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Controlling autocorrelated data in multistage manufacturing processes with an application to textile industry

Keshavarz, M ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1002/qre.2512
  3. Publisher: John Wiley and Sons Ltd , 2019
  4. Abstract:
  5. In recent years, much attention has been given to monitoring multistage processes in order to effectively improve the product reliability. To this end, the output of the process is investigated under special circumstances, and the values corresponding to reliability-related quality characteristic are measured. However, analyzing reliability data is quite complicated because of their unique features such as being censored and obeying nonnormal distributions. A more sophisticated picture arises when the observations of the process are autocorrelated in some cases, which makes the application of previous control procedures futile. In this paper, the accelerated failure time (AFT) regression models have been modified in order to account for autocorrelated data. Then, a cumulative sum (CUSUM) control chart and an exponentially weighted moving average (EWMA) control chart based on conditional expected values have been proposed to monitor the quality variable with Weibull distribution while taking the effective covariates into consideration. Extensive simulation studies reveal that the CUSUM control chart outperforms its counterpart in detecting out-of-control conditions. Finally, a real case study in a textile industry has been provided to investigate the application of the CUSUM control scheme. © 2019 John Wiley & Sons, Ltd
  6. Keywords:
  7. Accelerated failure time (AFT) regression model ; Autocorrelated observations ; Cumulative sum (CUSUM) control chart ; Exponentially weighted moving average (EWMA) control chart ; Multistage processes ; Control charts ; Flowcharting ; Regression analysis ; Reliability ; Textile industry ; Textiles ; Weibull distribution ; Autocorrelated ; Cumulative sum control charts ; Exponentially weighted moving average control charts ; Multistage process ; Regression model ; Process control
  8. Source: Quality and Reliability Engineering International ; Volume 35, Issue 7 , 2019 , Pages 2314-2326 ; 07488017 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/qre.2512