Production system configuration and layout planning for efficient manufacturing system design: An industrial case study

In recent years, the manufacturing industry has faced increasing challenges related to labor shortages and rising labor costs. One response to these challenges is the automation of production systems, which replaces part of the human workforce with equipment such as robots, machine tools, and conveyors. However, designing an automated production system remains a complex task, often requiring engineers to manually develop an optimal system configuration and layout that minimizes investment costs while satisfying constraints such as production demand, technological requirements, and limited floor space. The traditional approach, solving system configuration and layout planning separately, often requires numerous iterations when floor space is restricted, making it difficult to obtain feasible solutions within a practical time frame. To address this issue, this study applies a recent logic-based Benders decomposition approach to a real industrial production system configuration and layout planning problem, involving the design of a machining cell composed of robots, machines, and other resources. The recently proposed abstract model is extended to capture all practically relevant requirements, including detailed modeling of resources and manufacturing processes. A case study demonstrates how the optimization software can be integrated into the overall planning workflow and highlights the refinements made by human experts to adapt the automatically computed solution to fulfill all practical requirements. The results show that, compared to the conventional manual workflow, the proposed optimization approach and software tool reduced the required human design effort from 22 working hours to 4.5 h.