introduces new challenges for progress in visualisation modernisation. Most existing efforts to characterise collaborative visualisation has focused on coordinated cooperative scenarios-- with users working together at the same time to assess results or communicate the state of a battlefield.

Collocated collaboration usually involves shared displays, including large wall-sized screens and table-top devices. Systems supporting remote collaboration have primarily focused on coordinated interaction such as shared virtual workspaces and augmented reality systems that enable multiple users to interact concurrently with visualised operational directives.

Potential benefits of interactivity include changes of behaviour models, simulation parameters and system field-level scenarios during simulations facilitate an explorative solution development process and solution tuning. Developers do not have to wait for changes to take effect, for instance due to the compilation process and restart of simulations.

Instead, developers instantly see how the system behavior changes based on their modifications. So iterative, model-driven development process can be potentially performed more efficiently using interactive changes.

In contrast, relatively little attention has focused on how limited collaboration around visualisations affects mission outcomes. But by partitioning work across both time and space, limited collaboration may provide greater scalability for group-oriented missions.

There is evidence that, due in part to a greater division of labour, uncooperative decision making can result in higher-quality outcomes – broader discussions, more complete reports, and longer solutions – than face-to-face collaboration. One challenge to achieving the benefits of limited collaborative actions is determining the appropriate design decisions and technical mechanisms to enable effective collaboration around visual reality media.

Creating effective collaborative visual reality operational space raises a number of design questions. How should collaboration be structured, and what shared articles can be used to coordinate contributions? What are the most effective communication mechanisms?

To answer these questions, we envision future development projects of varying scopes. Marine leaders must focus on new visualisation and interaction techniques for supporting collaboration. Leaders must propose advanced mechanisms and ideally evaluate them through comparative study with other approaches. As listed above, new network communication models, pointing techniques, and story-telling interfaces are all candidates.

Future efforts into targeted techniques must be balanced with the design,, deployment, and evaluation of complete structural collaborative visual virtual reality space. Such systems will enable real-world groups to conduct collaborative virtual scenarios.

Studies of system usage can then measure the benefits of collaborative visual assessments in valid mission space settings and inform best practices for combining collaboration mechanisms.

A number of important experiments, such as those involving group directive organisation and incentives, may be best conducted in real-world settings and interfacing with the modern networks is critical to understanding how findings are disseminated and how collaborative virtual communications can be more deeply integrated into design of modern networks. These and other challenges present exciting opportunities for advancing visual system assessments.

We have presented design considerations for collaborative virtual reality systems, attempting to identify the aspects underlying successful collaboration and suggest mechanisms for achieving them.

Highlights include a list of collaborative virtual reality driven tasks and techniques to improve shared context and situational awareness level of field units, and suggestions for increasing engagement and allocating effort.

The overarching goal is to design behavioral/technical systems that improve our capabilities by promoting an effective division of troop tasks among participants, facilitating mutual understanding, and reducing the costs associated with collaborative tasks.

Visiting these considerations also provides an agenda for future research in collaborative virtual reality mission space to bring proposal to the surface of leadership attention and suggesting new technical mechanisms. For example:

1. Translate customer requirements into product specifications

2. Assist in quality product design based on product specification

3. Create optimal process design based on product design

4. Choose best process design based on product specifications

5. Translate product and process design into quality 3D item production

6. Define final test procedure and criteria to ensure product quality

7. Make cost projections based on customer requirements

8. Prepare cost projection based on customer specifications

9. Determine cost estimate based on product/process design

10. Predict final product cost based on operational priorities

Additional questions for future attention include:

1. What is the effect of different discussion models e.g., independent, embedded, and doubly on participation and the establishment of common ground?

2. Beyond textual discussion, what external representations will effectively support collaborative analysis and how do the representation affect grounding and the cost of integration?

3. How can the coordination of individual contributions be improved?

4. Can semi-automatic summarisation or merging of separately developed virtual reality views be used to form aggregated contributions?

5. How should selection and visual emphasis techniques be designed to provide realistic pointing behaviours?

6. Can referenced objects be clearly recognised by both Troops and machine collaborators?

7. How can pointing and graphics annotation be designed to handle dynamic visualisations and changing task sets?

8. How should behaviour navigation cues be effectively added to visual assessment tools to improve battlespace awareness?

9. Can automated techniques be used to help allocate effort by digging into past contributions, user profiles, and inferred networks to enable systems to direct collaborators to tasks in need of attention?

10. How can beneficial results of collaborative virtual reality assessments be more effectively exported, shared, and embedded in external network media?

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Top 50 Structured "Digital Twin" Simulation Model Require Multi-Agents Task/Subtasks Perform Training

6/1/2018

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Traditionally, Simulation training aboard Marine Corps Fleet Systems has relied predominantly on "Modeling the Expert" for complex behavioural tasks—the person undergoing training watches and imitates the performance of senior professionals.

This modeling is generally accomplished through on-the-job observation and hands-on experience in Mission space of systems. In the absence of comprehensive instructional design and attention to instructional abilities of the expert who is being modeled, this approach may have important limitations with respect to the quality of the training experience.

The overall training programme, not just one component, must be effective, with Simulators selected and designed to meet training needs instead of structuring training to fit the simulator.

Training performance must be measured against predefined performance criteria and be continued until the required proficiency level is reached. No matter how well the training programme is designed, refresher training may be needed to maintain a level of knowledge and skills. Structured evaluation of trainee performance prior to, during, at conclusion of, and after exercise is required to monitor programme effectiveness.

1. Overall training programme, not just one component, must be effective

2. Simulators must be selected and designed to meet training needs

3. Must guard against structuring training to fit the simulator

4. Training performance must be measured against predefined performance criteria

5. Training must be continued until required proficiency level is reached.

6. No matter how well the training programme is designed, refresher training may be required to maintain skill levels

7. Must establish structured evaluation of trainee performance prior to programme execution

8. Carry out operational assessments at the conclusion of training

9. Conduct debriefing after programme is reviewed to monitor programme effectiveness.

10. Conditions in Fleet System Workshops must be conducive to transfer of training to implement vital policies/practices

　

Top 10 “Digital Twin” Benefits/Value from Creating Simulation Leads to Changes in in Real World Operational Tactics

"Digital Twin" Simulator Mobile Fire Support Trainer for fire support teams can operate without having to deploy artillery units out to the field or have tank hulls to shoot at, they can put on those goggles and they can send a call for fire.

It will insert targets, potentially even moving targets – which we typically don’t get, we’re usually just shooting at old rusty tank hulls that are sitting on the ground. So we can have moving targets. We can integrate those fires with simulated forces that are moving towards an objective – so you can validate that you can turn off your fires at the right time.

We’ve realised we just can’t train those pockets of Marines independently. You really need to be able to connect those different training audiences with "Digital Twin" Simulation to work their procedures and do supporting and supported relationships and do those standardised tactics and get used to working with Marines in other troop groups.

As you send your calls for fires, requests for support, and do battle handoffs with them integration is required between a bunch of different training systems that were originally not designed or procured to ever work with each other.

1. Identify current configuration of field equipment increase perform

2. Improve product design and engineering change execution

3. Reduce operations and process variability

4. Create digital record of parts to assign tracking requirements

5. Reduce overall time/cost to field new product

6. Recognise long-lead-time components and impact to supply chain

7. Locate products in the field ready for upgrade

8. Improve time, efficiency and cost to service product

9. Predict and detect quality trend defects sooner

10. Determine when quality issue started

Top 10 Best Practice Model Steps for Simulating Equipment Status Updates in Systems Product Design/Service
　
Simulation Models are essential to giving orders directed at deploying complex interdependent systems and to communicate among team members and stakeholders.

Simulation provides a means to explore concepts, system characteristics and alternatives; open up the multi-agent trade space; facilitate informed decisions and assess overall system performance.

Must leverage collaborative innovation of numerous participants across multi-agent enterprise, permitting shared risk, maximised reuse of assets and reduced total ownership costs.

Combination of open systems architecture and an open multi-agent model permits acquisition of modular and interoperable system, allowing for system elements to be added/modified and replaced over duration of mobile exercises.

Modular open architecture includes updating key interfaces within the system and relevant design disclosure. Key enabler is adoption of an open multi-agent model requires doing mission status updates in a transparent way.

Smart to allow for system elements removal and/or support by different groups throughout the duration of exercise so afford opportunities for enhanced competition and innovation.

