Title: Guest editorial: Statistical thinking and experimental design as dual drivers of DFSS

Authors: T.N. Goh

Addresses: Quality and Innovation Research Centre, Department of Industrial and Systems Engineering, National University of Singapore, Singapore 119260, Singapore

Abstract: The application of statistical Design of Experiments (DOE) in Quality Management has been formalised in Six Sigma through its implementation in the Improve phase of the Define-Measure-Analyse-Improve-Control or DMAIC cycle. With the emergence of Design for Six Sigma (DFSS), DOE has assumed a critical role in activities leading to optimised performance of a new product or a process. DOE has even become a change agent in the way design engineers think and work, something the advocates of straight |Statistical Thinking| has not been able to do readily. In this paper, the experience in the use of statistical tools, specifically DOE, in an industrial setting is described. Thought changes, such as the recognition of variation and the need for robustness in design and manufacturing, are brought about via DOE applications. A |5S| roadmap, or a Start-Secure-Setup-Scrutinise-Share sequence, has become a framework to make statistical thinking and the application of statistical tools part of organisational culture.

Keywords: design for six sigma; DFSS; design of experiments; DOE; statistical software; performance optimisation; organisational culture; robust design.

DOI: 10.1504/IJSSCA.2009.024286

International Journal of Six Sigma and Competitive Advantage, 2009 Vol.5 No.1, pp.2 - 9

Published online: 30 Mar 2009 *

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