The concept of “Digital Twins” is beginning to expand beyond just the notion of a virtual product. The idea of the digital twin is that all of product data is contained together, from initial design files through simulation and materials data. Finally, data about the product’s performance in the field will also be added. Lately, the term is also including the product’s manufacturing data.
The twist that makes the Digital Twin concept important is that computers have greater predictive skills that humans working with physical prototypes. “The digital twin a good definition of what we do. It’s a virtual representative of a physical product or operation.
The point is the precision we can reach. A lot of our technology acquisitions have been in simulation, test, and electronics. If we can improve the precision of the models we’re creating, we can predict performance.”
Prediction is the key to the Digital Twin. If a computer can calculate and predict how materials perform, that computer can create the optimum configuration for the product. System level simulation is predicting how we expect that system to perform. Design requirements can be improved and move into the design phase with a higher set of requirements.”
As the data is moved through design and into test, the original design files remain attached as part of the Digital Twins data. “The Digital Twin comes with CAD and tool development. That gives a lot of information to the downstream processes.. If we understand the language of the product from its inception, we can see if it is meeting the desired threshold and how it will perform in the future.”
The goal is to create a model of the product that not just downplays the need for a physical prototype but actually surpasses what a prototype can provides. We can see the Digital Twin as many twins – the 3D simulation through the product in the field. All of that feeds back into the Digital Twin model. “If you look at the physical design, it’s generative design. Let the computer look at weight or aerodynamics. The physical analysis, the tech systems create the shape based on the constraints.”
The Digital Twin in the manufacturing process brings together two virtual worlds, the digitised product and the digitised shop floor processes. Beyond that, data relating to the supply chain is also part of the mix. “Using the Digital Twin of the factory, we can see how the factory is performing by looking through all of the data. We can look at future orders and create a model of how the factory would need to perform to meet the projections and thus predict the future.”
Take aerospace as an example of how a Digital Twin can assist with the performance and maintenance of a product. One application is to create a Digital Twin of every plane the comes down the line. We can understand the precise configuration that operates at any given time and create a Digital Twin to support the maintenance of each plane.”
The Digital Twin technology can benefit a wide range of industries, but it is particularly well suited to high volume, high mix products. “All of the discrete industries are benefiting from Digital Twin technology now. The industries benefiting the most are those ones what put a large emphasis on physical design like aerospace, To create a high-volume production run, you have to have high reliability in the model. Precision level is your confidence level. The Digital Twin has to be accurate.
A virtual reality function in the Digital Twin package may help in replacing the physical prototype, since it will give users a powerful sense of the product. “We use augmented and virtual reality to impact the feel of the aircraft. In the near future, there will be more confidence in viewing a product in virtual reality. They’re doing that in the test phase. In aerospace, physical prototypes were the name of the game, but we were going to get more accustomed with looking at the product in the digital world rather than as a prototype.”
Others define a Digital Twin as digital replicas of different assets, processes and systems in your business which can be used a number of ways. This generic definition is basically correct. However, a Digital Twin is more accurately described as an integrated set of digital replicas or models driven by a rich information model called a digital thread.
A true Digital Twin is not a single model of the asset, even though it’s referred to as a singular “Twin.” It consists of many mathematical models and virtual representations that comprehend the asset’s entire lifecycle – all the way from ideation, through realisation and utilisation – and all its constituent technologies, including electronics, mechanical, manufacturing and in-service performance.
We refer to a set of Digital Twins: Product, Production and Performance. Each of these Digital Twins consists of multiple virtual models appropriate for the given product and production system.
Accurate Digital Twins comprehend the interactions between all aspects of the product and production system. Digital Enterprise Tool was built on our Innovation platform, enables the creation of the most accurate, comprehensive Digital Twins possible.
Product Digital Twin. A Digital Twin for products is typically created using our Systems Driven Product Development tech, which drives the creation of intelligent 3D models. Technologies like Convergent Modeling, Generative Design and Predictive Analytics are the basis for these intelligent models.
Key enablers for System Product develop tech include our comprehensive, semantic digital thread data model, as well as a complete set of integrated tools to help you create model-based system representations and accurate Digital Twins of the product, and these Digital Twins are able to comprehend the impact of design changes on the production system.
