Abstract
The aim of this study is to propose a Six Sigma multiobjective optimization (SSMO) framework to improve online process control when multiple objectives are present. The proposed framework is divided into three steps: an improvement phase, online process control, and online optimization for multiple objectives. It integrates a process optimization routine with a DMAIC Six Sigma framework to provide the decision-maker with a set of compromise solutions that can be used to balance the set of process performance objectives simultaneously and maintain process stability. For a proof of concept, the approach was applied to an inventory problem to correct the differences between demand and on-hand and/or received replenishment inventory. It delivers a simultaneous response to maintain two conflicting objectives to be statistically in control. These conflicting objectives are to minimize inventory and ordering costs The results reveal that the integration of multiobjective optimization with the Six Sigma methodology reduces the defects per million opportunities by more than 50%.