Dick Slansky is senior analyst, PLM & engineering design tools, at ARC Advisory Group. He is responsible for directing the research and consulting in the areas of product lifecycle management (PLM), including computer-aided design (CAD), computer-aided manufacturing (CAM) and computer-aided engineering (CAE); engineering design tools for both discrete and process industries; Industrial Internet of Things (IIoT); advanced analytics for production systems; digital twin; and virtual simulation.
Tell us about state-of-the-art simulation-software technology.
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: Simulation-software technology is an integral component across the entire design/build/operate/maintain lifecycle. Traditional CAE applications, along with advanced simulation platforms enable engineers, scientists, manufacturers, builders and even consumers to virtually simulate the physical world to test, validate, optimize and virtually experience our products, systems and environment.
Also read: Simulation sets the stage
The simulation-software market has significantly expanded in scope to include many industries and areas of science. This includes everything from communications, automotive, aerospace, consumer electronics, military systems, transportation systems, smart buildings and cities, industrial controls, pharmaceuticals and biotech.
Scientists and researchers are able to simulate at the molecular level virtually, allowing them to create new compounds for drugs and new materials for various industries. Designers can plan and create 3D virtual cities and infrastructure for the next generation of smart cities. Manufacturing engineers are now able to create and fabricate parts by creating new materials specifically for additive manufacturing and design shapes and functions that could never be made using conventional methods. All of this is enabled by advanced 3D simulation tools that are transforming science, industry and our physical environment.
What have been the biggest improvements to simulation-software technology in the past five years?
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: Artificial intelligence (AI) and machine learning (ML), generative design, digital transformation, hyper scaled simulation, and digital-twin simulation. One of the most significant improvements is what I would call the democratization of simulation. Advanced simulation platforms are designed to accommodate non-subject matter experts. That is, designers can use simulation tools for complex testing, such as finite element analysis (FEA), computational fluid dynamics (CFD), multi-physics, electromagnetics and systems integration, that required simulation experts before. Additionally, with the emergence of the digital twin across multiple industries, simulation technology providers are offering comprehensive tools to build digital-twin applications, merging the virtual world with the physical world.
What’s the most innovative or efficient simulation-software technology application you’ve ever seen or been involved with?
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: There are multiple areas of new innovations being applied to simulation applications. AI-powered generative design applied to simulating the most efficient design for additive manufacturing is one. Designers can render designs based on fit, form and function parameters and additionally include requirements for the part to be manufactured using additive-manufacturing (AM) methods. AI algorithms will produce a design specifically for AM, where the part is light-weighted, uses more advanced materials and even exceeds functional requirements. The manufacturing engineer can build simulations of the complete manufacturing process, including fixtures and virtual dynamic simulation of the 3D printing machine.
How has simulation-software technology benefitted from remote connectivity and networking?
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: A typical simulated test application for FEA, CFD or multi-physics can be very computing-intensive. The design must be converted to large mesh models to do product testing. Many smaller engineering houses don’t have the in-house computing resources for large scale CAE testing, often requiring many hours of computing time. By using cloud-based computing resources, they can upload and run their test applications often in a matter of minutes, rather than many hours, saving valuable design/test time. Also, engineering organizations can share simulations remotely with other engineering groups.
Can you explain how improvements in simulation-software design and production have impacted industrial applications?
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: Manufacturers can use virtual simulation tools to simulate production lines, work cells, production machines, robots and automated assembly. These tools enable them to simulate the entire production process and validate their automation and control systems virtually before the physical systems are turned on. This is called virtual commissioning (VC) and is used extensively across manufacturing. The digital twin has taken this process to another level: Where VC is a one-time validation, implementing a digital twin is a continuous process-improvement method, merging virtual and physical systems using advanced analytics and AI.
How do simulation-software technologies figure into digital-twin platform models being used by manufacturers?
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: Advanced virtual simulation is a fundamental component of the digital twin where there is a merging of the virtual world and the physical world. While building virtual models to accurately simulate physical systems, production equipment and assets in the field is fundamental, it is just as critical to capture accurate physical configuration. When implementing, companies need to include physical context within the digital twin configuration. For predictive analytics or Industrial IoT to be effective, the context, or physical configuration, of the asset and system are required to know exactly what is needed to collect the relevant operational and performance data. Companies implementing any digital-twin project should begin by capturing and managing the actual physical configuration of the asset. Comprehensive digital-twin implementation platforms are designed to cover both the virtual simulation along with methods to capture physical configurations.
What future innovations will impact the use of simulation-software technology in manufacturing operations?
Dick Slansky, senior analyst, PLM & engineering design tools, ARC Advisory Group: While manufacturing-simulation tools are very advanced and enable manufacturers to virtually simulate entire production systems, including robotic work cells, machines and equipment, and production work flows, this simulation technology continues to evolve. Moving from virtual commissioning to full implementations of a digital twin is one aspect of this. The progression goes from condition monitoring to predictive analytics to prescriptive self-healing systems to ultimately completely autonomous factory systems. All of this requires advanced simulation tools to validate and implement, along with AI and ML algorithms to run the expert systems.
About the author: Mike Bacidore
Mike Bacidore is the editor in chief for Control Design magazine. He is an award-winning columnist, earning a Gold Regional Award and a Silver National Award from the American Society of Business Publication Editors. Email him at [email protected].
