Learn about the ways in which a digital twin is used today to help design better solutions.
- In today's hypercompetitive environment, there's pressure to develop and bring to market products faster, to identify efficiencies and how they are built, and to incorporate innovations in design and features. This is particularly true of highly sophisticated machinery and other complex systems, including buildings and cities. In the new product introduction, or NPI, process, the luxury of spending months and even years designing an improved or new system seldom exists anymore. Being able to relatively quickly create a accurate, functioning virtual replica of a future system and test it under all manner of scenarios is highly desired and beneficial. This is the role of a digital twin in the design phase. In the past few decades, the tools available to a design engineer have improved greatly. Initially, system design was done by a highly skilled hand and then supported by protractors, compasses, and stencils. However, beginning in the late 1950s, electronic support for design arrived. The productivity of two-dimensional or 2D drawing quickly increased. In the 1960s, support for three-dimensional, or 3D models was introduced. Capabilities in electronically supported design closely aligned with the evolution of microchips and computers. In the 1970s, the notion of comprehensive computer aided design, or CAD, was introduced. In 1982, AutoDesk began selling AutoCAD, the first 2D CAD software made for personal computers instead of mainframes and mini-computers. This revolutionized and democratized all manner of system and product design. In the years that have followed, CAD software has become sophisticated and powerful. Remarkable design and collaboration can now be achieved as a result of high performance processors, including those focused on graphics, the availability of big data, fast global networks, massive storage, cloud technology, and artificial intelligence. Today, a design engineer can render a detailed 3D model, manipulate all or part of the model, and view from any perspective. Its operational behavior can be simulated and better yet, conceivably every exhaustive variant of environmental factors can be emulated. By extending 3D CAD with several additional capabilities, we get the tools for designing a digital twin. The software that powers a digital twin today is typically a collaboration platform. Multiple stakeholders in the design process can engage as necessary. For example, the use of model-based systems engineering, or MBSE, takes the emphasis off the traditional hierarchy complexity of documents and drawings. It does this by testing and validating system characteristics early with other engineers and stakeholders, enabling faster feedback on requirements and design decisions. Another important characteristic of a digital twin in modeling is the use of data to inform design. In particular, historical data can be fed into the model to simulate how it performs under the new design. Hypothetical data is also essential for predicting behavior later, in the physical system. Simulations can also be used to design not just the product, but the production line for manufacturing the product. The most state-of-the-art design processes are now supported by what's called generative design. In this approach, designers provide parameters, such as required materials, manufacturing methods, and cost constraints. The software then explores multiple permutations to generate several design alternatives. Simulations then test and learn from each alternative in order to determine what design works and what doesn't. We're beginning to see digital twins in the design phase used to form higher quality 3D printing, or additive manufacturing, too. Simulating a 3D manufacturing process can result in better outcomes as the impact on complex design and material choices can be known and refined in advance. So in summary, a digital twin in the design phase is used to more accurately predict the performance of a to be built product or system. It serves to verify and validate design choices. It provides design engineers with the confidence that the physical end result will meet expectations, avoid failure, and generally reduce risk. Finally, it's no surprise that when recently asked in a poll, organizations said that the biggest benefit of using a digital twin in the design phase was to ensure product quality.