The future of Marine aviation is complex: aircraft are growing more technologically advanced, pilots face a proliferation of high-end and low-end threats, military budgets are squeezed and demand for Navy forces around the globe is growing.
So how will Marine aviation training keep up? In part, with fielding of tech advanced simulators.
Joint Terminal Attack Controllers using the simulator can coordinate with pilots in the air to identify and mark targets for air strikes from the ground
In a feat that combined live training and simulator training, we conducted a live, virtual and constructive demo. We took equipment that’s already on the aircraft that broadcasts the aircraft’s altitude, airspeed, position in real time, and we put a transmitter or receiver unit on the top of the building.
We were able to tap into that feed, and what that did was it took that feed of an actual aircraft on the range, and we piped it into simulator, and it was accurately recreated in the virtual workspace.
The aircraft is actually flying on the range and is properly displayed in the simulator with very low to minimal latency in a real-time altitude, airspeed, and attitude. So what that provided for is a real-time control of that aircraft with the ability to see the aircraft as well as have the ability to achieve visual recognition.
Marines are able to look up and actually assess the attitude and profile of that aircraft and then provide the clearance to essentially employ munitions on the desired intended target.
Before we had the simulator, we were really slow in the first few days on the range because that’s the first time operators did it. But now getting some practice time in, you get better control and better performance on the range with the live assets, so it makes it more efficient. So the simulator is really useful, it’s invaluable as far as getting Marines ready to go.
It has been harder and harder to get fleet aircraft that can support training due to a high operational tempo and due to challenges in keeping the aircraft ready to fly. The more training Marines can get on the range, the better they are when they actually get to an actual aircraft.
“So they’re not stumbling on Day 1, they’re already semi-proficient or trying to get there, whereas in the past before they had this simulator you’re a mess your first several times, so it’s good training for you, but for the guys airborne, they’re holding for a half hour just to get a bomb off because the guy on the ground is learning what to do.
The simulator has created a dramatic improvement in the first pass drop and the communications on the radio and everything. Marines work everything out here, so by the time that they’re on the range it’s just the real-life stuff that hits you. … A lot more first-pass drops, which is the whole goal of close-air support.
Want Marines will eventually be able to do is put this into a guy in a aircraft simulator and they’ll be running this simulator, talking to the guys in this simulator, and doing all their controls to get their currency requirements to satisfy their trainin while taking their targeting cues from other Marines in their own simulator.
A next step towards achieving that vision of connecting multiple simulators spread across the battlespace is the integrated training facility to house, all under one roof, simulators for pretty much anything in the carrier strike group.
We’ll be able to integrate them all together. Eventually we will be able to pipe in feeds from live aircraft out on our range – that’s the live part, and then vice versa hopefully we can pipe what’s being seen in the simulators, or what’s being constructed in the simulators, out to the live aircraft as well.
What we want to be able to do in the future, and this facility is the first step, is machine-to-machine data gathering. And that will allow us to gather large amounts of data – so not just necessarily how they did on that event, in the actual actions they took on that event, but we can also gather historical data on the aircraft, its system, how well the systems have held up.
We can look at, automatically, machine-to-machine, look at the pilot to assess proficiency, and see how much flight time was received recently, helping us build that bigger picture so we can inform leadership with the best information we can give them.
Despite the focus on high-end warfare technologies, aviators could face, equally dangerous less expensive threats like shoulder-launched anti-air missiles so we invested in Surface-to-Air Missile simulators to help ensure that pilots cycling through training events are aware of the threats they face on the ground and are flying with tactics that would keep them safe.
Though the SAM simulators aren’t connected to the planes in the air – so the pilot didn’t know in real-time he had been “shot” at with the simulator – the simulator logs video of the encounter. That video is incorporated into the pilot’s debrief after a training event, with the instructors explaining to the pilot whether his flight profile would have kept him safe or put him at risk to ground threats.
