摘要：This paper explores the current roles and future potential of augmented reality and cognitive capabilities for digital twins. Machine learning models are increasingly powering digital twins because of their ability to capture the complexity of the physical world with fidelity. However, machine learning models fall short when predicting beyond the experience of past data. Today's production systems and supply chains are navigating disruptions that they have not experienced previously. This research is motivated by the necessity to explore methods for managing large-scale disruptions outside the “learned” experience of both the data and the control strategy of the production system. To explore the interaction of human and machine intelligence in managing disruptions, this paper builds on ongoing work by the authors to develop a framework integrating production and logistics processes that employs a machine learning-enabled digital twin to ensure adaptive production scheduling and resilient supply chain operations.
关键词：Digital twin;Augmented reality;Machine learning;Cognitive digital twin;Production
