Six sigma, taguchi and shainin

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IJQRM 21,2

Received August 2002 Revised March 2003

A methodological comparison of three strategies for quality improvement
Jeroen de Mast
Institute for Business andIndustrial Statistics of the University of Amsterdam, Amsterdam, The Netherlands
Keywords Quality improvement, Statistical process control, Taguchi methods Abstract Quality improvement is understood by Juran to be the systematic pursuit of improvement opportunities in production processes. Several methodologies are proposed in literature for quality improvement projects. Three of thesemethodologies – Taguchi’s methods, the Shainin system and the Six Sigma programme – are compared. The comparison is facilitated by a methodological framework for quality improvement. The methodological weaknesses and strong points of each strategy are highlighted. The analysis shows that the Shainin system focuses mainly on the identiWcation of the root cause of problems. Both Taguchi’s methods and the SixSigma programme exploit statistical modelling techniques. The Six Sigma programme is the most complete strategy of the three.

Introduction According to Juran (1989) the activities in companies that assure quality can be grouped in three processes: (1) quality planning; (2) quality control; and (3) quality improvement. In this paper, I focus on the last process, quality improvement. It consistsof the systematic and proactive pursuit of improvement opportunities in production processes to increase the quality to unprecedented levels (“breakthrough”). Typically, quality improvement activities are conducted in projects. Its proactive and project-wise nature distinguish quality improvement from quality control, which is an online process that is reactive in nature. Compare as well Ishikawa(1990, p. 201) and Taguchi’s (1986) distinction between online and ofXine quality control.
International Journal of Quality & Reliability Management Vol. 21 No. 2, 2004 pp. 198-213 q Emerald Group Publishing Limited 0265-671X DOI 10.1108/02656710410516989

The author wishes to thank the Editor and referees for their useful comments. This paper is supported by funding under the EuropeanCommission’s Fifth Framework “Growth” Programme via the Thematic Network “Pro-ENBIS” contract reference: G6RT-CT-2001-05059. The author is solely responsible for the content and it does not represent the opinion of the community.

With the purpose of guiding an experimenter in conducting a quality improvement project several strategies have been proposed. I deWne a quality improvement strategy to be:
.. . a coherent series of concepts, steps (phases), methodological rules and tools, that guide a quality professional in bringing the quality of a process or product to unprecedented levels.

Three strategies for quality improvement 199

Traditionally, statistical methods have played an important role in quality improvement (as well as in quality control). The Weld of industrial statistics hasyielded a number of methodologies for quality improvement. Improvement strategies based on statistical methodology typically follow the pattern of empirical inquiry: (1) They try to identify improvement opportunities by discovering (causal) relations in the process between quality characteristics and inXuence factors. (2) Conjectured relations are tested to empirical data before they are acceptedas true (De Mast, 2002). I shall call improvement strategies that comply with the two points above statistical improvement strategies. In the literature on industrial statistics three statistical improvement strategies have received a lot of attention, namely Taguchi’s methods, the Shainin system and the Six Sigma programme (see, for example, Nair, 1992; Steiner et al., 2002; Hahn et al.,...
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