A product Digital Twin will typically include electronics and simulations applications, finite element structural, flow and heat transfer models and motion simulations.
Product Digital Twins also rely on predictive engineering analytics, which applies multidisciplinary engineering simulation and tests with intelligent reporting and data analytics. These capabilities lead to digital twins that can predict the product’s real-world behaviour throughout its lifecycle.
Predictive engineering analytics includes tools manufacturers leverage to expand traditional design verification and validation into a predictive role that supports system product development. The ultimate goal of implementing a predictive engineering analytics strategy is delivering innovation for complex products faster and with greater confidence.
Production Digital Twin. The Digital Twin for production uses many of the same tools and techniques to create a twin of the production system. Production Digital Twins, like product Digital Twins, can include 3D models and predictive analytical models as well as production engineering specific models that use tools for conceptual design and virtual commissioning of smaller Production Systems and Machine Tools used to engineer and virtually commission large production lines.
Performance Digital Twin. The Digital Twin for performance is based on tools enable insight discovery, analysis and monitoring from in-service products and production systems. Performance Analytics quickly identifies product issues disrupting the supply chain, manufacturing process or customer experience.
The performance Digital Twin may also include data analysis to discover hidden product issues before they occur; graphical displays to clearly identify potentially problematic configurations; and automated data monitoring to fine-tune operations and provide insight for improving your products.
Virtual Product Development is used to develop a product heavily – but not exclusively - relying on digital representations throughout the whole or a part of the project’s life cycle. The term “virtual” expresses that it does not yet exist as real hardware, that in fact it is not touchable.
Virtual development makes use of many tools for layout, geometry generation, calculation and analysis, test and evaluation including the management of digital data.
This suite enables to concurrently anticipate a lot more considerations sooner for product and process design than in earlier days. Although mostly relying on and working with approximated data, calculations and simulations today come close to verification and qualification test results.
The Digital Mockup is a core element in Virtual Development, as it is the culmination of the design intent that gives the product an “early face”. If Virtual Product Development is the unifying concept and approach, Virtual Prototyping actually is the process of digitally testing and evaluating the virtual representations of the product in all aspects of developmental and operational life. So the Digital Mockup is embedded in a spectrum of prototyping activities, which aim to mature the product as fast, as less costly and as reliably as possible
Construction of Hardware Mock-ups has been an integral part of any complex product development. A Mock-up is traditionally a hardware or physical model of a component, an assembly or an entire product. It can be full-size or a scaled model of metal or actual production hardware. All military airframe integrators use Hardware Mock-ups to evaluate and verify the design, train personnel or present them to customers.
Major Hardware Mock-ups activities involve the assessment of space allocations, detailed part fitting checks, interference and clearance studies, part installation and removal and assembly verification. A Hardware Mock-up as primary tool for determining lengths of electrical harnesses and for fitting tubes, hoses and other routings into a densely packed structural space. Maintenance checks could also be run with them. Mock-ups for marketing purposes still represent an important means in the commercial business and are likely to do so for quite some time.
Hardware Mock-ups, though having been standard and successful industry practice for a long time have a number of shortfalls that are better addressed with their digital substitutes. In fact, they are only an assurance that everything will fit together, in former times based on drawings.
No “pre-mock-up” investigations can be run. Update with modifications or duplications are expensive, as always a physical component has to be produced. The response to changes is relatively low except for minor ones like drilling holes and there is an inability to reflect real-time configurations.
So the mock-up is usually representative only for one aircraft, and is of very little use afterwards e.g. after certification. Last but not least, maybe the major issue, it is quite costly. There are design, labour and maintenance hours to be paid for, not to forget tools and all the materials. In addition, it consumes precious factory floor space.
The majority of Digital Mock-up applications, as the classical substitute of Hardware Mockups, cover the geometrical and functional areas. The closer one tries to assess the behaviour and interactions of the product in its environment the more will efforts shift to the right end of the spectrum.
Commercially available Digital Mock-up, Digital Simulation tools and Virtual Manufacturing/Digital Factory tools have matured as they cover most requirements for geometrical and functional assessment, and, to a lesser extent, operational constraints.