1. Demonstrate critical tech close to final form, fit and function within ops scenario

2. Complete system functional requirements review

3. Carry out system design review before system development start

4. Constrain system development phase to best estimates of future target date

5. Release design drawings to build simulation and test system-level integrated prototype

6. Establish reliability growth estimates and identify critical simulation processes

7. Identify key product characteristics and detect system faults and effects

8. Conduct producibility assessments to identify simulation tech risks

9. Make sure simulation meets cost, schedule and quality targets

10. Test simulation -representative prototype in intended scenario

Top 10 Elements of Marine Tactical Decision Kits Predict 3D Printed Parts Operational Scenarios to Build Effective Training Events

For deployed units, the ability to print parts on the go reduces the time it takes to secure new replacement parts and it also saves on the amount of gear the unit needs to take on deployment. For the operational crews, most importantly, 3D printing saves on lost training time and scrubbed operational sorties.

“While afloat, our motto is, ‘Fix it forward.” “3-D printing is a great tool to make that happen. Marines can now bring that capability to bear exactly where it’s needed most—on a forward-deployed MEU.”

1. Rapid decision-making

“The ability to think critically, innovate smartly, and adapt to complex scenarios and adaptive adversaries has always been the key factor we rely on to win in any place.”

2. Competition results in solid tactics

“We will promote experimentation of new concepts and capabilities during scheduled training events in order to test, fail, adjust, learn, and advance our capabilities.” “We will continue efforts to decrease centralised proscribed training requirements to accomplish mission essential tasks.

3. Force-on-force: a thinking adversary

“We will emphasise and increase opportunities to conduct force-on-force evolutions and operations within degraded scenarios in our training in order to challenge our Marines against a “thinking adversary” and maximise realism.”

4. Training decisiveness in any scenario

“While the means and methods we use to conduct operations will always be changing, we must always be prepared for combat.”

5. Immediate review & feedback

“We will continue striving to do what we do today better, but also be willing to consider how these same tasks might be done differently.”

6. Leveraging cross-function strengths

“Consist of a highly trained and educated force operating the most modern and technologically advanced equipment available…”

7. Create an training stage where Marines can enhancing decision-making and cohesion
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With less than 30% of time spent training in the field, Tactical Decision Kits concentrates rapid decisions with immediate feedback in garrison.

8. What the Tactical Decision Kits System Does

Interactive system allows users to create and execute in-depth, customisable systems that show second and third order effects of decisions, as well as being capable of preparing debriefs, or digital Sand Table Exercises, among other uses.

9. Virtual Battlespace

A first person shooter that places the Marine in up to squad- and platoon-level force-on-force scenarios where Troops are forced to think tactically, make decisions and communicate to Troops subordinates as well as his adjacent unit in a complex, competitive scenario utilising a range of supporting assets.

10. Augmented reality

This system allows Marines to use live Indirect Fire assets and real life Close Air Support while manoeuvreing digital generated troops, enabling the user to physically see both real impacts on the deck with a manoeuver element all in one picture. They are also capable of using a real life manoeuvre element with digital-generated Indirect Fire assets and real life Close Air Support capabilities

　
Top 10 Build Principles Make “Digital Twin” Select Decision by Authority Functions of Agent/Machine Option Levels Activities

1. Manual Build

Agent performs all tasks including monitoring the state of the machine, generating performance options, selecting decision making option to perform and physically implements it.

2. Action Support Build

At this level, the machine assists with performance of the selected action, although some agent control actions are required.

3. Batch Processing Build

Although agent generates and selects the options to be performed, then options are turned over to the machine to be carried out automatically, primarily in terms of physical implementation of tasks.

4. Shared Control Build

Both agent and machine generate possible decision options with agent retention of full control over the selection of which option to implement, but carrying out the actions is shared between the agent and machine.

5. Decision Support Build

Machine generates a list of decision options, which agent can select from, or generate own options, when selected turned over to the action model to implement. This level is representative of many expert systems or decision support systems that provide option guidance, which agent may use or ignore in performing a task. This level is indicative of a decision support system capable of also carrying out tasks, while previous shared control level is indicative of one that is not.

6. Blended Decisions Build

At this level, machine generates a list of decision options, which it selects from and carries out if agent consents. Agent may approve of the machine selected option or select one from among those generated by machine or agent then action carried out by machine. Representative of high-level decision support system capable of selecting among alternatives as well as implementing the selected option.

7. Rigid System Build

This level is representative of a machine that presents only a limited set of actions to agent selecting from among this set. Agent cannot generate any other options so machine is rigid in allowing agent little discretion over options and fully implements selected actions.

8. Automated Decisions Build

At this level, machine selects the best option to implement and carries out that action, based upon a list it generates augmented by alternatives suggested by agent so decision making is automated in addition to the generation of options-- as with decision support systems

9. Supervisor Control Build

At this level, machine generates options, selects the option to implement and carries out that action with agent mainly monitors action and intervenes if necessary so role is to make different option selection from those generated by machine-- example of typical supervisory control system in which agent monitoring and intervention is expected in conjunction with a highly automated system.

10. Full Automation Build

At this level, machine carries out all actions with agent completely out of the control loop and cannot intervene-- representative of a fully automated system where agent processing is not required
　

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Top 50 Models/Simulation Tools Utilised by Multiple Functional Areas During System Service Life

6/1/2018

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Models, simulations and metrics must be developed in well-defined and controlled engineering work space to support programme reuse of information across acquisition life phases or for reuse and repurposing in product support efforts.

Models, simulations and metrics must be integrated and controlled to ensure that the products maintain consistency with the system and external programme dependencies, provide a comprehensive view of the programme and increase efficiency and confidence throughout the product service life.

Models and simulations provide:

1. Efficient communication among stakeholders about relationships between system requirements set and the system being developed

2. Precise engineering metrics and traceability of designs to requirements

3. Exploration of system design element alternatives to support early identification of viable system change request solutions

4. Alternative solutions for building prototypes and enabling cost savings

5. Improved capability to address defects and failures at all levels for enhanced of the system.

6. Assigned engineering and design trade-off assessment studies

7. Support for early interface and interoperability testing

8. Greater efficiencies in design and simulation capabilities

9. Reduction in time and cost of iterative build/test/fix cycles

10. Insight into program cost, schedule, performance and supportability risk
　

Top 10 Modular Open Systems Approach Defined as Acquisition/Design Strategy

Modular Open Systems Approach consists of technical architecture adopts open standards and supports a modular, loosely coupled and highly cohesive system structure.

Modular open architecture is not an end result sought by the warfighter or end-item user; it is an approach to system design that can enable additional characteristics in the end item.

Modular open architecture benefits programme directorate by using general set of principles to help address system complexity by breaking up complex systems into discrete pieces.
Primary benefits of Modular open architecture include:

1. Increased interoperability and incremental approach to capabilities

2. Facilitation of technology refresh/interchange

3. Reduced support and sustainment costs without sacrificing capability

4. Enhanced competition/innovation and reduced reliance on single-source vendors ie, Vendor Lock

5. Shortened programme acquisition timeline for fielding

6. Enhanced rapid and agile product development

7. Accelerated transition from science and technology into acquisition/training due to modular insertion

8. Increased ability and flexibility to retrofit/upgrade system elements for new/changing capability
9. Enhanced ability to create security structures within design to reduce operation risk

10. Reduced operator learning curves by using systems with similar functions and mode of operations to reduce costs

Top 10 Performance Parameters Include Determination of Objective/Threshold Value Assess if Target Met in System Demo

According to Engineering Capability Maturity Model Integration for Acquisition an appropriate requirements process involves establishing an agreed-upon set of requirements, ensuring traceability between requirements and work products, and assigning teams for any changes to the requirements in collaboration with stakeholders.

Likewise, an effective risk assessment process identifies potential problems before they occur, so that risk-handling activities may be planned and invoked, as needed, across the life of the project in order to mitigate the potential for adverse impacts.