This is how you prove to Marines, you’re reachable, you need to be careful and you need to know what you’re doing, get your tactics right. Everything that’s out there is beatable, you’ve just got to know what you’re doing, but you’ve got to get your tactics right.
Readiness Tool allows top brass to determine which battalions and gear are most prepared for battle.
Marine Corps is experimenting with artificial intelligence to improve the way it deploys its forces and spot potential weaknesses years in advance.
The Marines built a tool that crunches data on personnel and equipment to measure how prepared individual battalions are for combat. The tool could ultimately help top brass deploy some 186,000 active-duty Marines and countless pieces of military hardware.
Allocating the service’s resources is an imperfect science. Leaders map out deployment strategies years or even decades in advance, but situations will invariably arise that throw a wrench in those plans.
Planners are constantly forced to “reshuffle the deck” as crises flare up in different places and figuring out which units to move around is a complicated process. Numerous factors—training, deployment history, equipment readiness and others—affect how prepared a group is for a given situation.
Today planners rely on spreadsheets, whiteboards and basic applications to track readiness and manage forces, but artificial intelligence can offer them a better understanding of the resources at their disposal and the long-term effects of the decisions they make.
The tech crunches both structured and unstructured data from multiple force management applications to create a real-time image of how prepared each unit is for combat. The tool specifically aims to build a five-year management plan for the Marine infantry battalions.
Tool has two primary functions: It flags the units that are most ready for action and explains why others come up short. Armed with that knowledge, commanders can proactively train and invest in less prepared groups before they fall even further behind.
“A lot of times Mairnes only invest more when the problem arises. Now they can see it ahead of time and say ‘OK, we’re going to take action now to prevent that from occurring.’”
The tool sheds light on how deployment decisions will affect forces in the long run. By analyzing historical trends along with real-time data, the tool could show how a unit’s readiness would change if it were, for instance, moved to a new location or given additional resources.
Marines are also building a separate AI system that ranks course of action plans based on those extrapolations, which could one day be merged with the readiness system.
“You integrate that all together and you get a full view of readiness across your force. Now you can really make some data-driven decisions.”
The next stage of the effort will include parts of the Marines’ aviation and logistics units, bringing about half branch into the purview of the program. With that additional data, the AI would further refine its processing rules to deliver better results.
So artificial intelligence is tasked with managing the particular deployments of troops in battle, moving them around in new and unexpected ways.
One way that future might manifest is by looking at a place where AI already manages workforce inventory-- like a warehouse stocking system, a process where items are unloaded wherever there is space in a warehouse and then scanned into a computer system than can track where the item is located.
When it comes time to retrieve an item for delivery, the same computer system directs warehouse workers to the most efficient route for finding the item, which could be stowed throughout the warehouse.
When modeling the warehouse system, it is interesting to consider how AI, given the same objectives as a commander, might organise and direct forces to achieve them.
“Why would an AI allocate forces in distinct areas of the battlefield? It could intermingle them and manage them at a granular level. Its categories are way more numerous, in the way that a warehouse AI manages categories at the shelf level.
Instead of distinct groupings of armor, air support, infantry, and artillery, a system run by artificial intelligence and managing a battle could coordinate a single helicopter with a pair of howitzers and an infantry platoon, directly grouping each in the same way that a warehouse worker finds an assortment of items to place into the same package.
“Anytime we’re on the road, our job, maintenance wise, is to provide safe and reliable jets for the pilots to accomplish their mission. Every new location presents a different challenge in how we get the job done, but the end goal for providing a safe jet for a pilot never changes. What does change is the environment in which we operate in.”
“Every exercise you go on is different, and it can be hard to start off. It could be not having the parts we need on hand, or not knowing how the base operates to get the support we need. Over time you figure out how to acquire some of that on site, what to bring along yourself and how to solve a problem before it becomes one.”
Here we consider how AI systems could be useful to a typical work order job of launch and recovery of aircraft, engine maintenance and servicing of life-saving equipment-- just a few of dozens of tasks Troops are expected to accomplish within a full day.