Shortfalls have to be compensated either with specific tools e.g. for tolerancing, tool developments or with physical specimen. To fully cover the whole spectrum requires all design tools to efficiently communicate with each other so that results obtained individually can be compressed to an overall view of the Virtual Prototype.
The majority of Digital Mock-up applications, as the classical substitute of Hardware Mockups, cover the geometrical and functional areas. The closer one tries to assess the behaviour and interactions of the product in its environment the more will efforts shift to the right end of the spectrum.
1. Baseline
A baseline is an agreed set of 3D and non-3D data at a certain time during development that is used as the reference for all design activities. It represents a preliminary status and is the starting point for the next iterations. It is a configuration of a product or status of product data, formally established at a specific point in time, which serves as a reference for further activities.
2. Change
Term used to identify a definition progress over time with reference to a basic or technical definition of a product managed by means of a modification system.
3. Dual-use
These are technologies, manufacturing facilities and products that have military and commercial applications. Commercially produced items, hardware or software, that can therefore be used, with or without adaptations, for military equipment.
4. Effectiveness
The effectiveness of a system is a quantitative measure of the degree to which the system’s purpose is achieved. Effectiveness measures are usually very dependent upon system performance.
5. Iteration
A repetition and rework activity that encompasses multiple passes for the design to converge to suit an array of sometimes conflicting specifications.
6. 3D Master Model
A Master Model is a set of digital 3D data-- surface or volume used as the basic reference for design and/or manufacturing. It progresses during development and when fully detailed it becomes the input for production, documentation and verification activities.
7. Modification
Any controlled change by the Modification system to the definition of the aircraft or equipment whose introduction affects airworthiness/certification, operational serviceability, customer or own company contractual/financial considerations.
8. Pilot
A pilot is a near term demonstration project. It can be a proof-of-concept and a preoperational assessment. Done in laboratories or usually in small-scale business units it serves to find out flaws in the behaviour of the system under operational or near operational conditions.
9. Prototype
A prototype is the first or original example of something that has been or will be copied or developed. It is a model or preliminary version.
10. Version
A specified customised definition of an allocated aircraft within a given production standard/model.
The twist that makes the Digital Twin concept important is that computers have greater predictive skills that humans working with physical prototypes. “The digital twin a good definition of what we do. It’s a virtual representative of a physical product or operation.
The point is the precision we can reach. A lot of our technology acquisitions have been in simulation, test, and electronics. If we can improve the precision of the models we’re creating, we can predict performance.”
Prediction is the key to the Digital Twin. If a computer can calculate and predict how materials perform, that computer can create the optimum configuration for the product. System level simulation is predicting how we expect that system to perform. Design requirements can be improved and move into the design phase with a higher set of requirements.”
As the data is moved through design and into test, the original design files remain attached as part of the Digital Twins data. “The Digital Twin comes with CAD and tool development. That gives a lot of information to the downstream processes.. If we understand the language of the product from its inception, we can see if it is meeting the desired threshold and how it will perform in the future.”
The goal is to create a model of the product that not just downplays the need for a physical prototype but actually surpasses what a prototype can provides. We can see the Digital Twin as many twins – the 3D simulation through the product in the field. All of that feeds back into the Digital Twin model. “If you look at the physical design, it’s generative design. Let the computer look at weight or aerodynamics. The physical analysis, the tech systems create the shape based on the constraints.”
The Digital Twin in the manufacturing process brings together two virtual worlds, the digitised product and the digitised shop floor processes. Beyond that, data relating to the supply chain is also part of the mix. “Using the Digital Twin of the factory, we can see how the factory is performing by looking through all of the data. We can look at future orders and create a model of how the factory would need to perform to meet the projections and thus predict the future.”
Take aerospace as an example of how a Digital Twin can assist with the performance and maintenance of a product. One application is to create a Digital Twin of every plane the comes down the line. We can understand the precise configuration that operates at any given time and create a Digital Twin to support the maintenance of each plane.”