Leading requirements assessment practices help organisations to better assign teams to execute the design, development, and delivery of systems within established cost and schedule time frames. These practices include :
1. Developing an understanding with the requirements providers of the meaning of the requirements

2. Obtaining commitment to requirements from project participants

3. Establishing Teams assess changes to requirements as they evolve during the project

4. Maintaining bidirectional traceability among requirements and work

5. Ensuring that project plans and work products remain aligned with requirements

6. Defining parameters used to assess/categorise source of risks and to control the risk team effort

7. Establishing and maintaining the strategy to be used for risk assessments

8. Evaluating and categorising each identified risk using defined risk categories and parameters, and determining its relative priority

9. Developing risk mitigation plans in accordance with the risk team strategy

10. Monitoring the status of each risk periodically and implementing the risk mitigation plan as appropriate.

Top 10 Contract Job Site Tasks Feature Capable Work Breakdown Service Structures Result from System Procurements

Task procedures and consistency of performance evaluations are issues to be resolved before solicitation release, or at least before contract award. After contract award, at each milestone point between programme procurement phases, Contract work orders provide framework for delineating multiple areas of responsibility to include/require attention include funding status, schedules, future contract performance & integrating total programme requirements.

1. Create and track buys with full-feature purchase order system

2. Build “parts list” for like-make/models as parts are charged out

3. Assess full-feature work orders with multiple operations/technicians

4. Transfer parts inventory between connected locations

5. Suspend repair scheduling for “out of service” models

6. Value inventory at average cost with user-defined fields

7. Respond in time to work order tasks via “reminders” feature

8. Import supplier “lists,” such as part numbers

9. Customise individual screens & add outside repair detail to history

10. Produce order queries for unique,specialised reports
　
Top 10 Equipment Readiness Information Application Questions for Product Support Decision Assign Directorate Capability Execution

　
Must enable communication between stakeholder through well-defined interfaces so Modular open architecture is broadly defined and inclusive of a variety of tools and practices.

1. How long have you been using the application to improve design efforts so information system processes are available & consistent?

2. When accessed how much time do you spend in application on efforts to make user support tech information timely & accurate?

3. Do you still need to make local reports with the application to reduce unnecessary duplication of information collection requirements generation?

4. Would you say the application cuts down time & effort to maintain, use & disseminate information?

5. What application features do you routinely use to improve personnel productivity by making use of communications updates between information units?

6. How often do you access application to achieve efficient use of automated information collection systems?

7. What reports do you routinely use to coordinate information policy/programmes with collection requirements definition efforts?

8. How are you using application during deployments to establish accountability for resources designated for assignment to information systems?

9. How would you rate use/access of application in field to foster information sharing & make compatible with systems from other Services?

10. Have you ever used application to brief from site to ensure information policies are consistent with changes in unit requirements?

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Top 50 Systems "Digital Twin" Engineering Work Include Readiness/Reliability Models Simulation Activity

5/20/2018

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Digital Twin Simulation in the form of virtual reality has now allowed some reliability/maintainability characteristics of a design to be "evaluated" before any model or prototype is even constructed.

Although not a total substitute for testing, virtual reality simulation can reduce the amount of time required by allowing some reliability aspects of the design to be verified without or with reduced maintainability demonstration and testing.

Digital Twin simulations have definite applications for designing reliable equipment. For example, based on Digital Twin design status updates, a virtual copy of the product can be "produced."

Maintainability engineers can then enter a virtual design space where maintenance can be "performed" on the product.

Accessibility of components, whether an item fits in an allocated space, and the approximate time required to perform specific maintenance actions all can be evaluated using Digital Twin Simulations.

Virtual copies of support equipment can be evaluated by "performing" maintenance activities with them. Digital Twin Simulation reliability updates could allow technicians to view virtual information panels "superimposed" using augmented reality techniques on the actual equipment.

In general, Digital Twin Simulations can be used by reliability engineers to assess degree can be reached in time, access, field of view, force structure posture and activity timing. In addition to designing for maintainability,
Digital Twin Simulations have many potential training applications. Maintenance and manufacturing procedures, especially procedures that are seldom performed or are difficult to teach using conventional approaches, can be taught using Digital Twin Simulatons.

Digital Twin Simulations could also be used to train individuals in performing difficult to anticipate procedures. For example, Infantry Troops can now "perform" operations without actually using any physical tools or a live operations.

As has been the case with previous new technologies, the possible uses of Digital Twin Simulations cannot be fully appreciated or anticipated. As virtual reality interest moves forward, the applications related to design for reliability will certainly increase in number and in fidelity
　
Equipment is out in the field, it’s out with the troops, they’re giving the feedback. The engineers developing the systems are there right with them, so they are using it and giving very good feedback.

They get it down, they give special operators a chance to work with the equipment. They touch it, they use it, and then we can quickly turn those things around.

Getting the input of users is extremely important, or you won’t have a reliable system that they’re going to use when it gets fielded.

It’s similar to a special operations model, which has been an inspiration in the effort to streamline acquisition of system reliability as whole.

Site Visit Executive job will be to focus on defining requirements as precisely and realistically as possible from the start and then to experiment to see what works before committing resources to reliability efforts

There are going to be trade-offs and all this and the reporting lines may change to make sure we get accurate optimisation of Digital Twin Simulations.

Everybody recognises we have reached a point of action for reconstituting readiness that we’ve got to just move forward with smart reliability models. it’s time to move from this industrial age system to a modernised system utilise Digital Twin Simulations.

1. The programme must use a digital model to develop depictions of the system to support all programme uses, including requirements assessments, architecture, design and cost trades; design evaluations; optimisations; system, subsystem, component, and subcomponent definition and integration; cost estimations; training aids and devices development; developmental and operational tests and sustainment.

2. Models and simulations must be used, to the greatest extent possible, in systems engineering and program/project risk management; cost and schedule planning; and providing critical capabilities to effectively address issues in areas including but not limited to interoperability, joint operations, and systems of systems across the entire acquisition life cycle.

3. The responsibility for planning and coordination programme use of models, simulations, tools, metrics, and the engineering job sites belongs to the programme administration; the performance of the actual tasks may be delegated to the programe systems engineer and other program staff as appropriate.

4. Programmes should identify and maintain model-centric technology, methodology/approach and usage preferably in a digital format e.g., digital system models, that integrate the authoritative technical metrics and artifacts generated by all stakeholders throughout the system life cycle. Unless impractical, the programme should develop the digital system models using standard model representations, methods, and underlying information structures.

5. The digital system models are a collaborative product of systems engineering and design engineering efforts. The program should construct the digital system modes by integrating metrics consumed and produced by the activities across and related to the programme.

6. The digital system models must include, but should not be limited to, the technical baseline, parametric descriptions, behaviour definitions, internal and external interfaces, form, structure, and cost. This information must be traced at a minimum from operational capabilities through requirements, design constructs, test, training, and sustainment. The programme should validate the digital system models baseline at appropriate technical milestones.

7. Systems engineers should use models to define, understand, evaluate, communicate, and indicate the project scope, and to maintain an authoritative source about the system. When captured digitally, the system model may be used to produce technical documentation and other artifacts to support programme decisions. It is expected that a properly managed, digitally based system model will be more accurate, consistent, and sharable.

8. Models, simulations, tools, methodology, and data employed in acquisition activities must have an established level of trust, and the programme must use the activities with an acknowledged level of risk appropriate to the application. The development of models, construction of simulations, and/or use of these assets to perform programme definition and development activities and Materiel Development Decision and requires collaboration among all project stakeholders and is led by the systems engineer.

9. The programme directorate must ensure sufficient training in the appropriate use of models, simulations, tools, data, and the engineering job site. The programme must identify metrics that show the link between training and the appropriate use of activities that result in benefits to the programme, especially in the areas of early identification of defects, cost avoidance, and risk reduction.

10. The programme should update the digital system models throughout the program life cycle and maintain configuration management i.e., version controls. These updates will provide continuity among all programme stakeholders, including the program model developers, simulation uses, and other engineering and programme administration activities.

Top 10 Evaluation Summary of Reliability Detection Models Predictions Included with Element Rationale

Reliability critical elements of the item extracted from the reliability modeling and reliability prediction effort must be listed and included in the summary to include conditions of high failure rate elements, over stressed parts i.e., exceed established parts rating criteria, and mission reliability single failure points. The detail tasks and methods for preparing reliability models and perfecting reliability predictions follow

The Basic Reliability model must consist of a reliability block diagram and an associated mathematical model. By definition, the Basic Reliability model is an all Series model which includes elements of the item intended solely ‘for redundancy and alternate modes of-operation.

