Proposal of variable sequential sampling plan having desired operating characteristics indexed by quality loss

Ryosuke Tomohiro, Ikuo Arizono, Yasuhiko Takemoto

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The proportion of non-conforming items has been traditionally utilised as an evaluation criterion for quality of items. However, the proportion of non-conforming items is not necessarily useful as a proper evaluation criterion for controlling high-quality manufacturing in recent years. Accordingly, in order to achieve further quality improvement and innovation, more careful quality evaluation has been required newly. Then, a concept of quality loss in the Taguchi methods has been devised as a severe criterion of quality evaluation. Hereby, a variable single sampling plan having desired operating characteristics (OCs) indexed by quality loss has been proposed in the area of statistical quality control. By the way, the most economical sampling inspection in the average sample number (ASN) is the sequential sampling plan based on the Wald’s sequential probability ratio test. Then, from the viewpoint of cost reduction, we discuss a variable sequential sampling plan having desired OC indexed by quality loss with the aim of expansion of the utility of variable sampling plan for quality loss. As the result, the design procedure of the sequential sampling plan for satisfying some required design conditions indexed by quality loss is provided. In addition, the effectiveness of the proposed sequential sampling plan is verified through some numerical examples.

Original languageEnglish
Pages (from-to)5742-5760
Number of pages19
JournalInternational Journal of Production Research
Volume54
Issue number19
DOIs
Publication statusPublished - Oct 1 2016

Keywords

  • sequential sampling plan; operating characteristics; Patnaik approximation; quality loss; average sample number

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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