An optimization tool for operational tolerances allocation, work in process inventory minimization, and machines assignment in a discrete part manufacturing environment

In the last two decades, many researchers have addressed the superior system performance resulted from the integration of process planning and scheduling functions. However, most of the published solution methods in this field fall short in three accounts. First, while integrating with scheduling, they ignore the checking of process planning feasibility with respect to tolerances allocation. Thus, operational tolerances may stackup beyond the blue print tolerances making the process plans infeasible. Second, they ignore the machines capabilities during the integration modeling which make these solution models practically inapplicable. Third, they focus on time consideration, such as makespan or lateness, and do not consider manufacturing cost related to operations-machines assignment. This paper presents an innovative model for the integration of process planning and scheduling in a job-shop environment. The model simultaneously serves three purposes: allocating operational tolerances while minimizing its manufacturing cost, minimizing the work in process inventory, and figuring the operation-machine assignments. The preemptive-goal programming method is used to solve the proposed multiobjective non-linear mixed integer model, and an implementation example is presented to demonstrate the effectiveness of the proposed modeling approach.