“We learn to operate in new environments, out here we’ve adapted our operations to give the best support possible. Maintenance is maintenance, our job never changes, but how we execute the mission does.”
“Our main mission is to enable successful sorties by generating aircraft parts, ultimately maintaining our full spectrum readiness. Our team encounters new repairs that force changes in direction and orders, but they all adapt and constantly find ways to make sure the job gets done.”
Maintaining the aging aircraft can be challenging as some parts are no longer commercially produced and the Fabrication Flight must collaborate and innovate to construct parts on their own.
“We all need each other in order to complete a task and make sure operations are done correctly. “Everything revolves in a circle – sheet metals technicians hand over parts to metals technicians who follow their technical order before sending to nondestructive inspection to make sure the piece is good for use on an aircraft.”
To display the teamwork necessary, the Troops walked us through the Fabrication Flight process.
Sheet metals technicians , kick off operations by receiving technical orders for aircraft repairs. Troops survey the technical order and pulls a thin, malleable sheet from their collection. The sheet is then cut to the specific measurements and handed off to a metals technician to be heat treated in a large oven.
"On our side we handle breaking the metal down and then crafting it to match the technical order for the specific part. When completed, the piece is hauled over to nondestructive inspection where tests are conducted to ensure the part is compositionally sound and aircraft ready.
"With the resources we have here, we are the final stop on a part's journey to an aircraft,” "If anything is wrong with the part, it's flagged and sent back to the workshop to either correct the issue, or start the operations all over again."
Accuracy in fabrication is essential in getting aircraft back up flying. When the part has completed all processes and is cleared for use, it is installed onto the aircraft, restoring readiness of the aircraft.
Fabrication flight Airmen gain a sense of accomplishment by witnessing their work come to fruition each time an aircraft takes off.
“Having combatant commands and other mission partners on base only adds to the importance of mission success. We take pride in the work of the flight, seeing the aircraft out there completing missions thanks to the maintenance here is an amazing feeling.”
By creating a virtual representation of an asset in the field using lightweight model “Digital Twin” visualisation, and then capturing info from smart sensors embedded in the asset, you can gain a complete picture of real-world performance and operating conditions. You can also simulate real-world scenario conditions for predictive operations.
Advances in virtual prototyping spaces has made possible the capability to simulating visual fidelity to a very high level. The next big challenge for virtual prototyping teams is simulating realistic interaction. Virtual prototyping, sometimes referred to as digital prototyping, is widely adopted by industry to simulate visual appearance and functionalities of production.
But conventional virtual prototyping techniques lack the simulation of the physical properties of a real interaction between user and product. Force feedback is based of development of virtual prototyping.
Virtual Reality tech creates an alternative reality in which worlds, objects and characters can be experienced that may not yet be available in reality so stakeholders are allowed to not only see the future product- achieved with concept sketch or mockup, but also experience the product and the interactions with its use context.
Simulation models as used in virtual engineering during development of training systems can be used during operation phases as well. In order to fully benefit from this, the simulation model must be connected to the physical system and other business operations In this way, information regarding past operation and current status can be fused with information regarding possible future operation, explored through virtual scenarios.
The overall result can be used for decision support in for instance operational planning or service and maintenance. In this way, simulation serves as a tool for arriving at a situation in which the future scenarios are perhaps not completely known, but in which one can readily address the most likely scenarios in an adequate manner.
Artificial intelligence can play a role in virtual manufacturing by improving simulation models or by offering better decision support. Extending the use of simulation models from the design phase to the operation phase also has advantages when new products are to be introduced or system needs to be reconfigured.
Virtual Reality is an attractive option since it offers the user a sense of being immersed in information where objects have a sense of ‘presence’ and allows them to interface with information at full scale if required. A design begins with an image or idea and the concept is disseminated via diagrams and descriptive speech.
Typically, information sources for conducting various virtual reality activities are not one single specific source, but instead all the different tech training information systems that are used in DoD The integration of these sources is not usually out-of-the-box-solution but most often highly customised solutions, engineered by specialists.
