Digital twin-based smart shop-floor management and control: A review

Abstract

Propelled by the latest advancements in information technology, shop-floor management and control (SMC) is transitioning towards a more intelligent paradigm, predominantly marked by data-driven insights and the integration of virtual reality. The digital twin (DT) stands out as a pivotal technology for the realization of cyber-physical systems, and its role in smart shop-floor management and control (SSMC) has attracted significant interest from both the industrial sector and academic circles. However, the application of DT in achieving SSMC remains diverse and lacks a structured methodology. In light of this, this review provides an in-depth analysis and discussion of the current state, limitations, and prospective trends of DT in SSMC. Initially, a DT-based SSMC framework is introduced to guide the subsequent literature review and thematic discussions. This is followed by an examination of DT-based SSMC research across four key dimensions: the development of shop-floor DT models, dynamic monitoring and forecasting of the shop-floor leveraging DT, DT-assisted shop-floor scheduling, and DT-driven production process control. The review culminates with an outline of challenges and future research directions for DT-based SSMC. This comprehensive review not only enhances researchers’ comprehension of SSMC but also offers a valuable reference for the continued application and integration of DT within this domain.