Contributions in statistical process control for high quality products

Abstract

This dissertation is focused mainly on the study of Statistical Process Control (SPC) techniques for high yield processes, and includes some topics on high reliability systems. It deals with the statistical aspects of establishing SPC in high yield processing, and providing insight and promising opportunity for future research on high reliability systems. The objective is to study the theory and practice of SPC for its use in the modern manufacturing environment, and establish a new research area on the topic of high reliability systems. Some new results in high yield process control chart - Cumulative Count of Conformance (CCC) chart - are presented, including the CCC chart with sequentially estimated parameters and the effects of parameter estimation in implementing CCC. The parameter estimation is presented and the run length distributions of the CCC Charts with sequentially estimated parameter are derived in order to assess the performances of the charts together with the proposed scheme for Phase I CCC Chart. The guidelines in establishing the CCC charts for both cases where process parameters are known or estimated are presented. In addition, the high yield process with sampling inspection is considered. A chain control scheme is proposed in order to monitor the process fraction nonconforming. The term High Performance System (HPmS) is defined and the roles of reliability tests in reliability improvement programs are highlighted. Besides, quality and reliability issues for high performance systems are discussed, paving the way for future research. A screening scheme for high performance systems is presented.