Solving integrated process planning and scheduling problem with constraint programming

Abstract

Process planning and scheduling are two important manufacturing functions which are usually performed sequentially. However, due to the uncertainties and disturbances frequently occurring in the manufacturing environment, the separately conducted process plan and shopfloor schedule may lose their optimality, becoming ineffective or even infeasible. Researchers have considered the potential of integrated process planning and scheduling (IPPS) to conduct the two manufacturing planning activities concurrently instead of sequentially. That is, to integrate process planning with dynamic shopfloor scheduling to cope with the realtimeshopfloor status. The IPPS problem is very complex and it has been regarded as an NP-hard problem. Many researchers have attempted to solve the IPPS problem with intelligent approaches such as meta-heuristics and agent-based negotiation. In this paper, a constraint programming-based approach is proposed and implemented in the IPPS problem domain. Constraint programming (CP) features great modeling capabilities to reflect complex constraints of a problem, and there is a great potential for CP to be used to solve IPPS problems. The approach is implemented and tested on the IBM ILOG platform, and experimental results show that the CP can handle the IPPS problem efficiently and effectively.