Integrated Approach of Process Scheduling and Planning Based on Combining Fuzzy Knowledge Base and Meta Heuristic Method

Process planning involves determining the most suitable and efficient manufacturing (assembly) processes and their sequence in order to produce a product (part). These processes should be compatible with required attributes in the product design documentation. In this paper, process planning and scheduling optimization is done through tacking qualitative parameters which are effective on job shop and flexible system. Fuzzy Inference System and Meta-heuristic algorithms with multiple objectives and goal functions are used to solve the problem. Objective functions include minimization of cost and time of processing parts and maximizing the utility of the process design. Results from solving numerical example, show that simulated annealing algorithm has better efficiency than imperialist competitive, particle swarm and bee colony algorithms.