The Mission Reliability model must consist of a reliability block diagram and an associated mathematical model. The Mission Reliability model must be constructed to depict the intended utilisation of elements to achieve mission success. Elements of the item intended for redundancy or alternate modes of operation ~must be modeled in a parallel configuration or similar construct appropriate to the mission phase and mission application.
　
1. Reliability Block Diagram

Reliability block .diagrams must be prepared to show interdependencies among all elements-- subsystems, equipments, etc.or functional groups of the item for each service use event. The purpose of the reliability block diagram is to show by individual shorthand the various series-parallel block combinations that result in item success. An understanding of mission definition, of item and service use profile is required to produce the reliability diagram.

2. Block Diagram Title

Each reliability block diagram must have a title including identification of the item, the mission identification or portion of the service use profile addressed, and a description of the mode of operation for which the prediction is to be performed.

3. Statement of Conditions

Each reliability block diagram must include a statement of conditions listing all constraints influencing the choice of block presentation, the reliability parameter or reliability variables utilised in the assessment, and the assumptions or simplifications utilised to develop the diagram.

4. Statement of Success

A statement of success must be defined in specific terms stating exactly what the calculated reliability represents for the items as diagramed and performing under the criteria presented in the statement of conditions.

5. Order of Diagram

The blocks in the diagram must follow a logical order which relates the sequence of events during the prescribed operation of the item.

6. Block Representation

The reliability block diagram must be drawn so each element or function employed in the item can be Identified. Each block of the reliability block diagram must represent one element of function contained in the item. All blocks of the reliability block diagram shall be configured in series, parallel, standby, or combinations thereof as appropriate.

7. Identification of Blocks.

Each block of the reliability block diagram shall be identified. Diagrams containing few blocks may have the full Identification written in the block. Diagrams containing many blocks shall use a consistent and logical code identification written for each block. The coding system shal1 be based upon the work breakdown structure work unit code numbering system or other similar uniform identification system that will permit clear traceability of the reliability block to its hardware or functional equivalent as defined in program documentation. The code must be identified in a separate listing.

8. Non-modeled Elements

Hardware or functional elements of the item which are not included in the reliability model must be identified in a separate listing utilising the coding system. Rationale for each element exclusion from the reliability model shall be provided.

9. Reliability Variable

Reliability variables shall be determined for each block and presented so association between the block and its variable is apparent. The reliability variable is a number-- time, cycles, events, etc. used to describe the duration of operation required by each block to perform its stated function. This variable must be used in calculating the reliability of the block.

10. Block Diagram Assumptions

Two types of assumptions shall be used in preparing reliability block diagrams:.technical and general. Technical assumptions may be different for each item and for each mode of operation. The technical assumptions shall be set forth under the statement of ‘conditions. The general assumptions are those applicable to all reliability block diagrams.

Top 10 Equipment Readiness Information for Product Support Item Decision Assign Reliable/Capability Models

While heavy military transport aircraft have very strict mission proﬁles, agile ﬁghter, trainer or attack type fleet usage variability aircraft are well known to experience substantial variability in their missions .

Once critical factors are identiﬁed in the aircraft design stage contributing to fatigue test performance, individual aircraft reliability tracking programmes are used to accumulate, so they cannot be tracked based on mission hours alone. So tracking program is necessary for agile combat type aircraft conducted with every the fatigue life status of each aircraft throughout its service life design, based on its own operational load spectrum

Amount of performance fatigue life consumed and the remaining life for each aircraft in the ﬂeet is assessed. One of the greatest beneﬁts of an individual aircraft tracking program is that calculated independently of other aircraft in the ﬂeet. Reliability Models based on individual design characteristics reveals loads monitoring can take place without a prior knowledge of the exact critical location.

Ideally, provided that wide spread in the rate of fatigue usage, sufﬁcient number of primary load carrying structures are routinely monitored, stresses at all critical locations hours on many aircraft. The fatigue accumulation rate is the individual aircraft fatigue damage values

Critical transfer function relating the monitored load are calculated using the standard location stresses. So change in the critical location an be accommodated through the design of transfer function to the new critical location. Some of the beneﬁts gained from the individual aircraft tracking program include:

1. Modeling of operations to stabilise the rate of fatigue life consumption,; life of an aircraft structure, knowledge of the actual load experienced by that structure is essential.

2. Drawing reliability comparison between design and usage spectra for each aircraft; with estimation of the fatigue life or damage status of major components on each aircraft based on loads monitoring in the primary structure of that aircraft and related to fatigue test results

3. Planning of maintenance action according to rate of fatigue damage accumulation for aircraft fleet reliability estimates, modiﬁcation of operations to stabilise the rate of fatigue life consumption, life of an aircraft structure, knowledge of the actual load experienced by that structure is essential.

4. Building an operational load reliability model in conjunction with ﬂight trials for application to a fatigue test and, where a safe-life may be stipulated, some aircraft are retired at a different number of ﬂight hours due to their to compare with early fatigue test metrics

5. Identifying the variability in response between aircraft calculated rate of fatigue damage accumulation being higher or lower than the reliability target rate because of operating ﬂeet under the same ﬂight conditions through assessment of mission severity, with prime factors driving individual aircraft tracking are the unique combination point-in-the-sky affects

6. Gaining better understanding of the loading scenario experienced by different aircraft in the ﬂeet and the availability of a good on-board reliability monitoring in conjunction with ﬂight trials metrics

7. Observing difﬁculties introduced by assumption that, if the ﬂeet average load factor exceeding curves matched that and structural redundancy at vertical tails of the design spectrum, the aircraft could be: operated until the design life, but operators of modern aircraft is likely to have a different systems

8. Designing future aircraft to be smart buyers in the acquisition of new aircraft for the same role; and usage spectrum to the design spectrum. The root bending moment of the component is the primary factor to assess.

9. Defining ﬂight trials metrics parameters to be measured on new aircraft or new monitor and ﬂeet-wide average load systems for the same aircraft to allow the more accurate calculation of critical components reliability

10. Seeking to maintain fleet structural integrity based on its reliability and identify operational overloads making individual aircraft tracking programme necessary. Test life extension must be substantiated by further fatigue tests to determine the next critical location and required repairs
　
　
Top 10 Mission Reliability Model Categories Standards Include Definition of Equipment Item Related to Reliability.

For Basic Reliability modeling; the item definition is simple - all equipments comprising the item are modeled in series. “All” equipments includes any equipments provided solely for redundancy or for alternate nodes of operation.

However, for Mission Reliability modeling, the item reliability model and mission success definition can become elusive problams especially for complex multimodal systems incorporating redundancies and alternate modes of operation.
In item definition, emphasis is placed on properly specifying reliability within the context of all other pressing requirements and restraints that comprise a functioning Item. A proper definition is important in order to establish meaningful requirements and goals

An adequate item definition aids in determining when the item is being used as intended, when it sees its anticipated environment, when its configuration has been changed beyond its original concept, as well as when it is performing its specified function.

Item reliability is defined as the probability of performing a specified function or mission under specified conditions for a specified time.

1. New item processed through a defense technical review activity for tasking and authorised for procurement that cannot be replaced with an existing item.

2. New item authorised for tasking that is contained in a new standard or revised superseding specification or standard that replaces prior items. This item will not be assigned stock number or an item standardisation code until a requirement for the item is generated.

3. Item authorised for tasking that has been included in standardisation an item reduction study but an intelligent decision could not be made due to lack of technical information.

4. New item processed through a defense technical review activity for tasking and authorised for standardisation but an intelligent decision could not be made due to lack of technical metrics.

5. Item no longer authorised for tasking which has been authorised for replaced by a new item as the result of new or revised standards superseding assigned specifications or standards

6. Item authorised for tasking which was initially identified for standardisation the result of a formal item reduction study and which was accepted as a replacement for one or more items not authorised.

7. Item authorised for tasking which as been included in an for standards item reduction study and which initially does not replace an item not authorised.

8. Item, which as a result of a formal item reduction study, is for procurement accepted as not authorised for tasking

9. Item authorised for tasking that has not yet been for procurement subject to item standardisation.

10. Item authorised for tasking that is in a specific procurement supply classification class or item name grouping consisting primarily of items which are one of a kind and, therefore, little or no potential exists for elimination of items through formal item reduction studies.
　
　
Top 10 Condition State Models Calculate Materiel Reliability Function When Service Life Estimates Not Directly Observable

At each observation moment to build reliability model, an indicator of the underlying unobservable condition state assessed, and the monitoring information is collected. The observation process is due to a condition monitoring system where the obtained information is not perfect so observation process doesn't directly reveal the exact condition state.