"Digital Twins" Provide Line of Sight to 3D Print Part Builds Previously Not Visible.
Digital Twins are learning digital models of physical assets, parts, processes and even systems. The purpose of the Digital Twins is to relay data about the performance and properties of a physical counterpart. With this information, Digital Twins will achieve complete repeatability of a 3D printed part, and greatly improve process reliability.
Now we have a digital representation of what the designer/customer wants, we have the actual part that we can touch and feel and also a Digital Twin of that actual part. In 3D printing we can only work in the digital world with a 3D digital model of the desired component. Now we can build the part, according to the 3D model, take that physical component and carry out our own 3D scan, creating yet another 3D model.
Digital Twin of the actual part can then be sent back to the designers and he can compare what we have manufactured to what his model wants, and even use the actual part model to simulate its impact, digitally, in the final design.
In the case of a 3D printer, we’re building a Digital Twin of a build process and recording the slightest defects, deviations and other build characteristics. With Digital Twins, models will continually be updated with each new build and become ever smarter in recognising and troubleshooting any potential issues that might arise.
Not only will there be a Digital Twin of the component, showing the internal and external requirements, but also a Digital Twin of the process that made that part; the process parameters, how long did the build take, how many layers were built, were there any issues.. all of these aspects building a digital picture of the part enabling further analysis and confidence in final applications of components.
Next generation of Digital Twins incorporate information from other sensors monitoring the 3D printing process, such as the shape of the pool of metal rendered molten by the laser. In addition, this smart, real-time quality control will not function in isolation.
The power of Digital Twins is their ability to share insights with each other. So you can imagine many 3D print machines sharing unique build insights with each other that makes them each more informed about what to watch for during a build process.
Through the Digital Twin process, you can accelerate the production of mission-critical equipment. Using Digital Twin technology, we’re aiming to rapidly speed up the time that parts could be re-engineered or newly created using 3D printing processes.
The key challenge with 3D printing is being able to additively build a part that mirrors the exact material composition and properties of the original part that was formed through subtractive measures. With operation of mission-critical parts there is no room for deviations in material performance or manufacturing error.
Properties and serviceability of 3D printed components are affected by their geometry, microstructure and defects. These important attributes are currently optimised by trial and error because the essential process variables can’t currently be selected from scientific principles.
A solution is to build and validate a Digital Twin of the 3D printing process capable of predicting of the spatial and temporal variations of physical parameters affecting the structure and properties of components.
In principle, the Digital Twin of 3D printing process , when validated with accurate with experimental data would replace or reduce expensive, time consuming physical experiments with rapid inexpensive numerical experiments. In the initial phase, the Digital Twin would consider all the important 3D print process variables as input and provide a transient 3D model.
1. Systems design: Design before you build with a visual, simulation approach.
2. Asset-based system of system design: Specify, publish, find, and reuse organisation simulation systems,
3. Product-line engineering: Design product platforms and variants quickly and efficiently, and make better trade-off decisions.
4. Systems model review: Improve product quality and model consistency through early design reviews within a systems modeling tool.
5. Systems model simulation: Validate complex behaviour earlier in the design life cycle, and establish predefined standards and best practice–based process.
6. Establish an open, flexible simulation system: Such a system is necessary to incorporate information sets from multiple engineering domains and quality control
7. Align combat engineering teams for better collaboration: Disconnected combat engineering teams across mechanical and electrical systems working in their own workgroups must collaborate as needed-- utility of systems-level view of products must be evaluated
8. Balance vitality and stability: Balancing vitality of innovation with reuse and predictive stability during establishment of an innovation platform for simulation and during product design and engineering.
9. Unify simulation connected systems optimisation: A single view of cross-domain system, product, and process is required for successful simulations
10. Incorporate quality with design and development: Achieving high level of product quality is why simulation virtually validates systems-level view. Assuring Incorporate/embed quality information from the early-stage design through subsequent product phases is key so simulations can more easily flow from system designs into product attributes.
