Editorial: Special issue on advanced optimization enabling digital twin technology

Excerpt

A digital twin is a real-time digital/virtual representation of a physical product or process. A key feature of digital twin technology lies in its ability to produce “individualized” digital models of a physical product or process. These digital models are constantly updated at regular or irregular intervals with data and customized to reflect the real-time characteristics of individual units (actual realizations of the physical product or process). A unique benefit of having these unit-specific models as opposed to population average models is that decisions (e.g., maintenance and control) can be optimized for each unit. As digital twin technology emerges to improve decision making, new and challenging optimization problems arise at the forefront of multiple engineering disciplines, such as model-based design, smart manufacturing, industrial IoT, machine learning (ML), and predictive maintenance. Adopting the digital twin concept on an industry scale requires developing innovative optimization solutions that leverage data from sensors and inspections (physical-to-digital) to deliver actionable insights to decision makers (digital-to-physical), effectively closing the digitalization loop. Some key advantages include the ability to customize control and maintenance actions to the real-time characteristics of individual units and the potential to enhance the design of future-generation products. …