I recently published a white paper that takes a closer look at the concept of a “Digital Twin,” and how it can be used to help close the loop between production and design. What follows is a brief extract from the paper. Those interested in reading the full paper can do so here.
Much has been written about the process of transferring the digital rendered designs to the shop floor so the right product is built. The challenge is that quite often what was designed isn’t actually built. Inevitably, issues occur whereby equipment doesn’t perform as planned, incorrect work instructions are used or user errors occur.
The Concept
A virtual, digital equivalent to a physical product, or a Digital Twin, was introduced in 2003 at my University of Michigan Executive Course on Product Lifecycle Management (PLM). At that time, digital representations of actual physical products were relatively new and immature. The information collected about the physical product as it was being produced was limited, manually collected and mostly paper-based.
Virtual products are rich representations of products that are virtually indistinguishable from their physical counterparts. The rise of Manufacturing Execution Systems (MES) has resulted in a wealth of data that is collected and maintained on the production and form of physical products. In addition, this collection has progressed from being manually collected and paper-based, to being digital and collected by a wide variety of physical non-destructive sensing technologies.
Three Parts to the Model
The Digital Twin concept model, as illustrated above, contains three main parts: a) physical products in Real Space, b) virtual products in Virtual Space, and c) the connections of data and information that ties the virtual and real products together. In the decade since this model was introduced, there have been tremendous increases in the amount, richness and fidelity of information of both the physical and virtual products.
On the virtual side, we have much more information now available. Numerous behavioral characteristics can not only visualize a product, but can be tested for performance capabilities. On the physical side, we now collect much more data about the physical product. Actual measurements from automated quality control stations, and data from the machines that produced the physical part, is now readily available to understand exactly what operations, at what speeds and forces, were applied.
Unifying the Virtual and Real Worlds
The amount and quality of information about the virtual and physical product have progressed rapidly in the last decade. The issue is that the two-way connection between real and virtual space has been lagging behind. Global manufacturers today either work with the physical product or with the virtual product. Historically, we have not developed the connection between the two products so that we can work with both of them simultaneously. This shortcoming, however, may soon go away.
In order to deliver the substantial benefits to be gained from this linkage between virtual and physical products, one solution is to have a Unified Repository (UR) that links the two products together. Both virtual development tools and physical collection tools could populate the Unified Repository, creating a two-way connection between the virtual and physical product.
On the virtual tool side, design and engineering would identify characteristics, such as dimensions, tolerances, torque requirements, hardness measurements, etc., and place a unique tag in the virtual model that would serve as a data placeholder for the actual physical product. Included in the tag would be the as-designed characteristic parameter.
On the physical side, these tags would be incorporated into the MES in the Bill of Process creation at the process step where they will be captured. As the processes are completed on the factory floor, the MES would output the captured characteristic to the UR.
The final step would be to incorporate this information back into the factory simulation. This would turn the factory simulation into a factory replication application. Instead of simulating what should be happening in the factory, the application would be replicating what actually was happening at each step in the factory on each product. Many interesting use cases could then be possible by leveraging this digital twin, which could then contribute to improving overall manufacturing excellence.
To read about these specific use cases, as well as further details on this concept, read the rest of the paper here.
Dr. Michael Grieves has published several books on this topic, which can be found here.
