How to Gain a Competitive Edge with the Digital Twin

Abstract

Abstract With the move towards IIoT and the Digital Age, companies in the process industry are looking to digitalize processes. One critical element in this development is the increased adoption of the Digital Twin (DT), which is being deployed in all phases of a product, plant, or process lifecycle from design to operations to maintenance. A DT is a virtual representation of a physical product or process used to understand and predict the physical counterpart's performance characteristics. They are used throughout the product lifecycle to simulate, predict, and optimize the product and production system before investing in physical prototypes. The concept is not new. For more than 30 years, product and process engineering teams have used 3D renderings and process simulation to validate manufacturability. What is new, however, is that several factors have now converged to bring the concept of the DT to the forefront as a disruptive trend in the process industry. This will be demonstrated using relevant use cases featuring organizations that have seen increases in efficiency improvements after employing digitalization and the DT By incorporating simulation, data analytics, and machine learning, the DT is able to demonstrate impacts of usage and training scenarios in a virtual setting. This enables identification of any potential issues in the design phase as opposed to the commissioning phase as is very common today. Process and sensor data from physical objects are collected and analyzed to determine real-time performance and operating changes over time. Feeding this data back into the product lifecycle, the DT is continuously updated to reflect changes to the physical counterpart. This creates a closed-loop of virtual feedback that makes products, production, and performance optimization possible at minimal cost.