Skip to main content
Log in

Variables sampling plans with PPM fraction of defectives and process loss consideration

  • Theoretical Paper
  • Published:
Journal of the Operational Research Society

Abstract

Acceptance sampling plans provide the vendor and the buyer decision rules for lot sentencing to meet their product quality needs. A problem the quality practitioners have to deal with is the determination of the critical acceptance values and inspection sample sizes that provide the desired levels of protection to both vendors and buyers. As today's modern quality improvement philosophy, reduction of variation from the target value is the guiding principle as well as reducing the fraction of defectives. The Cpm index adopts the concept of product loss, which distinguishes the product quality by setting increased penalty to products deviating from the target. In this paper, a variables sampling plan based on Cpm index is proposed to handle processes requiring very low parts per million (PPM) fraction of defectives with process loss consideration. We develop an effective method for obtaining the required sample sizes n and the critical acceptance value C0 by solving simultaneously two nonlinear equations. Based on the designed sampling plan, the practitioners can determine the number of production items to be sampled for inspection and the corresponding critical acceptance value for lot sentencing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Similar content being viewed by others

References

  • Borges WS and Ho LL (2001). A fraction defective based capability index. Qua Relia Eng Inter 17 (6): 447–458.

    Article  Google Scholar 

  • Boyles RA (1991). The Taguchi capability index. J Qual Technol 23: 17–26.

    Google Scholar 

  • Chan LK, Cheng SW and Spiring FA (1988). A new measure of process capability: Cpm . J Qual Technol 20: 162–175.

    Google Scholar 

  • Das NG and Mitra SK (1964). The effect of non-normality on sampling inspection. Sankhya 26A: 169–176.

    Google Scholar 

  • Duncan AJ (1986). Quality Control and Industrial Statistics, 5th edn. Irwin: Homewood, III.

    Google Scholar 

  • Govindaraju K and Soundararajan V (1986). Selection of single sampling plans for variables matching the MIL-STD-105 scheme. J Qual Technol 18: 234–238.

    Google Scholar 

  • Guenther WC (1969). Use of the binomial, hypergeometric, and Poisson tables to obtain sampling plans. J Qual Technol 1 (2): 105–109.

    Google Scholar 

  • Hailey WA (1980). Minimum sample size single sampling plans: a computerized approach. J Qual Technol 12 (4): 230–235.

    Google Scholar 

  • Hald A (1981). Statistical Theory of Sampling Inspection by Attributes. Academic Press Inc.: London.

    Google Scholar 

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

    Google Scholar 

  • Hsiang TC and Taguchi G (1985). A tutorial on quality control and assurance—the Taguchi methods. ASA Annual Meeting Las Vegas, Nevada, USA.

  • Hoffman LL (2001). Obtaining confidence intervals for Cpk using percentiles of the distribution of Cp . Qual Reliability Eng Int 17 (2): 113–118.

    Article  Google Scholar 

  • Jennett WJ and Welch BL (1939). The control of proportion defective as judged by a single quality characteristic varying on a continuous scale. J R Stat Soc (Ser B) 6: 80–88.

    Google Scholar 

  • Juran JM (1974). Quality Control Handbook, 3rd edn. McGraw-Hill: New York.

    Google Scholar 

  • Kane VE (1986). Process capability indices. J Qual Technol 18 (1): 41–52.

    Google Scholar 

  • Kao JHK (1971). MIL-STD-414: Sampling procedures and tables for inspection by variables for percent defective. J Qual Technol 3: 28–37.

    Google Scholar 

  • Kotz S and Johnson NL (1993). Process Capability Indices. Chapman & Hall: London.

    Book  Google Scholar 

  • Kotz S and Johnson NL (2002). Process capability indices—a review, 1992–2000. J Qual Technol 34 (1): 1–19.

    Google Scholar 

  • Kotz S and Lovelace C (1998). Process Capability Indices in Theory and Practice. Arnold: London, UK.

    Google Scholar 

  • Lieberman GJ and Resnikoff GJ (1955). Sampling plans for inspection by variables. J Am Stat Assoc 50: 72–75.

    Google Scholar 

  • Montgomery DC (2001). Introduction to Statistical Quality Control, 4th edn. Wiley: New York.

    Google Scholar 

  • Owen DB (1967). Variables sampling plans based on the normal distribution. Technometrics 9: 417–423.

    Article  Google Scholar 

  • Pearn WL, Kotz S and Johnson NL (1992). Distributional and inferential properties of process capability indices. J Qual Technol 24 (4): 216–233.

    Google Scholar 

  • Pearn WL, Lin GH and Chen KS (1998). Distributional and inferential properties of the process accuracy and process precision indices. Communications Stat: Theory Methods 27 (4): 985–1000.

    Article  Google Scholar 

  • Ruczinski I (1996). The relation between Cpm and the degree of includence. Doctoral Dissertation. University of Würzberg, Würzberg, Germany.

    Google Scholar 

  • Schilling EG (1982). Acceptance Sampling in Quality Control. Marcel Dekker Inc.: New York.

    Google Scholar 

  • Spiring FA, Leung B, Cheng SW and Yeung A (2003). A bibliography of process capability papers. Qual Reliab Eng Int 19 (5): 445–460.

    Article  Google Scholar 

  • Stephens LJ (1978). A closed form solution for single sample acceptance sampling plans. J Qual Technol 10 (4): 159–163.

    Google Scholar 

  • Subbaiah P and Taam W (1993). Inference on the capability index: Cpm . Communications Stat: Theory Methods 22 (2): 537–560.

    Article  Google Scholar 

  • Sullivan LP (1984). Targeting variability—a new approach to quality. Qual Prog 17 (7): 15–21.

    Google Scholar 

  • Sullivan LP (1985). Letters. Qual Prog 18 (4): 7–8.

    Google Scholar 

  • Suresh RP and Ramanathan TV (1997). Acceptance sampling plans by variables for a class of symmetric distributions. Commun in Statistics: Simulation and Computation 26 (4): 1379–1391.

    Article  Google Scholar 

  • Vännman K and Kotz S (1995). A superstructure of capability indices distributional properties and implications. Scand J Stat 22: 477–491.

    Google Scholar 

  • Vännman K (1997). Distribution and moments in simplified form for a general class of capability indices. Commun Stat: Theory Methods 26: 159–179.

    Article  Google Scholar 

  • Zimmer LS, Hubele NF and Zimmer WJ (2001). Confidence intervals and sample size determination for Cpm . Qual Reliab Eng Int 17: 51–68.

    Article  Google Scholar 

  • Zimmer LS and Hubele NF (1997). Quantiles of the sampling distribution of Cpm . Qual Eng 10: 309–329.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to W L Pearn.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pearn, W., Wu, CW. Variables sampling plans with PPM fraction of defectives and process loss consideration. J Oper Res Soc 57, 450–459 (2006). https://doi.org/10.1057/palgrave.jors.2602013

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/palgrave.jors.2602013

Keywords

Navigation