To match value of indications to the unobservable degradation state, a relationship between them is given by an observation reliability model. Time-dependent proportional condition state is considered to model equipment failure rate. Reliability Model Limitations include the problem of imperfect observations, and the problem of taking into account the condition state history of observations.

1. New, repaired or reconditioned materiel serviceable issue to all customers without limitation or restriction.

2. Serviceably and issued for its intended purpose but restricted to issue for training use only

3. Serviceable materiel requires or designated for test, alteration, modification, conversion or disassembly not to include items require inspection or tested immediately prior to use

4. Materiel involves only limited expense or effort to restore to serviceable condition accomplished in storage activity where materiel is located

5. Economically repairable materiel requires rework, repair, overhaul or reconditioning

6. Materiel requiring additional parts or components to complete end item prior to issue

7. Materiel determined to be unserviceable and uneconomical to repair

8. Materiel in stock suspended from issue pending condition classification where true condition is not known

9. Materiel returned from customers/users and awaiting condition classification

10. Materiel identified on item condition control record but turned over to service site
　

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Top 10 Factors to Consider for Setting Up Logistics System with Centralised Control Decentralised Task Execution

5/13/2018

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New Logistics Simulations Tools could resolve some issues Marines face in supply missions by combining the planning skills of expert Troops with artificial intelligence, robotics and metrics tracking. How do we dominate and operate effectively with decentralised execution in a contested information scenario?

Maybe if we just change a little bit of how we train and organise, we can dramatically impact the way we execute. We may have to spread out to greater distances with smaller units. Then you have to move supplies to the point of field requirement in a contested scenario with contested networks. Now you are facing a whole new set of problems.

Taskers are directives or action items at the executive level that require responses. Logistics Simulation gives users a common place to store and execute taskers so that at any given time, anybody involved in the task knows what’s going on with it.

Our Tool has led to an increase in Troop productivity and streamlined business process showing decreases in the average number of days that a tasker is late, average time it takes to complete a tasker and decrease in missed due dates.

This process provides a framework that MEU commanders can use to develop mission plans and understand where equipment shortfalls are likely. The process consists of simple steps that translate mission requirements into tasks, subtasks, and military activities, each of which is linked directly to the types of equipment needed for completion. It also highlights key parameters that may affect the types of equipment needed or the execution of key tasks.

Those numbers exceed expectations. Presently, we’re above the average metrics that we were looking for, so it’s a positive outcome so far. Another benefit from the tool has been better accountability since it can assign tasks to individuals or teams and allows review and approval before the work is released.

The tool holds ownership from leadership all the way down to accountability of taskers, making sure that taskers are completed in the right time frame. A lot of times, taskers get pushed down. They get lost in the shuffle as we do business, but with the Tool the tasker can’t get lost. We have accountability of where the tasker goes, and we know when it should be accomplished. That helps use engage in how to do business the right way.

For this report, the equipment list was provided by one of the MEUs we visited. This has the advantage of providing a realistic equipment set. However, as we explain later, the application we have developed can accommodate equipment lists that are significantly different, larger, and smaller than what we use as a baseline.

The approach used in this report is for the user to utilise the Tool to facilitate the development of planning factors and get better at assigning equipment to tasks.

The equipment available to perform the tasks associated with the missions consists of the equipment onboard with the unit and possibly additional, remotely located equipment.

We don’t really anticipate any major adjustments to the Tool because right now it’s currently doing what it’s designed to do: make sure taskers get accomplished in the timely fashion and pushing Marines away from the dinosaur age to … this new age of how we do business.

What equipment is available to Marines to accomplish mission tasks and subtasks? A diverse set of factors affect the types of equipment carried into theatre, including not only space available but also risk trade-offs made by commanders and expectations about the deployment risks.

Inputs to the system consist of an equipment list assigned to unit, the tasks identified through the mission deconstruction process, the measures and metrics used to define equipment capabilities, and the set of linkages between tasks and equipment.

What measures and metrics should be used to assess the capability of selected equipment? The loading list provided the set of available equipment. We then used equipment updates and sponsor input to define the capabilities of each piece of equipment in performing designated tasks. This information is displayed to the user when a piece of equipment is selected.

We identified the measures and metrics, or “planning factors,” needed to assess the capability of each piece of equipment in the loading list. In our initial construction of the Tool, we identified equipment substitution efforts might accomplish a task.

Equipment list was provided by one of the installations we visited. This has the advantage of providing a realistic equipment set. But the application can accommodate equipment lists that are significantly different, larger, and smaller than what we use as a baseline.

Centralised control and decentralised execution of tasks are ideals sought in logistics support operations. If achieved, support will be responsive, economical, and flexible. Site Visit Executive has determined good balance between centralisation and decentralisation of logistics operation functions is usually difficult to achieve.

Control may suffer because it is fragmented, or support may fall short because services and equipment are too concentrated. Consequently, Visiting Executive must use judgment and experience to achieve optimal mix of centralised control and decentralised execution based on specific circumstances popping up in fluid mission tasks.

Centralised control is most effective at the strategic levels, drawing on existing support infrastructure, established procedures established by Site Visit Executive & stability of missions in theatre.

The degree of centralisation varies at the operational level since forces can be fragmented, sometimes over great distances, and operations often take place under problematic expeditionary conditions. At the tactical level, the degree of centralisation is determined by mission/concept of operations-- factors that often override purely logistical considerations.

Site Visit Executive has submitted lots of written Principles of Supply Line Logistics to include detailed universal constants applicable to all aspects of logistics including responsiveness, simplicity, flexibility, economy, attainability, sustainability & survivability.

In addition to these principles, many other logistics considerations exist to keep Site Visit Executive in Business so installations of any size can use supply line routing application to apply smart techniques to deal with disparate situational connections realised when addressing supplier group contacts.

These considerations will not always dictate a specific course of action, but will assist Site Visit Executive in maximising effectiveness & efficiency of logistics operations if used smartly.

Site Visit Executive can first look at broad readiness, but can also look at readiness levels of subordinate units to provide the ability to control, distribute, and replenish equipment and supplies in assigned areas of operation, to receive supply support from and provide supply support to other services.

Readiness Terms are used in different contexts/processes. Operational gaps in systems used by Marine Units must be closed so exchange is seamless.

Capability to link information as it is processed by Units must be built.

Aggregated information provided to Commanders must be traced/linked to operational systems used to rollup information. But no Marine Site Executive has yet stood up to identify functions spanning across process and write terms required to support processes

If Site Visit Executive has better overview of equipment status, resources will be allocated/pooled more efficiently so greatest potential for operational readiness is realised.

Information from readiness systems is required to determine number of pieces of equipment available for deployment. No Site Executive has created an easy way to link equipment information available from readiness and Services systems.

Current readiness systems only include commander’s best estimate for equipment status. Estimates have traditionally been utilised usually for overall equipment assigned to the unit and not individual pieces of equipment.

Military Services use systems to maintain records of equipment under service, but records do not include any information about what units it is assigned to.

Marine Corps leadership utilise unreliable information when making decisions about major equipment end items and spare parts b/c Information contained in the Marine Corps legacy logistics and supply information systems is significantly inconsistent & inaccurate.

We believe this occurs because Marine Corps guidance does not sufficiently define the respective roles and responsibilities for Marine Corps logistics information directorates.

So this results in confusion among personnel in various Marine Corps commands about who is responsible for the accuracy of different elements contained in the systems.

Inconsistencies and inaccuracies also occurred, in part, because Marine Corps guidance lacks adequate operating procedures about logistics information systems. So field-level Troops are not aware of, or are not in compliance with, current operation procedures and logistics rules employed by the directorate.

We found the Marine Corps has insufficient assurance that most important information is transitioning to Global Combat Support Systems
　
When first standing up Logistics Directorate, Site Visit Executive usually creates a centralised organisational structure. The authority in such a structure is top-down, which makes it easy for operational headquarters to make important decisions and keep tight control over all aspects of the organisation.

As operations grow, it’s not uncommon for Site Visit Executive to gradually transition into a more decentralised structure. Here, decision-making authority trickles down to Troops who are no longer dependent on “the boss” to make all the decisions and dictate direction for every area of the organisation.

In decentralised system, more layers of teams are added to hierarchy, which gets more Troops involved in helping set strategic direction— but also can add to the complexity of decision making.