So how will Marine aviation training keep up? In part, with fielding of tech advanced simulators.
Joint Terminal Attack Controllers using the simulator can coordinate with pilots in the air to identify and mark targets for air strikes from the ground
In a feat that combined live training and simulator training, we conducted a live, virtual and constructive demo. We took equipment that’s already on the aircraft that broadcasts the aircraft’s altitude, airspeed, position in real time, and we put a transmitter or receiver unit on the top of the building.
We were able to tap into that feed, and what that did was it took that feed of an actual aircraft on the range, and we piped it into simulator, and it was accurately recreated in the virtual workspace.
The aircraft is actually flying on the range and is properly displayed in the simulator with very low to minimal latency in a real-time altitude, airspeed, and attitude. So what that provided for is a real-time control of that aircraft with the ability to see the aircraft as well as have the ability to achieve visual recognition.
Marines are able to look up and actually assess the attitude and profile of that aircraft and then provide the clearance to essentially employ munitions on the desired intended target.
Before we had the simulator, we were really slow in the first few days on the range because that’s the first time operators did it. But now getting some practice time in, you get better control and better performance on the range with the live assets, so it makes it more efficient. So the simulator is really useful, it’s invaluable as far as getting Marines ready to go.
It has been harder and harder to get fleet aircraft that can support training due to a high operational tempo and due to challenges in keeping the aircraft ready to fly. The more training Marines can get on the range, the better they are when they actually get to an actual aircraft.
“So they’re not stumbling on Day 1, they’re already semi-proficient or trying to get there, whereas in the past before they had this simulator you’re a mess your first several times, so it’s good training for you, but for the guys airborne, they’re holding for a half hour just to get a bomb off because the guy on the ground is learning what to do.
The simulator has created a dramatic improvement in the first pass drop and the communications on the radio and everything. Marines work everything out here, so by the time that they’re on the range it’s just the real-life stuff that hits you. … A lot more first-pass drops, which is the whole goal of close-air support.
Want Marines will eventually be able to do is put this into a guy in a aircraft simulator and they’ll be running this simulator, talking to the guys in this simulator, and doing all their controls to get their currency requirements to satisfy their trainin while taking their targeting cues from other Marines in their own simulator.
A next step towards achieving that vision of connecting multiple simulators spread across the battlespace is the integrated training facility to house, all under one roof, simulators for pretty much anything in the carrier strike group.
We’ll be able to integrate them all together. Eventually we will be able to pipe in feeds from live aircraft out on our range – that’s the live part, and then vice versa hopefully we can pipe what’s being seen in the simulators, or what’s being constructed in the simulators, out to the live aircraft as well.
What we want to be able to do in the future, and this facility is the first step, is machine-to-machine data gathering. And that will allow us to gather large amounts of data – so not just necessarily how they did on that event, in the actual actions they took on that event, but we can also gather historical data on the aircraft, its system, how well the systems have held up.
We can look at, automatically, machine-to-machine, look at the pilot to assess proficiency, and see how much flight time was received recently, helping us build that bigger picture so we can inform leadership with the best information we can give them.
Despite the focus on high-end warfare technologies, aviators could face, equally dangerous less expensive threats like shoulder-launched anti-air missiles so we invested in Surface-to-Air Missile simulators to help ensure that pilots cycling through training events are aware of the threats they face on the ground and are flying with tactics that would keep them safe.
Though the SAM simulators aren’t connected to the planes in the air – so the pilot didn’t know in real-time he had been “shot” at with the simulator – the simulator logs video of the encounter. That video is incorporated into the pilot’s debrief after a training event, with the instructors explaining to the pilot whether his flight profile would have kept him safe or put him at risk to ground threats.
This is how you prove to Marines, you’re reachable, you need to be careful and you need to know what you’re doing, get your tactics right. Everything that’s out there is beatable, you’ve just got to know what you’re doing, but you’ve got to get your tactics right.
