An optimization-based system for adaptive planning in a discrete part manufacturing environment

Abstract

An optimization-based decision support tool that can be used for adaptive planning in a discrete part manufacturing environment is presented in this paper. In adaptive planning, the process plan is modified based on the status of the manufacturing system to achieve a higher level of success in the production of parts. Modifications to the process plan could be in the form of routing changes, operational tolerance adjustments, or generation of a new process plan. The mathematical model proposed in this paper covers the first two cases. Solution to the mathematical model generates operational tolerances, assigns machines to operations, provides a measure of process plan feasibility, identifies sources of infeasibility, recommends alternative machines, and identifies the required process capabilities to make an infeasible process plan feasible. Experimental results confirm the effectiveness of the proposed model.