Digital Twins are all the rage. They seem to be more popular than Pokemon Go was in July of last year. Nearly every article, blog post, or story about Digital Transformation or the Industrial Internet of Things (IIoT) mentions Digital Twins. The term Digital Twin has been around since 2003 when Dr. Michael Grieves introduced the concept. Since its introduction, the term Digital Twin has evolved considerably from its rather engineering design-centric roots.
Today, the industry refers to any digitized version of virtually anything physical as the Digital Twin of that item. Yet, exactly what that Digital Twin represents and how the information is used can vary widely. With Google getting almost 3 Million hits on the term in less than a second, it is no wonder there is so much confusion about Digital Twins. Over the next series of blog posts, LNS Research hopes to provide some clarity as to how we see Digital Twins impacting manufacturing and asset-intensive industries. In this first post, we will explain the differences in how we see the Digital Twin concept impacting products versus assets.
PLM: The Origin of the Digital Twin
Product lifecycle management (PLM) is the discipline of taking an idea through to the actual realization of that idea into a product and then ultimately even its disposal. PLM is the evolutionary outgrowth of computer aided engineering and/or design (CAE/CAD) just as enterprise resource planning (ERP) is the evolutionary outgrowth of manufacturing resource planning (MRP II). PLM is product-centric. When Dr. Grieves introduced the Digital Twin concept in 2003, it was also product-centric.
As little as two years ago, most of the Digital Twin dialog in the market was about smart connected products; focused on products sold into the consumer market. Embraced by the major PLM providers, the Digital Twin discussion focused initially on the product design activity, then the manufacturing process activities, and finally expanded to incorporate product feature engineering for expanded value creation.
The value of the Digital Twin was seen initially in using virtual prototyping to reduce product development costs. Following that was assessing manufacturability to reduce production costs, and in creating a virtual product to aid in customer acquisition and market share development.
Smart Connected Assets Demand More From Digital Twins
Smart connected products were the final Digital Twin evolutionary step from the PLM perspective. The value of the Digital Twin was focused on the product after delivery to the consumer. An example was in servicing the products such as Tesla’s ability to update the functionality of their vehicles while they are parked in a customer’s garage overnight. Another aspect of the Digital Twin was the concept of gathering performance and usage data to refine product design of subsequent models; another PLM-centric use case. For more see Michael Porter’s Harvard Business Review article on Smart Connected Products.
It soon became obvious that the ideas around servicing smart products also applied to extremely complex products like MRI machines, locomotives, or mining excavators. The next logical step was to extend the Digital Twin concept to any physical asset that had sufficient information about its performance available. Enter the Industrial Internet of Things (IIoT). With the IIoT almost any physical asset is capable of being made “smart, ” and the value of the Digital Twin suddenly becomes different. While having a Digital Twin of a new refinery as it is being constructed can certainly aid in the design and construction process, the real value is delivered over the next 30-50 year of life of that asset. It becomes about being able to more effectively maintain that asset, operate it more efficiently, and reduce the operational risks associated with its operation.
This Smart Connected Assets Digital Twin is a subset of the Smart Connected Product Digital Twin but has special needs that go beyond what the broader category requires. Unlike smart products that have a twin “at birth” as a result of their inherent design, the twins associated with smart connected assets often may be better thought of as clones more than twins. They are both built from the DNA of the asset as it currently exists and, in many cases, long after its original construction. Because of smart connected asset Digital Twins' complexity and the long lives with ongoing repairs and modifications, they are sometimes more likely to be one-offs, with constantly evolving characteristics.
These twins are more complex than PLM-centric product twins and will require far more processing capabilities to use effectively. In the next blog post, I will expand on the functionality and capabilities LNS believes will be critical elements of these asset-centric Digital Twins.