Readiness Tool allows top brass to determine which battalions and gear are most prepared for battle.
Marine Corps is experimenting with artificial intelligence to improve the way it deploys its forces and spot potential weaknesses years in advance.
The Marines built a tool that crunches data on personnel and equipment to measure how prepared individual battalions are for combat. The tool could ultimately help top brass deploy some 186,000 active-duty Marines and countless pieces of military hardware.
Allocating the service’s resources is an imperfect science. Leaders map out deployment strategies years or even decades in advance, but situations will invariably arise that throw a wrench in those plans.
Planners are constantly forced to “reshuffle the deck” as crises flare up in different places and figuring out which units to move around is a complicated process. Numerous factors—training, deployment history, equipment readiness and others—affect how prepared a group is for a given situation.
Today planners rely on spreadsheets, whiteboards and basic applications to track readiness and manage forces, but artificial intelligence can offer them a better understanding of the resources at their disposal and the long-term effects of the decisions they make.
The tech crunches both structured and unstructured data from multiple force management applications to create a real-time image of how prepared each unit is for combat. The tool specifically aims to build a five-year management plan for the Marine infantry battalions.
Tool has two primary functions: It flags the units that are most ready for action and explains why others come up short. Armed with that knowledge, commanders can proactively train and invest in less prepared groups before they fall even further behind.
“A lot of times Mairnes only invest more when the problem arises. Now they can see it ahead of time and say ‘OK, we’re going to take action now to prevent that from occurring.’”
The tool sheds light on how deployment decisions will affect forces in the long run. By analyzing historical trends along with real-time data, the tool could show how a unit’s readiness would change if it were, for instance, moved to a new location or given additional resources.
Marines are also building a separate AI system that ranks course of action plans based on those extrapolations, which could one day be merged with the readiness system.
“You integrate that all together and you get a full view of readiness across your force. Now you can really make some data-driven decisions.”
The next stage of the effort will include parts of the Marines’ aviation and logistics units, bringing about half branch into the purview of the program. With that additional data, the AI would further refine its processing rules to deliver better results.
So artificial intelligence is tasked with managing the particular deployments of troops in battle, moving them around in new and unexpected ways.
One way that future might manifest is by looking at a place where AI already manages workforce inventory-- like a warehouse stocking system, a process where items are unloaded wherever there is space in a warehouse and then scanned into a computer system than can track where the item is located.
When it comes time to retrieve an item for delivery, the same computer system directs warehouse workers to the most efficient route for finding the item, which could be stowed throughout the warehouse.
When modeling the warehouse system, it is interesting to consider how AI, given the same objectives as a commander, might organise and direct forces to achieve them.
“Why would an AI allocate forces in distinct areas of the battlefield? It could intermingle them and manage them at a granular level. Its categories are way more numerous, in the way that a warehouse AI manages categories at the shelf level.
Instead of distinct groupings of armor, air support, infantry, and artillery, a system run by artificial intelligence and managing a battle could coordinate a single helicopter with a pair of howitzers and an infantry platoon, directly grouping each in the same way that a warehouse worker finds an assortment of items to place into the same package.
“Anytime we’re on the road, our job, maintenance wise, is to provide safe and reliable jets for the pilots to accomplish their mission. Every new location presents a different challenge in how we get the job done, but the end goal for providing a safe jet for a pilot never changes. What does change is the environment in which we operate in.”
“Every exercise you go on is different, and it can be hard to start off. It could be not having the parts we need on hand, or not knowing how the base operates to get the support we need. Over time you figure out how to acquire some of that on site, what to bring along yourself and how to solve a problem before it becomes one.”
Here we consider how AI systems could be useful to a typical work order job of launch and recovery of aircraft, engine maintenance and servicing of life-saving equipment-- just a few of dozens of tasks Troops are expected to accomplish within a full day.
“We learn to operate in new environments, out here we’ve adapted our operations to give the best support possible. Maintenance is maintenance, our job never changes, but how we execute the mission does.”
