As is true with any emerging field of technology, Digital Twins is just now coalescing into a clearer definition of what it actually means in practice. Many market observers and vendors have offered up their views on what Digital Twins means to them. The ingredients have been around for a while, but their synergistic combination is just now bearing initial business fruit. Key enablers are the increasing accuracy of CAE models, the declining costs of high-performance computing, expanding cloud accessibility, and low-cost sensors.
What is IIoT? IoT (Internet of Things) is just connecting physical devices/systems to each other via the internet (think: your home internet-connected thermostat and an app on your smartphone that enables you to observe and change the temperature in your home from anywhere on earth if you have an internet connection). If the devices and connections and data transfer via the internet are for business/industrial systems, that’s the INDUSTRIAL Internet of Things. A lot more detailed and involved, but the same basic idea. When one of the “things” is a current/updated physics/simulation-based digital model, that’s where IIoT plays a role in Digital Twins.
This “How It Works” area of the Revolution In Simulation website is your go-to source for more in-depth background information on Digital Twins and the latest relevant end-user enterprise and vendor case studies and success stories.
Physics-based simulation models (CAE) have proven their mainstream business value during the development and manufacturing phases of the Product Performance Life-cycle (PPL).
Now they are moving beyond those phases into the entire life cycle of products and systems by being updated/modified to reflect the ongoing true in-field status/condition of such products and by being subject to the actual in-field loadings and boundary conditions obtained from sensors (the Industrial Internet of Things – IIoT). The resulting Digital Twins can then be used to anticipate needed maintenance and predict the behavior of future proposed operational changes to the physical structures and systems they represent in digital form.
This white paper discusses how synthetic datasets for training AI can be generated in hours using the OnScale cloud simulation platform. The demonstrated approach of using synthetic datasets to train AI networks can drastically reduce cost, risk, and time for the development of new hardware technologies.
The true cost of deploying and maintaining a digital twin is in collecting and analyzing the data. The data gives life to static 3D models.
Beyond CAE's Dr. Dennis Nagy shares his prediction for Digital Twins in the coming year.
"Although analytical twins have existed for a while, this evolution of simulation-based models that lead to the creation of digital twins is really transforming manufacturing, as product designs become more customized, unique and intricate by nature."
“Collaborating with ANSYS to create an advanced IoT digital twins framework provides our customers with an unprecedented understanding of their deployed assets’ performance by leveraging physics and simulation-based analytics.” — Sam George, corporate vice president of Azure IoT, Microsoft
Bentley Systems conference focuses on infrastructure uses of digital twins.
Let's discuss the importance of keeping your digital twins in sync with real products. Models so accurate they’re a digital twin of the product you’re creating can help you throughout the design and development process. 1D models can help you determine the best architecture for your multi-physics system, 3D models can help you design into the details, and testing can help you improve modelling realism. Combining all the three technologies gives you the highest possible accuracy while making design decisions. But in today’s world the design job isn’t done when you ship. You have to be able to take feedback, track how products are used – with detailed data coming from the increasing numbers of sensors in modern devices – and then use that to support, maintain and improve the products you have out in the market, as well as incorporating all that information into your next generation. That means keeping your digital twins in sync with the real products, even once they’re in customers’ hands.
How can food and beverage companies use the digital twin and industrial IoT to dramatically improve production performance? This eBook shares the value of the digital twin and IIoT for companies that produce food and consumer packaged goods. Then, it shares some practical examples and advice to get started down the path to streamline R&D and new product development, optimize production plans, increase performance, gain production intelligence, improve quality, and compete as an integrated supply chain.
In a commissioned study of IoT decision makers conducted by Forrester Consulting on behalf of Siemens in May 2019, respondents of varied IoT maturity levels recognized that digital twins can continuously improve their product offerings and improve product quality.
Karen Willcox is a leading aerospace researcher and expert in simulation-based engineering who specializes in the aerospace industry. Her work on simplified simulation models has made it possible to accelerate the development and design of complex systems.
