A mathematical programming model for constructing the confidence interval of process capability index Cpm in evaluating process performance: an example of five-way pipe

Abstract The process capability index Cpm can reflect process loss as well as process yield, thus is the most frequently used index for evaluating product quality in manufacturing industries. When evaluating the process performance, confidence intervals are often used for assurance with regard to the critical value of the process capability index. Unfortunately, sampling distributions of Cpm are obtained in a very complex way, which leads to difficulty in calculating the confidence interval of Cpm. Hence, this paper develops a mathematical programming model to construct the confidence interval of Cpm. Then for verifying the effectiveness of the proposed approach, the Monte Carlo simulation is used to find the coverage percentage. The proposed mathematical programming model can obtain the confidence interval of Cpm without complex statistical computations. Besides, managers can evaluate and monitor the process performance in an easy way. We also provide a case in which a five-way pipe process is presented as an illustration of how the proposed method is implemented.

[1]  Samuel Kotz,et al.  An overview of theory and practice on process capability indices for quality assurance , 2009 .

[2]  E. Ziegel Juran's Quality Control Handbook , 1988 .

[3]  Wen Lea Pearn,et al.  A PRACTICAL IMPLEMENTATION OF THE PROCESS CAPABILITY INDEX Cpk , 1994 .

[4]  Richard K. Burdick,et al.  Using Confidence Intervals to Compare Process Capability Indices , 2004 .

[5]  Kwok-Leung Tsui,et al.  A review and interpretations of process capability indices , 1999, Ann. Oper. Res..

[6]  Muhammad Aslam,et al.  Capability indices for Birnbaum–Saunders processes applied to electronic and food industries , 2014 .

[7]  Kerstin Vännman,et al.  Process capability plots—a quality improvement tool , 1999 .

[8]  Kuen-Suan Chen,et al.  Comparing the Capability of Two Processes Using Cpm , 2004 .

[9]  Chien-Wei Wu,et al.  Generalized confidence intervals for the process capability index Cpm , 2008 .

[10]  Shey-Huei Sheu,et al.  Enhancement of Axle Bearing Quality in Sewing Machines Using Six Sigma , 2010 .

[11]  A Bayesian approach to obtain a lower bound for the C pm capability index , 2005 .

[12]  Evdokia Xekalaki,et al.  A New Method for Constructing Confidence Intervals for the Index CPM , 2001 .

[13]  Youn Min Chou,et al.  Lower confidence limits on process capability indices. , 1990 .

[14]  Abbas Parchami,et al.  Confidence interval of generalized Taguchi index , 2013, J. Intell. Fuzzy Syst..

[15]  Evdokia Xekalaki,et al.  On the relationship between process capability indices and the proportion of conformance , 2016 .

[16]  Samuel Kotz,et al.  Process Capability Indices , 1993 .

[17]  Russell A. Boyles,et al.  The Taguchi capability index , 1991 .

[18]  Wen Lea Pearn,et al.  Capability measures for processes with multiple characteristics , 2003 .

[19]  Fred Spiring,et al.  Introduction to Statistical Quality Control , 2007, Technometrics.

[20]  Roger G. Schroeder,et al.  Six sigma: A goal-theoretic perspective , 2003 .

[21]  Kuen-Suan Chen,et al.  The communion bridge to Six Sigma and process capability indices , 2009 .

[22]  L. Franklin,et al.  Bootstrap Lower Confidence Limits for Capability Indices , 1992 .

[23]  Norma Faris Hubele,et al.  Confidence intervals and sample size determination for Cpm , 2001 .

[24]  Fred A. Spiring,et al.  A New Measure of Process Capability: Cpm , 1988 .

[25]  Samuel Kotz,et al.  Encyclopedia and Handbook of Process Capability Indices - A Comprehensive Exposition of Quality Control Measures , 2006, Series on Quality, Reliability and Engineering Statistics.

[26]  Kuen-Suan Chen,et al.  Capability performance analysis for processes with multiple characteristics using accuracy and precision , 2014 .

[27]  Fred A. Spiring,et al.  A Bibliography of Process Capability Papers , 2003 .

[28]  Samuel Kotz,et al.  Process Capability Indices—A Review, 1992–2000 , 2002 .

[29]  Shu-Kai S. Fan,et al.  LOWER BAYESIAN CONFIDENCE LIMITS ON THE PROCESS CAPABILITY INDEX Cpm: A COMPARATIVE STUDY , 2004 .

[30]  S. Balamurali,et al.  Bootstrap lower confidence limits for the process capability indices Cp, Cpk and Cpm , 2002 .

[31]  C-H Wang,et al.  Application of 6-sigma design system to developing an improvement model for multi-process multi-characteristic product quality , 2011 .

[32]  Kuen-Suan Chen,et al.  A MAIC approach to TFT-LCD panel quality improvement , 2006, Microelectron. Reliab..

[33]  Guo Jin-li,et al.  A New Measure of Process Capability , 2008 .

[34]  Z. Abbasi Ganji,et al.  A class of process capability indices for asymmetric tolerances , 2016 .

[35]  Kuen-Suan Chen,et al.  Testing and analysing capability performance for products with multiple characteristics , 2016 .

[36]  Kuen-Suan Chen,et al.  Sputtering Process Assessment of ITO Film for Multiple Quality Characteristics With One-Sided and Two-Sided Specifications , 2014 .

[37]  Kuen-Suan Chen,et al.  Using a QCAC–Entropy–TOPSIS approach to measure quality characteristics and rank improvement priorities for all substandard quality characteristics , 2014 .