Automation of Decision Support in Simulation-Based Digital Twins in Manufacturing: A Survey

Simulation-based Digital Twins are increasingly used for decision support in manufacturing. This paper examines peer-reviewed studies to evaluate how, and to what extent, decision support is automated in existing Digital Twins implementations. We analyze each implementation across six dimensions: (i) the domain of application, (ii) the main goal, (iii) the methodology used to develop or extract the Digital Twin model, (iv) the decision support methodology, (v) the level of automation, and (vi) the main gaps and limitations of the implementation. Across the reviewed studies, automation remains partial; no implementation achieved fully autonomous end-to-end operation of the Digital Twin. Building on this analysis, we identify key enablers and barriers to automating decision support in Digital Twins, with a primary focus on the manufacturing domain. Based on these findings, we outline research priorities to help close the decision support automation gap in Digital Twins, emphasizing the importance of human oversight, risk-aware control, and data privacy and security. In addition, we emphasize the importance of generalizability and scalability, and the evaluation of decision outcomes and Artificial Intelligence components. ... mehrOverall, this review clarifies the current state of automation in decision support within Digital Twins and highlights targeted areas for future development toward fully autonomous decision support in Digital Twins.