Analytical Methods for Performance Enhancement in Unreliable Multistage Manufacturing Systems with Imperfect Production

Abstract

To confront the fierce international and domestic competition, manufacturing companies are endeavoring to increase production rate, improve manufacturing quality, reduce inventory, cut down operational costs, and hence maintain competitive standing in the market. Performance enhancement is challenging in a multistage manufacturing system, because of the complex configuration and various uncertainties in the system. This thesis details a modeling framework for performance analysis of multistage manufacturing systems. This modeling framework characterizes the uncertain properties of manufacturing systems that undermine system performance, in particular: 1) machines are unreliable and may experience deterioration; 2) production is imperfect and defective parts are generated randomly. The modeling framework can be used to estimate a variety of quantitative and qualitative performance measures. These estimates may enable one to assess and improve the management of a multistage manufacturing system. A managerial issue investigated in this research is preventive maintenance, which is widely implemented in manufacturing systems for improving machine reliability. Although analytical models of single or two-machine systems with preventive maintenance have been proposed in the literature, similar study on multistage systems remains limited. Based on the modeling framework, the author presents an algorithm to determine the frequency of preventive maintenance on each machine of a multistage manufacturing system. Performing preventive maintenance at the frequency prescribed by the algorithm may avoid excessive or insufficient maintenance, resulting in improved production rate. In addition to machine unreliability, imperfect production may also substantially increase the cost of a manufacturing system. In order to mitigate the corrupting effects of defective parts generated due to imperfect production, the quality inspection of the multistage manufacturing system is also investigated in this thesis. An algorithm is formulated for determining the placement of inspection machines in such a system. With the inspection allocation scheme indicated by this algorithm, the quality of material flow in the multistage manufacturing system is improved. This may reduce the waste on processing defective parts and penalty resulting from defective parts shipped to customers. Based on the modeling framework, the author further explores the extension for multistage manufacturing systems with batch operations and generally distributed processing times. This extension makes it possible to model a wider range of real manufacturing systems.