An iterative MILP-based approach to automated multi-product multi-stage manufacturing systems

An efficient MILP-based approach is presented to solve flow shop scheduling problems in automated manufacturing systems. The problem comprises complex production constraints and stringent storage policies in a multiple product multistage batch process. Automated transfers accross the entire system, recicle flows and different production recipes are also considered in the process scheme. The proposed decomposition approach was able to solve the entire problem in a sequential manner by dividing it into two major stages that are iteratively solved to find near optimal results with an acceptable CPU time. The effectiveness of this method is tested and compared with a monolithic MILP formulation by solving a real-world problem.