Innovation and new technology applications are being established as part of core business management tools and are starting to appear in the area of managing M&A. When M&A is announced, organisations are committing to buy an asset or asset groups – at which point a due diligence effort is usually conducted to establish the actual state of the asset. Digital Twins have shown significant promise for the management of assets, and could also be transformational in the M&A process to qualify the quality of the assets.
PREVIOUS WEBINAR AVAILABLE ON DEMAND The phrase “digital twin” has become the be-all-and-end-all of manufacturing buzzwords, stirring up Utopian views on what it can do for predictive maintenance, simulation and more. But how is a digital twin different from a 3D CAD product model? Can it ever live up to its full potential? Is anyone really making use of digital twins? In this LIVE webcast, DE challenges panelists to discuss: a no-nonsense definition of digital twins; the types of products that make sense as digital twins; real-world examples of digital twins in operation.
Digital twins are virtual representations of physical products. They have the ability to unlock value and optimization throughout a product’s lifecycle. By leveraging real-world data from IIoT-connected product and physics-based simulations, digital twins can better inform and predict product performance. This enables users to develop new designs, operations and controls to optimize performance, reduce downtime and enable service-based products — often without the customer needing to upgrade hardware. The technology to get an IIoT digital twin running is available, however, many organizations are having a hard time implementing and connecting all of the digital, physical and data assets together. With the help of ANSYS Twin Builder and PTC ThingWorx, engineers can simplify the creation of digital twins using physics-based simulations.
For industry and the internet of things (#IoT), digital twins, offering virtual representations of real-world products will be the innovation backbone of the future. Entire systems can be simulated and tested long before a physical prototype has been built. Even operation of existing systems can be further optimized using a #DigitalTwin. Imagine the extraordinary possibilities merging them with artificial intelligence (#AI). Industry experts for digital twins are already using all these possibilities in concrete applications. Siemens Stories on Digital Twin: https://sie.ag/2FSldHZ Make use of it: https://sie.ag/2XcV2q8
Karen Willcox is a leading aerospace researcher and expert in simulation-based engineering who specializes in the aerospace industry. Her work on simplified simulation models has made it possible to accelerate the development and design of complex systems. Karen E. Willcox is Director of the Oden Institute for Computational Engineering and Sciences and a Professor of Aerospace Engineering and Engineering Mechanics, at the University of Texas at Austin. She holds the W. A. “Tex” Moncrief, Jr. Chair in Simulation-Based Engineering and Sciences and the Peter O'Donnell, Jr. Centennial Chair in Computing Systems. Prior to joining the Oden Institute in 2018, she spent 17 years as a professor at the Massachusetts Institute of Technology, where she served as Professor of Aeronautics and Astronautics, the founding Co-Director of the MIT Center for Computational Engineering, and the Associate Head of the MIT Department of Aeronautics and Astronautics. She is also an External Professor at the Santa Fe Institute.
Exploring how digital twins are shaping our digital fabric and engineering future.
At the center of the "Simulation and Digital Twins" colloquium was the question of how to better monitor processes and plants using digital twins, and how simulations offer completely new possibilities for 3D production.
Industrial research requires simulation experts with a passion for digital twins. In the race to innovate, their enthusiasm makes the crucial difference.
From RevSim sponsor PLM Alliances' principal Rich McFall comes this excellent CMSights Blog: In this month’s CMsights we asked Configuration Management practitioner, standards influencer, trainer, and author Kim Robertson to help us distill all the hype about digital twins and digital threads so we can understand their impact on as-maintained configuration management for long-life aerospace & defense equipment. Kim Robertson has over 39 years of experience in the A&D sector and is a co-author of “Configuration Management: Theory, Practice and Application” which is being used as the text for a graduate level course in C&DM at the Technical University of Eindhoven. He holds a CMPIC Configuration Management Principles and Implementation certification and is a National Defense Industrial Association (NDIA) Certified Configuration Data Manager (CCDM). Kim is a member of the SAE International G-33 committee for CM Standards and worked on Revision C of SAE/EIA-649.
