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Design and construction of a variables switch-based sampling system for product acceptance determination

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Abstract

This article proposes a variables switch-based sampling system, called the quick-switching sampling (QSS) system, based on one-sided capability indices for product acceptance determination when the quality characteristic of interest follows a normal distribution and has a unilateral specification limit. The QSS system is among the simplest sampling systems that involves a normal plan and a tightened plan under switching rules. The operating characteristic function of the proposed system is derived from an exact sampling distribution. The plan parameters are determined by a mathematical model that ensures the prescribed quality and risk requirements. The performance and behavior of the proposed variables QSS system are discussed and compared with those of conventional plans. For practical purposes, this article provides tables of the plan parameters under various conditions, and illustrates the method on an example taken from the integrated circuit industry.

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References

  1. Pearn WL, Wu CW (2007) An effective decision making method for product acceptance. Omega - International Journal of Management Science 35(1):12–21

    Article  Google Scholar 

  2. Montgomery DC (2009) Introduction to statistics quality control, 6th edn. Wiley, New York

    Google Scholar 

  3. Schilling EG, Neubauer DV (2008) Acceptance Sampling in Quality Control (2nd ed.). Chapman & hall/CRC, New York

  4. Dodge HF (1967) A dual system of acceptance sampling, Technical Report No. 16, The Statistics Center, Rutgers - The State University, New Brunswick, NJ

  5. Romboski LD (1969) An Investigation of Quick Switching Acceptance Sampling System. Doctoral dissertation, Rutgers - The State University, New Brunswick, New Jersey

  6. Hamaker HC (1979) Acceptance sampling plan for percent defective by variables and by attributes. J Qual Technol 11(3):139–148

    Article  Google Scholar 

  7. Balamurali S, Jun CH (2007) Multiple dependent state sampling plans for lot acceptance based on measurement data. Eur J Oper Res 180(3):1221–1230

    Article  MATH  Google Scholar 

  8. Tsai TR, Lu YT, Wu SJ (2008) Reliability sampling plans for Weibull distribution with limited capacity of test facility. Comput Ind Eng 55(3):721–728

    Article  Google Scholar 

  9. Negrin I, Parmet Y, Schechtman E (2009) Developing a sampling plan based on C pk. Qual Eng 21:306–318

    Article  Google Scholar 

  10. Negrin I, Parmet Y, Schechtman E (2011) Developing a sampling plan based on C pk. Qual Reliab Eng Int 27(1):3–14

    Article  Google Scholar 

  11. Balamurali S, Jun CH (2009) Designing of a variables two-plan system by minimizing the average sample number. J Appl Stat 36(10):1159–1172

    Article  MathSciNet  Google Scholar 

  12. Wu CW (2012) An efficient inspection scheme for variables based on Taguchi capability index. Eur J Oper Res 223(1):116–122

    Article  MATH  Google Scholar 

  13. Wu CW, Aslam M, Jun CH (2012) Variables sampling inspection scheme for resubmitted lots based on the process capability index C pk. European Journal of Operation Research 217(3):560–566

    Article  MATH  Google Scholar 

  14. Aslam M, Wu CW, Azam M, Jun CH (2013) Variable sampling inspection for resubmitted lots based on process capability index C pk for normally distributed items. Appl Math Model 37(3):667–675

    Article  MathSciNet  MATH  Google Scholar 

  15. Liu SW, Lin SW, Wu CW (2014) A resubmitted sampling scheme by variables inspection for controlling lot fraction nonconforming. Int J Prod Res 52(12):3744–3754

    Article  Google Scholar 

  16. Liu SW, Wu CW (2014) Design and construction of a variables repetitive group sampling plan for unilateral specification limit. Communication in Statistics: Simulation and Computation 43(8):1866–1878

    Article  MathSciNet  MATH  Google Scholar 

  17. Liu SW, Wu CW (2016) A quick switching sampling system by variables for controlling lot fraction nonconforming. Int J Prod Res 54(6):1839–1849

    Article  Google Scholar 

  18. Kurniati N, Yeh RH, Wu CW (2015) Designing a variables two-plan sampling system for controlling process fraction nonconforming with unilateral specification limit. Int J Prod Res 53(7):2011–2025

    Article  Google Scholar 

  19. Wu CW, Liu SW, Lee AHI (2015) Design and construction of a variables multiple dependent state sampling plan based on process yield. European Journal of Industrial Engineering 9(6):819–838

    Article  Google Scholar 

  20. Lee AHI, Wu CW, Chen YW (2016) A modified variables repetitive group sampling plan with the consideration of preceding lots information. Ann Oper Res 238(1):355–373

    Article  MathSciNet  MATH  Google Scholar 

  21. Lee AHI, Wu CW, Wang ZH (2018) The construction of a modified sampling scheme by variables inspection based on the one-sided capability index. Comput Ind Eng 122:87–94