“Our main mission is to enable successful sorties by generating aircraft parts, ultimately maintaining our full spectrum readiness. Our team encounters new repairs that force changes in direction and orders, but they all adapt and constantly find ways to make sure the job gets done.”
Maintaining the aging aircraft can be challenging as some parts are no longer commercially produced and the Fabrication Flight must collaborate and innovate to construct parts on their own.
“We all need each other in order to complete a task and make sure operations are done correctly. “Everything revolves in a circle – sheet metals technicians hand over parts to metals technicians who follow their technical order before sending to nondestructive inspection to make sure the piece is good for use on an aircraft.”
To display the teamwork necessary, the Troops walked us through the Fabrication Flight process.
Sheet metals technicians , kick off operations by receiving technical orders for aircraft repairs. Troops survey the technical order and pulls a thin, malleable sheet from their collection. The sheet is then cut to the specific measurements and handed off to a metals technician to be heat treated in a large oven.
"On our side we handle breaking the metal down and then crafting it to match the technical order for the specific part. When completed, the piece is hauled over to nondestructive inspection where tests are conducted to ensure the part is compositionally sound and aircraft ready.
"With the resources we have here, we are the final stop on a part's journey to an aircraft,” "If anything is wrong with the part, it's flagged and sent back to the workshop to either correct the issue, or start the operations all over again."
Accuracy in fabrication is essential in getting aircraft back up flying. When the part has completed all processes and is cleared for use, it is installed onto the aircraft, restoring readiness of the aircraft.
Fabrication flight Airmen gain a sense of accomplishment by witnessing their work come to fruition each time an aircraft takes off.
“Having combatant commands and other mission partners on base only adds to the importance of mission success. We take pride in the work of the flight, seeing the aircraft out there completing missions thanks to the maintenance here is an amazing feeling.”
By creating a virtual representation of an asset in the field using lightweight model “Digital Twin” visualisation, and then capturing info from smart sensors embedded in the asset, you can gain a complete picture of real-world performance and operating conditions. You can also simulate real-world scenario conditions for predictive operations.
Advances in virtual prototyping spaces has made possible the capability to simulating visual fidelity to a very high level. The next big challenge for virtual prototyping teams is simulating realistic interaction. Virtual prototyping, sometimes referred to as digital prototyping, is widely adopted by industry to simulate visual appearance and functionalities of production.
But conventional virtual prototyping techniques lack the simulation of the physical properties of a real interaction between user and product. Force feedback is based of development of virtual prototyping.
Virtual Reality tech creates an alternative reality in which worlds, objects and characters can be experienced that may not yet be available in reality so stakeholders are allowed to not only see the future product- achieved with concept sketch or mockup, but also experience the product and the interactions with its use context.
Simulation models as used in virtual engineering during development of training systems can be used during operation phases as well. In order to fully benefit from this, the simulation model must be connected to the physical system and other business operations In this way, information regarding past operation and current status can be fused with information regarding possible future operation, explored through virtual scenarios.
The overall result can be used for decision support in for instance operational planning or service and maintenance. In this way, simulation serves as a tool for arriving at a situation in which the future scenarios are perhaps not completely known, but in which one can readily address the most likely scenarios in an adequate manner.
Artificial intelligence can play a role in virtual manufacturing by improving simulation models or by offering better decision support. Extending the use of simulation models from the design phase to the operation phase also has advantages when new products are to be introduced or system needs to be reconfigured.
Virtual Reality is an attractive option since it offers the user a sense of being immersed in information where objects have a sense of ‘presence’ and allows them to interface with information at full scale if required. A design begins with an image or idea and the concept is disseminated via diagrams and descriptive speech.
Typically, information sources for conducting various virtual reality activities are not one single specific source, but instead all the different tech training information systems that are used in DoD The integration of these sources is not usually out-of-the-box-solution but most often highly customised solutions, engineered by specialists.