The Digital Twin technology can benefit a wide range of industries, but it is particularly well suited to high volume, high mix products. “All of the discrete industries are benefiting from Digital Twin technology now. The industries benefiting the most are those ones what put a large emphasis on physical design like aerospace, To create a high-volume production run, you have to have high reliability in the model. Precision level is your confidence level. The Digital Twin has to be accurate.
A virtual reality function in the Digital Twin package may help in replacing the physical prototype, since it will give users a powerful sense of the product. “We use augmented and virtual reality to impact the feel of the aircraft. In the near future, there will be more confidence in viewing a product in virtual reality. They’re doing that in the test phase. In aerospace, physical prototypes were the name of the game, but we were going to get more accustomed with looking at the product in the digital world rather than as a prototype.”
Others define a Digital Twin as digital replicas of different assets, processes and systems in your business which can be used a number of ways. This generic definition is basically correct. However, a Digital Twin is more accurately described as an integrated set of digital replicas or models driven by a rich information model called a digital thread.
A true Digital Twin is not a single model of the asset, even though it’s referred to as a singular “Twin.” It consists of many mathematical models and virtual representations that comprehend the asset’s entire lifecycle – all the way from ideation, through realisation and utilisation – and all its constituent technologies, including electronics, mechanical, manufacturing and in-service performance.
We refer to a set of Digital Twins: Product, Production and Performance. Each of these Digital Twins consists of multiple virtual models appropriate for the given product and production system.
Accurate Digital Twins comprehend the interactions between all aspects of the product and production system. Digital Enterprise Tool was built on our Innovation platform, enables the creation of the most accurate, comprehensive Digital Twins possible.
Product Digital Twin. A Digital Twin for products is typically created using our Systems Driven Product Development tech, which drives the creation of intelligent 3D models. Technologies like Convergent Modeling, Generative Design and Predictive Analytics are the basis for these intelligent models.
Key enablers for System Product develop tech include our comprehensive, semantic digital thread data model, as well as a complete set of integrated tools to help you create model-based system representations and accurate Digital Twins of the product, and these Digital Twins are able to comprehend the impact of design changes on the production system.
A product Digital Twin will typically include electronics and simulations applications, finite element structural, flow and heat transfer models and motion simulations.
Product Digital Twins also rely on predictive engineering analytics, which applies multidisciplinary engineering simulation and tests with intelligent reporting and data analytics. These capabilities lead to digital twins that can predict the product’s real-world behaviour throughout its lifecycle.
Predictive engineering analytics includes tools manufacturers leverage to expand traditional design verification and validation into a predictive role that supports system product development. The ultimate goal of implementing a predictive engineering analytics strategy is delivering innovation for complex products faster and with greater confidence.
Production Digital Twin. The Digital Twin for production uses many of the same tools and techniques to create a twin of the production system. Production Digital Twins, like product Digital Twins, can include 3D models and predictive analytical models as well as production engineering specific models that use tools for conceptual design and virtual commissioning of smaller Production Systems and Machine Tools used to engineer and virtually commission large production lines.
Performance Digital Twin. The Digital Twin for performance is based on tools enable insight discovery, analysis and monitoring from in-service products and production systems. Performance Analytics quickly identifies product issues disrupting the supply chain, manufacturing process or customer experience.
The performance Digital Twin may also include data analysis to discover hidden product issues before they occur; graphical displays to clearly identify potentially problematic configurations; and automated data monitoring to fine-tune operations and provide insight for improving your products.
Virtual Product Development is used to develop a product heavily – but not exclusively - relying on digital representations throughout the whole or a part of the project’s life cycle. The term “virtual” expresses that it does not yet exist as real hardware, that in fact it is not touchable.
Virtual development makes use of many tools for layout, geometry generation, calculation and analysis, test and evaluation including the management of digital data.
This suite enables to concurrently anticipate a lot more considerations sooner for product and process design than in earlier days. Although mostly relying on and working with approximated data, calculations and simulations today come close to verification and qualification test results.
