 Multi-response quality improvement by non-parametric DOE methodsGeorge J. Besseris International Journal of Productivity and Quality Management, 2009, vol. 4, issue 3, 303-323 Abstract: Quality management principles promote the systematic elimination of problematic areas of products before they reach the marketplace. It is a rare fact that a product is as good as optimising just a single quality trait of it. A practical and economical method is presented in this work for placing statistical significance on non-linear multiresponse-to-factor relationship during screening experimentation with unreplicated and saturated fractional factorial designs. A technique is developed on a simple additive rule for multiple ranked responses all of which are tested synchronously against a group of product or process parameters. The developed hypothesis is tested based on the multi-level nonparametric method proposed by Jonckheere-Terpstra. Advantages exhibited are the minimal computational effort and convenience in usage while relaxing strict normality assumptions. The theoretical developments are illuminated by a case study on a recently posed problem in the ever-popular area of small-component plastic injection moulding. Keywords: quality optimisation; design of experiments; DOE; non-parametric testing; unreplicated fractional design; robust design; multi-response quality improvement; productivity; quality management; plastic injection moulding. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:4:y:2009:i:3:p:303-323 Access Statistics for this article More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd |
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