Comparison of the GD and MTR approaches for estimating proportion of non-conformance

Shirley Anak Johnathan Tanjong, Raafat Nasr Ibrahim, Mali Abdollahian

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Abstract

This paper compares our proposed method of using the modified tolerance region (MRT) to the generalised distance (GD) approach for estimating the probability of non-conforming product. For correlated quality characteristics, the tolerance region needs to be redefined so that the model is more stringent in identifying potentially poor product quality, as perceived by customers. The paper shows that the MTR approach is more effective in estimating the proportion of non-conformance (PNC) for correlated quality characteristics as compared to the GD approach. We also compare the multivariate capability index computed using the PNC values obtained from both the GD and MTR methods. The estimation of PNC assists not only in the evaluation of process performance and capability but also in the quantification of cost of poor quality.
Original languageEnglish
Title of host publicationProceedings of the 4th International Workshop on Computer Science and Engineering
Place of PublicationSingapore
PublisherInternational Association of Computer Science and Information Technology
Pages1 - 5
Number of pages5
Publication statusPublished - 2015
EventInternational Workshop on Computer Science and Engineering (WCSE-Winter 2014) - , Hong Kong
Duration: 26 Dec 201428 Dec 2014
Conference number: 4th
http://www.wcse.us/2014.html

Workshop

WorkshopInternational Workshop on Computer Science and Engineering (WCSE-Winter 2014)
Abbreviated titleWCSE 2014-Winter
CountryHong Kong
Period26/12/1428/12/14
OtherWorkshop Conducted at the International Conference on Mechatronics and Mechanical Design
Internet address

Cite this

Johnathan Tanjong, S. A., Ibrahim, R. N., & Abdollahian, M. (2015). Comparison of the GD and MTR approaches for estimating proportion of non-conformance. In Proceedings of the 4th International Workshop on Computer Science and Engineering (pp. 1 - 5). International Association of Computer Science and Information Technology.