Variation management of key control characteristics in multistage machining processes considering quality-cost equilibrium

Abstract

In multistage machining processes (MMPs), variations from key control characteristics (KCCs) continue to propagate and eventually accumulate to deviations in key product characteristics (KPCs). Therefore, the variation control of KCCs is significant to ensure the final product quality. In this paper, a variation management framework for KCCs in MMPs is established to address this issue. The new concept of variation management consists of process-oriented tolerancing and maintenance planning, and the optimal variation management strategy for each KCC is assigned based on its impact to the manufacturing system. The proposed framework deduces corresponding KCC variation distributions for previously unresearched locating schemes, thereby expanding the application scenarios of this method. For the quality specification constraints, geometric tolerances are integrated for the first time beside traditional dimensional tolerances, which expand the error scale of quality control. The modified Chebyshev goal programming (MCGP) approach is adopted to find the equilibrium point between quality and cost effectively. The superiority of the proposed method is verified by a case study of an automotive engine cylinder block MMP. The results show a remarkable improvement on the manufacturing system performance in terms of quality and cost.