Congratulations, it’s Twins! How to get the Most from Your Digital Twin in the Design Phase
Engineering Excellence begins with the digital twin. A digital twin is a complete 360° digital representation of a physical asset, i.e., a pump, motor, turbine, or an entire plant. By creating digital twins of physical assets, data generated by the asset during its design and operational life is collected, visualized and analyzed, enabling unified life-cycle simulation.
During the design phase, the digital twin allows for the analysis of processes, equipment and operations through multiple simulations for optimal safety, reliability and profitability. At the concept phase, fast evaluation of design alternatives are analyzed and continuously iterated through variable specifications allowing integrated asset modeling of interacting but separate systems. Each iteration provides a more complete data-set aiding in agile software development. Here’s how each twin is used:
Once assets are deployed and facilities commissioned, the digital twin continually updates itself with ongoing operational and process data. During operational stages, variations from optimal process and asset design are captured during run-time, and the digital twin updated with this information. Given the current state of an asset, the digital model uses predictive learning technology to proactively identify potential asset failures before they occur. Using artificial intelligence with advanced process control, control strategy design and process optimization, the necessary variations from process and asset design are fed back to the engineering stage of the lifecycle enabling a complete and efficient digital value loop.
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Livia Wiley is the Sr. Product Marketing Manager for SimSci software at AVEVA. She is primarily responsible for expanding SimSci’s brand awareness and marketing of its design, simulation & training, and optimization software. She has more than 20 years of experience in process simulation; assisting clients model, troubleshoot, and optimize their processes through technical and economic studies. Prior to joining Schneider Electric in 2014, she worked for suppliers of process simulation and automation technology, including Honeywell, Aspen Technology, and legacy SimSci. Livia holds a B.Sc. in Chemical Engineering from Queen’s University, and a M.Eng in Chemical Engineering from the University of Houston.