Heterogeneous demand–capacity synchronization for smart assembly cell line based on artificial intelligence-enabled IIoT

An assembly cell line (ACL) is one type of cell production practice, derived from the Toyota Production System in the electronics industry and rapidly spread to other fields. In this mode, the conveyor line is divided into assembly cells (ACs) where various parts and tools are placed closer to the workers, enabling them to perform multiple tasks throughout an entire product assembly from start to finish. In this way, ACL allows manufacturers to rapidly configure an appropriate heterogeneous capacity to match heterogeneous demands with diversified customer orders in the high-mix, low-volume (HMLV) environment, which is the spread of the Just-In-Time (JIT) philosophy from the material level to the organization level. However, due to the lack of real-time information sharing in the ACL workshop, especially the up-to-date individual capacity and asynchronous production processes within and between ACs, it is hard to coordinate the heterogeneous capacities of ACs to meet the HMLV demands in a complex manufacturing environment with uncertainties. In this context, this paper proposes a heterogeneous demand–capacity synchronization (HDCS) for smart ACL by using artificial intelligence-enabled IIoT (AIoT) technologies, in which computer vision (CV) is applied for up-to-date capacity analysis of ACs. Based on these, an AIoT-enabled Graduation Intelligent Manufacturing System (GiMS) with feedback loops is developed to support real-time information sharing for the synchronous coordination of the ACL operation, which also provides the basis for the implementation of the HDCS mechanism through a rolling scheduling approach. Finally, a real-life industrial case is carried out by a proof-of-concept prototype to verify the proposed approach, and the results show that the measures on shipment punctuality and production efficiency are both significantly improved.