Integration of Process Planning and Production Scheduling Based on A Hybrid PSO and SA Algorithm

Process planning and production scheduling play important roles in manufacturing systems. In this paper, a fuzzy inference system (FIS) in choosing alternative machines for integrated process planning and scheduling of a job shop manufacturing system are proposed. Machines are chosen based on the machine's reliability characteristics. This ensures the capability of the machine in fulfilling the production demand. In addition, based on the capability information, the load for each machine is balanced by using the particle swarm optimization (PSO). Simulation study shows some promising results in integrating production capability and load balancing during scheduling activity. There are few objectives could be optimized individually or simultaneously. This gives a choice to the scheduler in determining which objective is the most important