So what is the stage of mission development is a big factor in determining which type of organisational structure is best. Factors include the makeup of your Troop base, the strengths and weaknesses of your administrative team, and the best practices followed by other Units In each of the Services, among other factors

The type of organisational structure utilised — whether centralised or decentralised — is important because it forms the basic framework to achieve mission success and how decisions will be made. Following are a few common characteristics of centralised and decentralised organisations, as well as some of the advantages and drawbacks of each:

1. Top-down authority in centralised structure establishes a specific chain of command, with Site Visit Executive making all the key decisions with little or no input from rank-and-file Troops

2. Centralisation consolidates decision-making authority, goals and objectives with uniform across the organiation and standard sets of policies and procedures followed by all Troops can reduce costs and ensure Service-wide consistency

3. Multiple individuals, including rank-and-file can make important decisions and set policies and procedures that guide how the mission s run in decentralised operations

4. Team structure is created throughout the organisation in decentralised system results in a broader range of input that can generate more solutions and ideas.

5. Troops at all levels of the organisation are empowered to make decisions, often with little or no input from higher-ups in decentralised system

6. Decision-making may be slow in centralised operations and disrupt the flow of work order tasks momentum

7. Troops may feel less motivated to do their best work in centralised system if they feel they don’t have a voice for sharing their ideas on how improve outcomes

8. Executives in decentralisation system will have less control and need to rely more on personell beneath them to carry out the mission and goals of the organisation. This process of “letting go” may be difficult for Site Visit Executive.

9. Decentralistation may promote unnecessary competition among those who have previously worked together under a centralised structure, but are now working in different departments or divisions.

10. Decentralised structure sometimes doesn’t work well in during early stages of missions development that have not yet built a solid infrastructure

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Top 10 Multi-Agent Model Simulations of Field Deployed Troops Decision Behaviour in Mobile Situations

5/7/2018

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The Multi-agent model includes a “Digital Twin” simulation of every foxhole in the area affected as well as every road, communication network, etc. And the scenario is populated with more than One Million Agents—a synthetic population statistically identical to the real population of the affected area in factors such Troop equipment.

Each agent is an autonomous subroutine that responds in reasonably human ways to other agents and the evolving disaster by switching among multiple modes of behaviour—for example, flight, and efforts to find other Troops

The point of such models is to avoid describing troop missions from the top down with fixed equations, as is traditionally done in such fields as economics. Instead, outcomes such as vehicle crash through the interactions of many individuals, leading to a real-world spontaneous behaviour that is otherwise hard to simulate.

That kind of detail is exactly what commanders need, The model can warn system fail point X might well lead to a surprise traffic jam at point Y. If commanders decide to deploy mobile dispatch centre in the early hours of the crisis to restore communications, the model can tell them whether more vehicles will take to the roads, or fewer.
Agent-based models are how you get all these pieces sorted out and look at the interactions.

The downside is that models tend to be big—each of the model's initial runs kept large microprocessor computing cluster busy for couple of days—forcing the agents to be relatively simple-minded.

"There's a fundamental trade-off between the complexity of individual agents and the size of the simulation."

But computers keep getting bigger and more powerful, as do the data sets used to populate and calibrate the models. More and more decision-makers are taking agent-based models seriously. "They're the most flexible and detailed models out there,"which makes them by far the most effective in understanding and directing policy."

One early success was to simulate troop interactions on ordinary desktop computers, they pared agent-based modeling down to its essence: a set of simple agents that moved around a grid in search of resources that was abundant in some places and scarce in others. Though simple, the model gave rise to surprisingly complex group behaviours such as combat, and troop segregation.

Another milestone has been when Operational Simulation System, an agent-based traffic model developed. Unlike traditional traffic models, which used equations to describe moving vehicles en masse as fluid, each vehicle and driver was modeled as an agent moving through a contingency theatre road network.

The simulation included a realistic mix of combat vehicles, driven by troops with a realistic mix of abilities, and destinations. When applied to the road networks in actual combat theatre, Simulations did better than traditional models at predicting traffic jams one reason agent-based models are now a standard tool in planning of mobile operations.

The model also incorporates data on how troops typically move between stations. The result is a model that not only predicts how bad a situation could get—something commanders could determine from equations—but also suggests where the worst hot spots might be.

Given how much is at stake in those simulations, users always want to know why they should trust the results. How can they be sure the model output has anything to do with real-world scenarios—especially in cases such as mission disasters, which have no empirical data to go on?

That question has several answers. First, users shouldn't expect the models to make specific predictions about, say, a mission crash in the future. Instead, most modelers accommodate the inevitable uncertainties by averaging over many runs of each scenario and displaying a likely range of outcomes, allowing planners to use the model as a test bed to game out the consequences of taking action A, B, or X.

Modelers should not just slap the model together and see whether the final results make sense. Instead, they should validate the model as they build it, looking at each piece as they slot it in—how troops get to and from point of action, for example—and matching it to real-world data sources. "At every step, there is data that you're calibrating to,"

Modelers should also try to calibrate the agents behaviors by using studies of troop behaviour. Doing so can be tricky—troops are complicated—but in crisis situations, modeling behaviour becomes easier because it tends to be instinctive. The model, for example, gets by with built-in rules that cause the agents to shift back and forth among just a few behaviours, such as shelter-seeking, evacuating or attack.

Even so, field studies point to crucial finer points, "When a mission falls apart, "we find that troops are more likely to consider twice, weighing possibility of being without support from others even with priority of the crisis itself."

Likewise when under fire, commanders tend to assume that when the alarm sounds, troops will immediately file toward the exits in an orderly way. But just watch the next time your unit has a fire drill. Troops don't evacuate without first talking to others"—and if need be, collecting friendly forces.

The evidence also suggests that blind, unthinking panic is rare. In an agent-based model, model developers tried to reproduce what happened in a past incident where the unit came under fire. Some in the group jammed together so tightly that no one could move, and casualties were taken. Between participants accounts, the team had good data on the behaviour, and their relationships to others.

And when we incorporated those relationships into the model, the runs most consistent with the actual incident under fire involved almost no panic at all. "We found that Troops were trying to get out with those in the unit that shared a similar assignment and proximity to the fight.

Results from the model can sometimes be counterintuitive. For example, the model suggests that right after the strike, commanders should expect to see some troops rushing toward ground zero, jamming the roads in a frantic effort to pick up their comrades. The model also points to a good way to reduce chaos: to quickly restore communications service, so commanders can verity the safety of troops.

If agent-based modelers have a top priority, it's to make the simulations easier to build, run, and use—not least because that would make them more accessible to real-world decision-makers.

Decision makers access a playbook: network status updates containing digital versions of every large operational theatre, with pre-computed models of just about every potential hazard. "Then, if something actually happens, like an explosion commanders could pick model being closest match and do near–real-time calculation for things like the optimal mix of engagement and evacuation.

It is "agent-based modeling as a service." Teams are developing and testing a networked tool that lets commanders to build disaster simulations and do what-if assessments on their own, without having to hire programmers. With just a few clicks, users can specify key variables such as the region of interest, and the type of attack. Then, using the tool's built-in maps and graphs, commanders can watch the simulation unfold and see the effect of their proposed response protocols.

Despite being specialised for troop movement in and out of theatre, the tool's underlying geographic models and populations are general, and they can be applied to other kinds of disasters. Ultimately, the goals are to build such models into services that are individualised to each unit and situation.

So it won't just be decision-makers far away from the fight using those systems. It will be you. "It will be as routine as Google Maps.

Advances of the last decades in information and communication technologies have triggered fast developments in a large number of application areas involving cooperation among networked agent entities.

Network tech advances have enabled implementation of number of predicted models that were just waiting for the proper conditions, and on the other hand they motivated the development of new concepts.

One of the main underlying trends in Training development is the focus on agent models, protocols, and mechanisms to support the collaboration of pre-existing entities in distributed real-world scenarios, be it among organisations, among Troops, or among Troops and organisations.

Strong reliance on standards will contribute to facilitate the interfacing of existing applications with the virtual infrastructure, but unfortunately not all classes of information that need to be exchanged among virtual agents are covered by existing standards.

Initiatives of application agent groups contribute to facilitate this process. In general, it is necessary to develop some interface/mapping layer, at each enterprise, to adequately have this enterprise interacting with virtual infrastructure.

It is also noticed that most legacy applications were designed for a enterprise-centered local operation and to be operated by agents. In order to have these applications supplying information to or consuming information from the virtual network, it is clearly necessary to extend their functionality.

Interoperability among enterprise applications represents a major challenge for supporting the rapid formation of virtual scenarios, in response to new operational opportunities. On the other hand it is important to have in mind that each enterprise has its own way of doing business.