Manned diving operations are a necessary part of maintaining offshore oil and gas assets, but also a very costly and dangerous process. With new technological developments such as Digital Twins, could a future where divers no longer have to work on offshore rigs be in sight? Umar Ali explores the potential of ‘zero dive.’
BECOMING A PREDICTIVE DIGITALLY ENABLED COMPANY”, presented by Front End Analytics, reveals how FEA’s Predictive Analytics 3.0, deployed using EASA, is enabling the adoption of artificial intelligence (AI), machine learning (ML) and digital twins for next generation simulation and modeling.
For industry and the internet of things (#IoT), digital twins, offering virtual representations of real-world products will be the innovation backbone of the future. Entire systems can be simulated and tested long before a physical prototype has been built. Even operation of existing systems can be further optimized using a #DigitalTwin. Imagine the extraordinary possibilities merging them with artificial intelligence (#AI). Industry experts for digital twins are already using all these possibilities in concrete applications.
EASA's Sebastian Dewhurst discusses how much faster the learning process would be if an algorithm "knew". There would be far fewer failures early on, and far less data would be required.
The phrase “digital twin” has become quite the manufacturing buzzword, stirring up Utopian views on what it can do for predictive maintenance, simulation and more. But how is it different from a 3D CAD product model? Can it ever live up to its full potential? In this LIVE webcast, DE engages expert panelists to discuss the topic.
Configurable safety relays help prevent injuries and damage in factory automation systems by cutting off electrical power in response to data received from sensors. When a safety relay fails, the production line must be halted until the relay can be repaired or replaced, resulting in expensive downtime.
The oil and gas industry is always searching for ways to produce energy at lower costs. To achieve this goal, the industry can apply oil and gas digital twins to various industrial equipment. Physics-based digital twins provide prognostics and health management which enables system optimization and predictive maintenance.
Cambashi, a leading UK-based computer/software market analyst firm has just published this article on the growing importance of Digital Twins.
Industry 4.0 and digital twins are buzzwords we hear on a daily basis. But how far have companies come, and how does COMSOL come into play in the new era? Here, we will look into one successful case, where ABB Traction Motors intends to make mass customization available by using simulation applications for electric motor design. By turning high-fidelity multiphysics models into simulation applications, new analysis capabilities are planned to be available to several departments, from product design to sales.
COMSOL Blog: "Is the term “digital twin” just hype, or a trick to get a new angle to sell modeling software? In this blog post, we discuss the difference between models, applications, and digital twins. We conclude that although the term has been misused to a certain extent (in relation to the original formulation), there is substance behind it."
Growth in the Internet of Things is spurring interest in digital twins. Here's how you can make money from it.
"By definition, a virtual sensor is a type of software that, given the available information, processes what a physical sensor otherwise would. It learns to interpret the relationships between the different variables, and observes readings from the different instruments. Think of it as a kind of a “ghost” of the physical sensor." (Chad Jackson)
ZF applies the latest VR and simulation technology.
People have been feeding sensor data to simulations for years. How are Digital Twins different? This post explains the key difference between the two scenarios.
Akselos to generate Digital Twins of pressure vessels within the OGTC robotics program.
This article explains the concept of a Digital Twin, a digital model driven by sensor data to provide future or deeper insight into an existing physical product's performance.
At the NAFEMS European Conference in Budapest in October 2018 (focus topic: Multiphysics Simulation), the Moderator of the Digital Twins "How It Works" area of Revolution in Simulation (Dennis Nagy) presented a keynote on the definitions and current status of Digital Twins. Take a look.
What good is a revolution if it doesn’t result in useful change? See how companies are achieving significant time savings with measurable improvements in consistency, accuracy & repeatability…READ MORE
Digital Twins have been around for a while, but they are just beginning to bear fruit. Key enablers are the increasing accuracy of simulation, lower Cloud computing costs and accessibility, and low-cost sensors.