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How the Digital Twin Boosts Smart Manufacturing
Asset lifecycle management was one of the first areas of focus for digital twin implementation (ALM). Maintaining assets in the field has traditionally been a time-consuming and expensive task, but it is crucial to the uptime of equipment and systems.
Fremont, CA: In recent years, a number of technologies have emerged that are critical to the advancement of smart manufacturing as well as the Industrial Internet of Things (IIoT). While all of these technologies are altering the face of manufacturing today, according to recent research, the IIoT, connected smart assets, and, in particular, the digital twin, are having the most immediate and significant impact on how companies implement smart manufacturing.
The fundamental concept of the digital twin is not novel. It entails combining virtual engineering models with physical products or equipment in an environment that allows for change and enhancement of the product as designed and as-built. Nevertheless, as enabling technologies advance and evolve, there is a renewed emphasis on the implementation of the digital twin and the associated benefits that can be realized. Manufacturers can decrease the time and cost associated with assembling, installing, and validating factory production systems by utilizing digital twins that represent the product and production systems. Furthermore, implementing digital twins for asset management typically provides quantifiable advantages for field equipment maintenance.
Asset lifecycle management was one of the first areas of focus for digital twin implementation (ALM). Maintaining assets in the field has traditionally been a time-consuming and expensive task, but it is crucial to the uptime of equipment and systems. Maintenance technicians can now use technologies such as augmented reality (AR) to access virtual engineering models and overlay these models over the physical equipment on which they are performing maintenance, using specialized AR goggles or glasses. This enables them to use the most accurate and up-to-date engineering, assisting in the efficient performance of the correct maintenance and performance specifications. These same maintenance methods, which are based on the integration of virtual and physical environments, can be used to maintain factory production systems, machines, and work cells.
Furthermore, virtual simulations of products, machines, production systems, and work cells can be used to test and validate physical systems prior to assembly and installation. Furthermore, virtual commissioning of production automation, a well-established technology and process, is blending with the broader scope of the digital twin. Virtual commissioning is typically used to validate an automated production system once. The digital twin, on the other hand, represents an ongoing analytical and optimizing process that occurs in real-time.
It is becoming clear that digital twins will be utilized throughout the product and process lifecycle to simulate, predict, optimize, and maintain products, assets, and manufacturing systems rather than developing physical prototypes and test equipment. Today, a sizable proportion of companies and organizations implementing IIoT use, or plan to use, some form of a digital twin as an important component of a predictive analytics strategy.