"Digital Twins" Provide Line of Sight to 3D Print Part Builds Previously Not Visible.
Digital Twins are learning digital models of physical assets, parts, processes and even systems. The purpose of the Digital Twins is to relay data about the performance and properties of a physical counterpart. With this information, Digital Twins will achieve complete repeatability of a 3D printed part, and greatly improve process reliability.
Now we have a digital representation of what the designer/customer wants, we have the actual part that we can touch and feel and also a Digital Twin of that actual part. In 3D printing we can only work in the digital world with a 3D digital model of the desired component. Now we can build the part, according to the 3D model, take that physical component and carry out our own 3D scan, creating yet another 3D model.
Digital Twin of the actual part can then be sent back to the designers and he can compare what we have manufactured to what his model wants, and even use the actual part model to simulate its impact, digitally, in the final design.
In the case of a 3D printer, we’re building a Digital Twin of a build process and recording the slightest defects, deviations and other build characteristics. With Digital Twins, models will continually be updated with each new build and become ever smarter in recognising and troubleshooting any potential issues that might arise.
Not only will there be a Digital Twin of the component, showing the internal and external requirements, but also a Digital Twin of the process that made that part; the process parameters, how long did the build take, how many layers were built, were there any issues.. all of these aspects building a digital picture of the part enabling further analysis and confidence in final applications of components.
Next generation of Digital Twins incorporate information from other sensors monitoring the 3D printing process, such as the shape of the pool of metal rendered molten by the laser. In addition, this smart, real-time quality control will not function in isolation.
The power of Digital Twins is their ability to share insights with each other. So you can imagine many 3D print machines sharing unique build insights with each other that makes them each more informed about what to watch for during a build process.
Through the Digital Twin process, you can accelerate the production of mission-critical equipment. Using Digital Twin technology, we’re aiming to rapidly speed up the time that parts could be re-engineered or newly created using 3D printing processes.
The key challenge with 3D printing is being able to additively build a part that mirrors the exact material composition and properties of the original part that was formed through subtractive measures. With operation of mission-critical parts there is no room for deviations in material performance or manufacturing error.
Properties and serviceability of 3D printed components are affected by their geometry, microstructure and defects. These important attributes are currently optimised by trial and error because the essential process variables can’t currently be selected from scientific principles.
A solution is to build and validate a Digital Twin of the 3D printing process capable of predicting of the spatial and temporal variations of physical parameters affecting the structure and properties of components.
In principle, the Digital Twin of 3D printing process , when validated with accurate with experimental data would replace or reduce expensive, time consuming physical experiments with rapid inexpensive numerical experiments. In the initial phase, the Digital Twin would consider all the important 3D print process variables as input and provide a transient 3D model.
1. Systems design: Design before you build with a visual, simulation approach.
2. Asset-based system of system design: Specify, publish, find, and reuse organisation simulation systems,
3. Product-line engineering: Design product platforms and variants quickly and efficiently, and make better trade-off decisions.
4. Systems model review: Improve product quality and model consistency through early design reviews within a systems modeling tool.
5. Systems model simulation: Validate complex behaviour earlier in the design life cycle, and establish predefined standards and best practice–based process.
6. Establish an open, flexible simulation system: Such a system is necessary to incorporate information sets from multiple engineering domains and quality control
7. Align combat engineering teams for better collaboration: Disconnected combat engineering teams across mechanical and electrical systems working in their own workgroups must collaborate as needed-- utility of systems-level view of products must be evaluated
8. Balance vitality and stability: Balancing vitality of innovation with reuse and predictive stability during establishment of an innovation platform for simulation and during product design and engineering.
9. Unify simulation connected systems optimisation: A single view of cross-domain system, product, and process is required for successful simulations
10. Incorporate quality with design and development: Achieving high level of product quality is why simulation virtually validates systems-level view. Assuring Incorporate/embed quality information from the early-stage design through subsequent product phases is key so simulations can more easily flow from system designs into product attributes.
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