Furthermore the level of information sharing among virtual agents is likely to either change of the trust level among partners or with adjustments to configuration in time. Therefore, flexible virtual coordination and information visibility rights definition mechanisms are needed, in order to support both the autonomy and change order properties in behaviour of virtual agents.
　
The first step is to understand and document user requirements and Constraints for system capability so process can meet requirements availability/ reliability parameters must be explained and guide trade-off studies of mission capability and operational support, defining baseline against which the new system will be measured.
So performance factors need to be matched up with user needs into clearly defined system parameters and allocate/ integrate parameters to relevant disciplines needed to realise success.

Systems engineering attempts to optimise effectiveness and affordability as the capability is created. The systems approach makes sure the question What are the user needs and constraints? is answered before designing the answer.

The top-level programme plan for achieving required available/reliable is executed in manner to ensure requirements are achievable. Through understanding user needs and constraints, new capabilities begin to be defined.

Must establish the case for a materiel approach to resolve gaps in capability. The primary focus is to acquire quality products balancing process of satisfying user needs while improving mission capability and operational support, also adhering to scheduling constraints and justifiable costs.

During capability assessments, time and resources need to be set aside to measure and characterise current operational experience, organise metrics and supply line performance to reach conclusions about the causes of shortfalls.

It is also imperative to understand subsystem design complexity and influence on availability/reliability. Capabilities-based approach leverages the expertise of all service directorate activities defining new capabilities.

Primary focus is to ensure that joint force is properly equipped and supported to perform across disciplines to identify improvements to existing capabilities and create new warfighting capabilities.

Process defines needed capabilities through characterisation of doctrine, organisation, training, materiel, leadership, and Troop units. Availability/reliability levels are defined within this framework, principally in the category of materiel.

So Goal is to inform and share information among decision makers tasked with use and system support. Information to be shared includes user requirements, and how system will be used or potentially miss targets.

Key to any assessments is description of use/support location, constraints on what support is available for system, what information will be available to decision makers, and how that information will be verified.

Operation commanders typically have relatively clear ideas about the planning factors for specific pieces of equipment. However, Troops usually do not have an updated set of planning factors that it uses to develop mission plans or to guide what it brings aboard its ships.

This lack of training on character of planning factors led us to rely more heavily on the users of the application. We consulted equipment training tasks that provided details on the capabilities of pieces of equipment, such as payload, maximum speed, or lift capacity, and the application makes this information available to the user tasked with selection of equipment to accomplish required tasks.

Site Visit Executive Found Nothing but Problems During Simulation Training Exercises. The “problem” part of the Fleet Deployment Problem is inspired by several sources.

In some cases, we identified “problems” during our war games. Played at the operational level, [OpFor] team. Most of the time, each game identifies several key operational enablers employed by our forces.

With the help of our team, we capture that key moment—friendly force disposition, enemy situation, mission, and even the losses suffered on both sides—and use it as a point of departure both for our input to the Chief Integrated Agenda and for our Fleet Problems.

In other cases, as we considered how our ConOps would play out in reality, it became apparent there were warfighting tasks that were critical to success that we could not execute with confidence.

This gap was not because the unit did not practice these tasks individually—the efficiency of the plan ensured they could—but because we as a force never practiced them together, in combination with multiple tasks, against a free-playing, informed, and representative Red Team.

In one case, during an exercise planning session, we discussed a critical operational tactic that is used routinely in exercises and assumed to be executable by the fleet.

In the course of the brief, someone piped up and said, “Sir, you know we can’t actually do that.” In the silence that followed we could see some in the room thought we could, while others were nodding in agreement that we could not. With that, we had the scenario for a Fleet Problem with the mandate to “go find out.”

We learned that the doctrine and assumptions in one area had removed the capability to implement key tactics in another. Having never performed the task together in theatre, the disconnect never was identified clearly. It was not until we tried to execute under realistic, true free-play conditions that we discovered the problem’s causal factors, leading to the ability to apply solutions.

In discussion with the Troops we frame the problem that is given to a unit or formation. For example, it is critical that we be able to operate carrier strike groups [CSGs] in areas of significant submarine threat.

Our traditional approach to this challenge would be to create an antisubmarine warfare [ASW] exercise, tasking submarines to act as targets within a set geographic area.

In a Fleet Problem, we instead would task the CSG to conduct a combat mission-- conduct strikes on, giving it maximum flexibility in timing and mechanism. We then would create scenarios rich in submarine threats.

The CSG’s mission would not be ASW, but rather conducting a core combat strike mission in support of the joint fight in a robust submarine threat scenario.

Teaming the submarine threat is the means to the end —strike. If you destroyed all enemy submarines and lost no friendly units but were unable to execute the mission assigned—strike—then Blue loses and Red wins. How the CSG commander manages that threat to accomplish the mission is not prescribed.

Speed and manoeuvre? Go for it. Aggressive surface ASW? Great. Will the escorts sweep ahead or stay near the CSG? Air assets? Of course. How is that coordination going?

“Task success equals mission success” may hold true in training scenarios as long as Red is constrained. But in our experience, rarely in the real world does the sum of the tasks successfully completed equal mission success to note that there is no experimentation in the usual sense in Fleet Problems.

We are not notionally employing systems and weapons that are not already deployed in the fleet. Each unit attacks the problem using what it has physically on hand today. So commander developing and executing a plan must be based on our warfighting intent rather than ticking off a discrete schedule of individual training objectives.

The biggest challenge stems from the combinatorial size of the problem. There are several dozen organisations that team up to administer requirements and provision of tactical training, schoolhouses, resource sponsors, as well as a group of different Training status updates to specify policy for agent modeling and simulation and an unknown number of simulators.

Beyond the basic phase of training, training requirements for ships are only minimally articulated. Each ship must complete a set of training exercises tailored to counter deficiencies of the ship in question.

These exercises are selected and planned by a number of different teams. In the intermediate and advanced phases of training, there is little consistency in the choice of exercises or the requirements that must be met, and, in all phases of the operation several different teams evaluate the success of training.

Training requirements and standards are often too general or inconsistent for assessing readiness, further complicating the problem of determining how agent-based simulation must best be used.

Early directives have authorised DoD to use simulators to make training more effective and to help maintain military readiness. Agent-based training simulators permit:

1. Training impractical if done with actual systems or equipment

2. Concentrated practice in selected normal and emergency actions

3. Training of operators to address possible equipment faults

4. Training of maintainers to diagnose equipment failure

5. Increases in proficiency despite shortages of equipment

6. Improvements in abilities even with reduced amount of operational space

7. Authorised availability of training time for operations

8. More access to testing/training ranges

9. Control of training costs over all phases of service life

10. Reduction of systems required in maintenance training.

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Top 10 Benefits of On-Demand Prototype Innovation to Readiness Programmes Job Site Shop Build Capacity

4/26/2018

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Establishing new and improved levels of Navy readiness now and into the future requires creation of schedule-driven workload strategy directly linked to the Navy Sustainable Readiness Model. This approach ensures Navy prototype capabilities are focused on meeting its highest readiness priorities.

Valuable resources must be optimised at the enterprise-level in charge of new prototypes to make workload predictable and stable while providing a mechanism to continually evaluate and assess risk to the operating force.
Navy is as dependent on industry capabilities and capacity to produce viable prototypes. We know from hard experience that workload to capacity mismatch creates delays in prototype completion, increasing costs and reducing time for training and operations. As we look to the future, we see the potential for these conditions to exist.

Advance Construction has benefit of enabling early prototype exercises of build contractor and supplier manufacturing and materiel ordering, thereby strengthening select areas of the supplier industrial base.

Prototype programmes must initiate procurement of numerous long lead time components in support of manufacturing and assembly plan. These component orders will not only de-risk the build schedule but will also allow critical suppliers to begin their increase in materiel ordering and manufacturing capacity earlier than otherwise would be possible.

Capability and capacity of key vendors to provide quality material on-time is crucial for meeting Navy Fleet enterprise construction goals. The industrial base can support prototype challenge with improvements at the prime builders and suppliers in the areas of workload stability, facilities, and recruitment and retention of skilled resources.

The Navy and construction contractors have jointly established action plans with each of the critical suppliers in need of improvement. In many cases, those plans require that the Job Sites invest in new prototype facilities and increase the expertise of the workforce. The Navy will work closely with the builders and suppliers to reduce risk.

