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Improving the Product Reliability in Multistage Manufacturing and Service Operations
Author(s) -
Asadzadeh Shervin,
Aghaie Abdollah
Publication year - 2012
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1254
Subject(s) - ewma chart , cusum , control chart , reliability (semiconductor) , reliability engineering , quality (philosophy) , statistical process control , computer science , shewhart individuals control chart , product (mathematics) , variable (mathematics) , chart , statistics , process (computing) , engineering , mathematics , mathematical analysis , power (physics) , physics , philosophy , geometry , epistemology , quantum mechanics , operating system
Monitoring and improving the product reliability is of main concern in a large number of multistage manufacturing processes. The process output is commonly inspected under limited load conditions, and the tensile strength of reliability‐related quality characteristic is measured. This brings about censored observations that make the direct application of traditional control charts futile. The monitoring procedure becomes aggravated when the influence of variable competing risk is pronounced during the conducted test. To deal with this critical issue, we propose a regression‐adjusted cumulative sum (CUSUM) chart to effectively monitor a quality characteristic that may be right censored because of both fixed and variable competing risks. Moreover, two exponentially weighted moving average (EWMA) control charts on the basis of conditional expected values are devised to detect decreases in the tensile mean. The comparison of the three competing monitoring schemes confirms the superiority of the regression‐adjusted CUSUM procedure. Not only is the proposed control chart applicable to manufacturing processes with the aim of monitoring reliability‐related quality variables, it is also appropriate for monitoring similar quality measurements in service operations such as survivability measures in healthcare services. Copyright © 2011 John Wiley & Sons, Ltd.