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The effect of inspection error on quality and producer losses: the case of nominal-the-best type quality characteristic and rework

Author

Listed:
  • Gülser Köksal
  • Aysun TaÅŸeli
  • Leman Esra Dolgun
  • Ä°nci Batmaz

Abstract

In this study, the effect of inspection error (IE) on quality and producer losses is investigated for a nominal-the-best type quality characteristic determined by a manufacturing process centre with a separate rework unit. The probability distribution and the first two moments of the resulting quality characteristic values are derived and used together with Markov chain models and simulation to study the quality and producer losses and the related statistics for various processes and gauge capability levels. The results of this study confirm with strong theoretical and empirical evidence that an effective way of achieving robustness to IE is to improve the process capability. This study provides benchmarks that support understanding and decision making of quality professionals. [Received 11 November 2010; Revised 3 June 2011; Revised 6 December 2011; Accepted 18 December 2011]

Suggested Citation

  • Gülser Köksal & Aysun TaÅŸeli & Leman Esra Dolgun & Ä°nci Batmaz, 2013. "The effect of inspection error on quality and producer losses: the case of nominal-the-best type quality characteristic and rework," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 7(4), pages 497-528.
    • Handle: RePEc:ids:eujine:v:7:y:2013:i:4:p:497-528
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    Citations

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    Cited by:

    1. Hsi-Tien Chen & Kuen-Suan Chen, 2016. "Assessing the assembly quality of a T-bar ceiling suspension by using an advanced multi-process performance analysis chart with asymmetric tolerance," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(2), pages 264-283.
    2. Razmkhah Mansooreh & Sadeghpour Gildeh Bahram & Ahmadi Jafar, 2017. "An Economic Design of Rectifying Double Acceptance Sampling Plans via Maxima Nomination Sampling," Stochastics and Quality Control, De Gruyter, vol. 32(2), pages 99-104, December.
    3. Ruiying Li & Qiang Dong & Wenting Ma & Rui Kang, 2023. "A test-based methodology for the probabilistic assessment of system resilience under random disturbances," Journal of Risk and Reliability, , vol. 237(4), pages 671-685, August.

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