    Article  Google Scholar 

  22. Balamurali S, Usha M (2012) Variables quick switching system with double specification limits. Int J Reliab Qual Saf Eng, 19(2):125008–125001–17

  23. Wu CW, Lee AHI, Liu SW, Shih MH (2017) Capability-based quick switching sampling system for lot disposition. Appl Math Model 52:131–144

    Article  MathSciNet  Google Scholar 

  24. Kotz S, Lovelace C (1998) Process capability indices in theory and practice. Arnold, London, U.K.

    Google Scholar 

  25. Wu CW, Pearn WL, Kotz S (2009) An overview of theory and practice on process capability indices for quality assurance. Int J Prod Econ 117(2):338–359

    Article  Google Scholar 

  26. Chou YM, Owen DB (1989) On the distributions of the estimated process capability indices. Communications in Statistics - Theory and Methods 18(12):4549–4560

    Article  MathSciNet  MATH  Google Scholar 

  27. Pearn WL, Chen KS (2002) One-sided capability indices C pu and C pl: decision making with sample information. International Journal of Quality & Reliability Management 19(3):221–245

    Article  Google Scholar 

  28. Pearn WL, Shu MH (2003) An algorithm for calculating the lower bounds of C pu and C pl with application to low-drop-out linear regulators. Microelectron Reliab 43(3):495–502

    Article  Google Scholar 

  29. Wu CW, Pearn WL (2006) Bayesian approach for measuring EEPROM process capability based on the one-sided indices CPU and CPL. Int J Adv Manuf Technol 31(1–2):135–144

    Article  Google Scholar 

  30. Wu CW (2007) An alternative approach to test process capability for unilateral specification with subsamples. Int J Prod Res 45(22):5397–5415

    Article  MATH  Google Scholar 

  31. Kurniati N, Yeh RH, Wu CW (2015) A variables sampling plan for resubmitted lots based on one-sided capability indices. Qual Technol Quant Manag 12(4):501–515

    Article  Google Scholar 

  32. Pearn WL, Wu CH, Chuang CC (2016) An effective powerful test for one-sided supplier selection problem with multiple independent characteristics. Qual Technol Quant Manag, 13(2):182–196

  33. Pearn WL, Wu CW (2006) Critical acceptance values and sample sizes of a variables sampling plan for very low fraction of defectives. Omega – Int J Manag Sci 34(1):90–101

    Article  Google Scholar 

  34. Nocedal J, Wright SJ (2006) Numerical Optimization, (2nd Edition), Springer Verlag, New York

  35. Chapra SC (2012) Applied Numerical Methods with MATLAB for Engineers and Scientists, (3rd Edition), McGraw-Hill, New York

  36. Wu CW, Lee AHI, Chang Chien CC (2017) A variables multiple dependent state sampling plan based on a one-sided capability index. Qual Eng 29(4):719–729

    Article  Google Scholar 

  37. Wortham AW, Baker RC (1976) Multiple deferred state sampling inspection. Int J Prod Res, 14(6):719–731

  38. Vaerst R (1982) A procedure to construct multiple deferred state sampling plan. Methods Oper Res 37:477–485

    Google Scholar 

  39. Soundararajan V, Vijayaraghavan R (1990) Construction and selection of multiple dependent (deferred) state sampling plan. J Appl Stat 17(3):397–409

    Article  Google Scholar 

  40. Govindaraju K, Subramani K. (1993) Selection of multiple deferred (dependent) state sampling plans for given acceptable quality level and limiting quality level. J Appl Stat, 20(3):423–428

  41. Wu CW, Lee AHI, Chen YW (2016) A novel lot sentencing method by variables inspection considering multiple dependent state. Qual Reliab Eng Int 32(3):985–994

    Article  Google Scholar 

  42. Wu CW, Wang ZH (2017) Developing a variables multiple dependent state sampling plan with simultaneous consideration of process yield and quality loss. Int J Prod Res 55(8):2351–2364

    Article  Google Scholar 

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Funding

This work was partially supported by the Ministry of Science and Technology of Taiwan under Grant No. MOST 103-2221-E-007-103-MY3.

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Authors and Affiliations

  1. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan

    Chien-Wei Wu, Shih-Wen Liu & Jr-Tzung Chen

  2. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan

    Jhih-Jia Lin

Authors
  1. Chien-Wei Wu
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  2. Shih-Wen Liu
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  3. Jr-Tzung Chen
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  4. Jhih-Jia Lin
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Correspondence to Chien-Wei Wu.

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Wu, CW., Liu, SW., Chen, JT. et al. Design and construction of a variables switch-based sampling system for product acceptance determination. Int J Adv Manuf Technol 101, 2643–2652 (2019). https://doi.org/10.1007/s00170-018-3147-7

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  • DOI: https://doi.org/10.1007/s00170-018-3147-7

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