Developing an Integrated Quantity and Quality Approach for Improving the Performance of Multistage Manufacturing Systems

Abstract

Improving the performance of manufacturing systems is of great importance for industrial manufacturers to survive the fierce competition brought about by globalization. However, such improvement becomes challenging because of the various uncertainties present in the system. Uncertainties such as machine failures, imperfect product quality, random processing times and other system configurations, such as, varied inspection fraction, finite buffers and possible rework loops, further complicate the performance analysis. This thesis proposes analytical methods for modeling such multistage systems. These methods are used to calculate various quantitative and qualitative performance measures. Based on these methods, the author further explores a variety of managerial problems for improving performance, such as continuous sampling plans, bottleneck identification, inspection machine location and buffer space allocation.