Semi-Generative Macro-Process Planning For Reconfigurable Manufacturing

Global competition and frequent market changes are challenges facing manufacturing enterprises at present. Manufacturers are faced with new unpredicted modifications at the part design level, which require increased functionality at the system design level. Reconfigurable Manufacturing Systems (RMS) addresses this situation by providing the exact capacity needed when needed. Process planning concepts and methods should be developed to support this new manufacturing environment. Variant process planning systems with their rigid definition of the boundaries of part families do not satisfactorily support Reconfigurable Manufacturing Systems. A semi-generative macro process planning system has been developed and is reported in this paper. Precedence graphs, which depict the precedence relationships between features/operations, are reconfigured by adding and removing nodes. The problem of generating optimal macro-level process plans is combinatorial in nature and proven NP-hard. Hence, a random-based heuristic based on Simulated Annealing is tailored for this problem. Finally, a realistic case study is presented to illustrate the proposed methodology. A family of single-cylinder front covers is used. The proposed method produced good quality optimal solutions and is proven efficient in terms of computation time as demonstrated by the obtained results.