A data-driven smart management and control framework for a digital twin shop floor with multi-variety multi-batch production

To solve the problems of strong uncertainty, dynamics, and high complexity during the operation process in a discrete manufacturing shop floor that produces a variety of variable-volume products, a data-driven smart management and control framework of a digital twin shop floor (DTS) is proposed. Its implementation process is analyzed. Five key tasks are illustrated in detail: (1) the construction of a shop floor digital twin (DT) model from the multi-dimensional multi-scale perspective; (2) data acquisition and management technology in a DTS; (3) the real-time data-driven synchronous modeling of the shop floor operating status; (4) the model- and data-driven online prediction of the shop floor operation status; and (5) the multi-agent-based operation decision of a DTS. In addition, for products that are complex to produce on the assembly shop floor, a DT-based smart management and control system named the DT-VPPC is developed. The effectiveness of the proposed method is verified by a specific application example on an assembly shop floor.