CAPABILITY INDICES FOR INDUSTRIAL PRODUCTION PROCESS: A COMPARISON OF CLEMENT'S AND PERCENTILE APPROACHES

Abstract The concept of process capability, rooted in statistical process control, emerged as a response to the growing need for systematic approaches to quality management. As industries evolve and consumer demands become more stringent, the need for effective tools to assess and improve process capability becomes increasingly apparent. Hence, this study delves into the context surrounding capability indices and the methodologies employed in evaluating industrial process capability when process data is not normal. In real life, industrial processes are not normally distributed and may contain outliers, thereby; using traditional process capability may leads to wrong conclusions. The aim of this study is to comprehensively evaluate and compare the Clement’s, percentile, and Z-score approaches for assessing industrial process capability. Through empirical analysis and theoretical examination, the study would analyze and compare the practical applicability of the Clement’s, Percentile, and Z-score approaches using two real-life industrial process data. The empirical evaluation of the methods would be conducted to assess their effectiveness and reliability. The appropriate process capability approach to the two industrial processes would be recommended. Keywords: Clement method, Non-normal data, Percentile method, Probability Distribution, Process Capability Index.