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
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