The Digital Mockup is a core element in Virtual Development, as it is the culmination of the design intent that gives the product an “early face”. If Virtual Product Development is the unifying concept and approach, Virtual Prototyping actually is the process of digitally testing and evaluating the virtual representations of the product in all aspects of developmental and operational life. So the Digital Mockup is embedded in a spectrum of prototyping activities, which aim to mature the product as fast, as less costly and as reliably as possible
Construction of Hardware Mock-ups has been an integral part of any complex product development. A Mock-up is traditionally a hardware or physical model of a component, an assembly or an entire product. It can be full-size or a scaled model of metal or actual production hardware. All military airframe integrators use Hardware Mock-ups to evaluate and verify the design, train personnel or present them to customers.
Major Hardware Mock-ups activities involve the assessment of space allocations, detailed part fitting checks, interference and clearance studies, part installation and removal and assembly verification. A Hardware Mock-up as primary tool for determining lengths of electrical harnesses and for fitting tubes, hoses and other routings into a densely packed structural space. Maintenance checks could also be run with them. Mock-ups for marketing purposes still represent an important means in the commercial business and are likely to do so for quite some time.
Hardware Mock-ups, though having been standard and successful industry practice for a long time have a number of shortfalls that are better addressed with their digital substitutes. In fact, they are only an assurance that everything will fit together, in former times based on drawings.
No “pre-mock-up” investigations can be run. Update with modifications or duplications are expensive, as always a physical component has to be produced. The response to changes is relatively low except for minor ones like drilling holes and there is an inability to reflect real-time configurations.
So the mock-up is usually representative only for one aircraft, and is of very little use afterwards e.g. after certification. Last but not least, maybe the major issue, it is quite costly. There are design, labour and maintenance hours to be paid for, not to forget tools and all the materials. In addition, it consumes precious factory floor space.
The majority of Digital Mock-up applications, as the classical substitute of Hardware Mockups, cover the geometrical and functional areas. The closer one tries to assess the behaviour and interactions of the product in its environment the more will efforts shift to the right end of the spectrum.
Commercially available Digital Mock-up, Digital Simulation tools and Virtual Manufacturing/Digital Factory tools have matured as they cover most requirements for geometrical and functional assessment, and, to a lesser extent, operational constraints.
Shortfalls have to be compensated either with specific tools e.g. for tolerancing, tool developments or with physical specimen. To fully cover the whole spectrum requires all design tools to efficiently communicate with each other so that results obtained individually can be compressed to an overall view of the Virtual Prototype.
The majority of Digital Mock-up applications, as the classical substitute of Hardware Mockups, cover the geometrical and functional areas. The closer one tries to assess the behaviour and interactions of the product in its environment the more will efforts shift to the right end of the spectrum.
1. Baseline
A baseline is an agreed set of 3D and non-3D data at a certain time during development that is used as the reference for all design activities. It represents a preliminary status and is the starting point for the next iterations. It is a configuration of a product or status of product data, formally established at a specific point in time, which serves as a reference for further activities.
2. Change
Term used to identify a definition progress over time with reference to a basic or technical definition of a product managed by means of a modification system.
3. Dual-use
These are technologies, manufacturing facilities and products that have military and commercial applications. Commercially produced items, hardware or software, that can therefore be used, with or without adaptations, for military equipment.
4. Effectiveness
The effectiveness of a system is a quantitative measure of the degree to which the system’s purpose is achieved. Effectiveness measures are usually very dependent upon system performance.
5. Iteration
A repetition and rework activity that encompasses multiple passes for the design to converge to suit an array of sometimes conflicting specifications.
6. 3D Master Model
A Master Model is a set of digital 3D data-- surface or volume used as the basic reference for design and/or manufacturing. It progresses during development and when fully detailed it becomes the input for production, documentation and verification activities.
7. Modification
Any controlled change by the Modification system to the definition of the aircraft or equipment whose introduction affects airworthiness/certification, operational serviceability, customer or own company contractual/financial considerations.
8. Pilot
A pilot is a near term demonstration project. It can be a proof-of-concept and a preoperational assessment. Done in laboratories or usually in small-scale business units it serves to find out flaws in the behaviour of the system under operational or near operational conditions.
9. Prototype
A prototype is the first or original example of something that has been or will be copied or developed. It is a model or preliminary version.
10. Version
A specified customised definition of an allocated aircraft within a given production standard/model.
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