I. Prototype Job shops aren’t what they used to be.

Manufacturing was once a simple business: Training in machining and metalworking—sometimes on the same equipment they learned on years earlier. Though this process may have been complicated by technological advancements, if you needed help or advice it was likely sitting across from you at the mess hall table.

There is no doubt that the pace of change is accelerating. If you’re having a hard time believing such a claim, just take a moment to reflect on how often you got a new phone over the last few decades. This makes it much more difficult to maintain the old model of passing down knowledge from one generation to the next. Compounding this difficulty is the fact that the manufacturing sector itself is changing, with many companies switching to a small-batch, on-demand prototype model.

“It’s no longer enough for you, as a manufacturing company, to get one large order for millions of parts and run that order for the next couple of months. “With on-demand prototype manufacturing, you need to be able to take on hundreds or thousands of different orders.

You need to be flexible, but you also need streamlined processes for your customers to place their orders, otherwise you’ll be overwhelmed and lose your margin. how can you leverage it to meet the changing requirements of DoD?

II. On-Demand Prototype Manufacturing Explained

As with the on-demand prototype services we know generally, on-demand prototype manufacturing is all about getting exactly what you need, right when you need it. This model requires a fundamental shift in the way we think of the industry as a whole.

“An on-demand prototype production network is one where parts get manufactured as needed and in small quantities, “so it’s not like the mass production that we have today, which tends to have long planning cycles. With an on-demand prototype network, a client could order even just one part, but still get exactly that from the supplier right away.”

Smaller production volumes are a consequence of an as-needed approach, but there’s another factor that’s driving this trend toward on-demand prototype manufacturing.

Custom Prototypes is the watchword of the 21st Century, and custom goods—by definition—cannot be mass produced.

“In the end, “if you want mass customs, you can only do that at a very basic level without on-demand prototype production. You can offer your customers a few different setups for a car, for example, and call that ‘custom’ but it’s not true custom in the sense of making an impact on the performance. If my options are between choosing a blue or a black car, that’s not really custom.”

Between these trends of on-demand prototype manufacturing, one technology in particular stands out: 3D printing. “With 3D printing, you get the custom for free. As long as you can print the object, it doesn’t matter how complex it is or how different it is from your next print. If you want to use traditional manufacturing methods, then you have to change your tooling and systems between jobs.

So, in that case your costs go up a lot, but with 3D printing they stay pretty flat.”

To sum up: producing custom goods requires producing at lower volumes, which is where additive and on-demand manufacturing excel, but this also presents a problem. The challenge is producing custom goods at low volumes efficiently without making your production costs explode.”

III. Advantages of On-Demand Prototype Manufacturing

Accessing on-demand prototype production networks offer the solution to the challenge.

“You need access to machine capacities to deal with hundreds or thousands of orders. “Ideally, you’ll be able to serve a wide variety of clients, which means having many different materials available and lots of different production types. Of course, there are lot sizes of one, but on-demand prototype can also involve lot sizes in the hundreds or thousands.

In those cases, you want to be flexible enough to be able to outsource the production to partners in your on-demand prototype network. So, you can still accept the order from your client, but it doesn’t depend on just the resources you have available, since you can use your network to absorb the extra capacity demand.”

This goes back to the trend for manufacturing to become less centralised and more distributed: the production capacity of any one job shop is less important than that of the entire network, just like the Internet. Beyond increasing your production capacity, being part of an on-demand prototype network also opens up the types of production capabilities you can offer.

“If you want to use additive manufacturing to make high-quality parts, then you don’t want to use one machine with multiple materials. “Of course, each industrial-quality machine is quite expensive, so if you want to be able to offer a wide variety of materials, you’re better off working with a couple of partners and reselling their capacity than buying the machines yourself.”

IV. Roadblocks to On-Demand Prototype Manufacturing

Between increasing your production capacity and enabling access to additional 3D printing processes that you wouldn’t otherwise have, the benefits of on-demand prototype manufacturing are clear. So, why isn’t everyone adopting this new model?

Well, for one thing, setting up an on-demand prototype network all by yourself—or even with a few partners—is difficult. However, by using platforms, the task becomes considerably simpler.

“We can quickly establish an on-demand prototype network from scratch since we already have a large supplier network. So if you’re a new company and you want to participate, you can step into that already existing network. If you already have some partners, we’re happy to integrate them as well, and continue to extend the network that way. In both cases, we’re using our growing user-base to build and strengthen these networks.”

We offer platforms to help manufacturers join on-demand prototype networks and access to suppliers. Our application solution allows print shops to join an on-demand prototype network, adding their capacities to it and enabling them to selling those capacities via their own networked shop.

“We basically connect the different network shops in the background to establish the networks. Our Enterprise solution gives users access to the on-demand prototype suppliers— as well as the ability to compare their internal capacities with those of the companies on the network.

Once you have your network in place, you‘re ready to consider our challenge in depth. The transition from producing many parts from a few orders to producing a few parts from many orders isn’t easy, especially when it comes to quoting.

“It’s definitely one of the biggest roadblocks right now. “Even if you’re fast, it usually takes significant block of time to prepare a quotation for an order. There’s also a lot of ‘communication “ping-pong” at the beginning: someone sends a request, you check if the part is printable, it’s not, so you request changes back and forth, and it just goes on like that.”

Fortunately, you can avoid all that communication “ping-pong” by automating your quotations and printability checks. Our Enterprise Platform is designed to do just that. In addition to giving you direct access to our network of additive manufacturing suppliers, the platform can also evaluate models for pricing and printability, include side-by-side comparisons of internal 3D printers with those in your on-demand prototypes network.

Given the extent to which 3D printing plays a role in on-demand prototype manufacturing, determining which parts would benefit from being additive manufactured is crucial to running a successful on-demand prototype job shop. For this reason, a lack of experience or knowledge of 3D printing can be another major stumbling block.

However, with our platform, that knowledge and experience doesn’t have to come from in house.

“We have customers who have a lot of experience with 3D printing and know exactly what they want, but we also have customers who come to us and basically say, ‘Hey, we heard about 3D printing and we don’t want to miss out on it. What should we do?’ These are the guys who rely on our supplier network and who may not even have a single printer in their facility.

V. On-Demand Prototypes & The Future of Manufacturing

Whether you’re a production supplier or huge organisation like DoD, keeping up with the pace of change is key to staying competitive. Disruptive new technologies are emerging and constantly changing within the lifetime of a single prototype generation, making it impossible to rely solely on the knowledge and the experience of our predecessors. But our platforms are now providing the tools to begin on-demand prototype manufacturing without large upfront investments.

1. Prototyping effort benefits were worth the cost, provided a positive return on business case investment include customer needs are valid and can best be met with advancement of chosen concept to be produced with existing resources, such as time, money, and available technology.

2. Prototyping provided programmes with information on technology maturity, feasibility of the design concepts, potential costs, and on achievement of planned performance requirements assist in injecting realism into business cases.

3. Prototyping demonstrated key technologies or proposed design solutions to determine if riskier, cutting edge design was feasible. Without prototyping, programmes would not have had sufficient information to be confident in riskier option-- contractor would not have proposed it without opportunity to provide functional demo.

4. Prototyping informed programmes understanding of prices to validate business case cost estimates. During prototyping process, contractors select vendors, ensure productive communications with suppliers, purchase materiel, and build full system version or parts of the system to provide information on potential costs.

5. Prototyping increased cost information available to programmes leading to cost reductions and competitive prototyping incentivised contractors to determine cost drivers in order to be more competitive in next phase.

6. Prototyping made programmes better understand requirements to make performance trade-offs meeting cost targets.for example to determine if different versions of system were best suited to meet unique requirements.

7. Prototyping provided programmes means to improve system performance, for example, collect information support operational success during prototype testing set stage to improve target classification and identify potential reliability issues early in process.

8. Prototyping changed perception of subsystem materiel utility based on information about wear/tear during prototype testing-- prototypes served as test assets during system project milestones or used to continue demo efforts.

9. Prototyping approaches to competition generated additional benefits to enable more favourable business terms using competition to result in service life cost savings and reduce operation/support expenditures over life of programmes.

10. Prototyping with competition reduced likelihood that contractors would team up in the next phase so prospect of only one proposal is diminished. In other cases, competition improved quality of systems contractors to introduce/continue cutting edge designs to remain competitive in next phase of programmes using existing capital for prototyping efforts
　

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