Process planning and scheduling integration with optimal rescheduling strategies

Abstract

It is of more practical significance to carry out research on the integrated process planning and scheduling/rescheduling (IPPSR) to achieve a global improvement for the performance of a manufacturing system with sustained pursuit and various uncertainties. In this paper, a framework and a unified dynamic rescheduling model for IPPSR with three typical types of situations normally encountered in a production system, i.e. arrival of new jobs, machine breakdown and order cancellation have been constructed. Meanwhile, an improved evolutionary algorithm (IEA) for the integrated process planning and scheduling (IPPS) to generate an optimal initial scheduling plan has been developed. In order to improve the performance of the algorithm for IPPS and facilitate the extension of it to rescheduling situation, new genetic representation for the scheduling plan combined with process plans and corresponding genetic operators are developed. Based on the dynamic rescheduling model and initial optimised result, the integrated rescheduling strategies for the above three types of situations have been developed. In order to verify the feasibility and performance of the proposed strategies, experimental studies were conducted and comparisons were made for different performance measures; the results show that the proposed approaches not only provide more effective result for IPPS but also for integrated rescheduling with the above three types of uncertainties.