Before we can explore the full functionality and benefits of digital twins, it is important to understand exactly what digital twins are and how they can be applied throughout the operational lifecycle. A digital twin is, as the name suggests, a virtual model of a physical object or system that can be used to simulate the behavior of that object or system to better understand how it works in real life.
At present, the most commonly used type of digital twin is a product digital twin. These twins allow product development teams to create a complete digital representation of an item, even before a physical version exists. Engineers can build digital twins to the mechanical, electrical, and software requirements of a product in development and simulate its performance under various conditions as the work to optimize design. Digital twins also allow engineering teams to improve, among other things, the reliability, manufacturability, testability, and safety of their products by “designing for x.”
Digital twins can also replicate shop floors and entire supply chains. Just as product digital twins represent the behavior of a specific item, these digital twins can simulate how complex systems operate. This gives stakeholders powerful insight into how effective these systems are and even helps companies redesign them to optimize their efficiency.
In addition, digital twins can mirror a company’s service process, giving them visibility into how equipment performs in the field and allowing them to predict service and maintenance needs.
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Dr. Che is a Professor and the Director of the School of Information Security and Applied Computing in the GameAbove College of Engineering and Technology at Eastern Michigan University. Before his academic career, he worked as a system and network engineer in the IT industry for approximately 20 years. Dr. Che received his BE in Electrical Engineering and ME in Computer Engineering from Zhejiang University, his MS in Software Engineering from Bowling Green State University, and his Ph.D. in Computer Science from Wayne State University. His main research interests are cybersecurity and computational intelligence. He is the author and co-author of multiple research publications and holds several IT and Cybersecurity professional certifications.
