To manage increasingly complex manufacturing systems, involving material flows across numerous transporters, machines, and storage locations, the semiconductors and display fabrication industries have implemented automated material handling systems (AMHSs). AMHSs typically involve complex manufacturing steps and control logic, and digital twin models have emerged as a promising solution to enhance the visibility, predictability, and responsiveness of production and material handling operation systems. However, digital twins don’t always fully reflect reality, potentially affecting production performance and may result in delays.
Calibration framework for digital twins improves prediction accuracy
