An emergent synthesis approach to simultaneous process planning and scheduling

Optimality of a process plan and a production schedule frequently conflict. It is difficult to determine a proper plan that meets both objectives simultaneously. This paper proposes a new simultaneous process planning and scheduling method to solve dilemmas posed by such situations using evolutionary artificial neural networks based on emergent synthesis. The effectiveness of the proposed method is confirmed by solving a benchmark problem, thereby demonstrating high productivity resulting from role-sharing among machines. Results also show that the proposed method is applicable to more realistic problems including larger volumes of products and production demand fluctuations.