It seems of late that every technology or manufacturing event one attends includes some discussion of “digital twins” and their potential. CAD and CAE aficionados alike will say, accurately, that virtual modeling of products has been present in design teams and engineering work groups for years. So what’s different about today’s discussion on virtualization and digital twins?
The difference is a flexible level of content one can apply to the virtual model of a product, building, or entire manufacturing plant as well as the ability that exists to analyze and share these rich, multi-layered models with a global team, within and outside of engineering. Although today you cannot buy a digital twin solution per se, there are still investments beyond CAD and CAE you can and should make to get closer to one. Third platform technologies cloud, mobile, analytics, and social business enable digital twins across value chains and are increasingly prevalent at manufacturers today – according to our research growing at 13% CAGR. The potential result of this investment and democratization of modeling is better collaboration, improved quality, faster development, and faster time to market.
How far into an organization can the digital twin go? There are many potential layers. For products, production, plants, and robots. Virtual models of products are nothing new for designers and engineers – what’s new is the broadening usage of simulation upstream to ideation for new product development and downstream to manufacturing for modeling of processes and the layout of a plant. Having a visual representation of the idea, product, or manufacturing line, with the appropriate level of content for users, is where the real value of a digital twin comes to light. We think of the digital twin as the vehicle for communication across a product innovation platform – leveraging simulation and visualization technology to improve the innovation, collaboration, and quality improvement process among suppliers, partners, and internal stakeholders.
Better decision support and closed-loop quality are two of the biggest reasons why digital twins of products, or at least a visualization tool, are important to manufacturers today. Having this living, digital model that ties big data analytics with statistical analytics from the product or plant floor improves communication and expedites action, leading to faster time to market and resolution of quality issues. Another reason is manufacturing optimization: one large automotive manufacturer spoke at a recent event about the importance of using ergonomic simulation to ensure proper training and usage of shop floor equipment and manufacturing lines.
Digital twins can be the communication mechanism for analytics, which is (rightfully so) the current hot area in PLM. Connected products and processes provide a gold mine of information for product and service innovation improvement – but how do you communicate those nuggets of information to service technicians, or quality management, or engineering? This communication bridge, if you will, has not been built at most manufacturers today – the innovation platform may be in place, as is the connected product, and flexible manufacturing line, but not the analytic, visual tool for decision support. Hence the rampant discussion about the potential of digital twins.
So are digital twins necessary for innovation transformation? Yes. Essentially, digital twins are the extended application of simulation and visualization throughout a digitally transformed organization, for better communication and collaboration.
I’ll continue to look at this emerging trend in product design, engineering, and manufacturing. In the meantime, as always I welcome your thoughts at firstname.lastname@example.org.