Title: Empirical verification of a mathematical model for measuring the required reduction in process variation to achieve Six-Sigma quality benchmarks

Authors: Eisenhower C. Etienne

Addresses: Operations/Logistics Supply Chain and Quality Management, School of Business and Industry, Florida A&M University, One SBI Plaza, Tallahassee, FL 32307, USA

Abstract: The measurement and reduction of process variation are recognised in both Total Quality Management and Six-Sigma Strategy as critical drivers of systematic process improvement. However, there exists no systematic computational procedure for measuring the reduction in variation that is required to move a process from a current sigma measure to the Six-Sigma metric. The current Six-Sigma practice simply applies the DMAIC process to compute process sigma metrics, define and launch projects that will simply reduce process variation and measure and compare the resultant sigma measures to the Six-Sigma benchmark, after-the-fact. This paper introduces and empirically evaluates a mathematical model for exactly computing in advance of the specification and launch of improvement projects, the Required Reduction in Process Variation (RRPV) that will drive a process to perform at the Six-Sigma benchmark.

Keywords: six sigma; process improvement; Taguchi methods; robust quality; Deming philosophy; Hoshin Kanri; policy deployment; process variation; DMAIC; SPC; sigma metric; QFD; statistical process control; quality function deployment; mathematical modelling.

DOI: 10.1504/IJSSCA.2009.029915

International Journal of Six Sigma and Competitive Advantage, 2009 Vol.5 No.4, pp.359 - 379

Published online: 02 Dec 2009 *

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