Original Research

A Lean Six Sigma approach to the improvement of the selenium analysis method

Bronwyn C. Cloete, André Bester
Onderstepoort Journal of Veterinary Research | Vol 79, No 1 | a407 | DOI: https://doi.org/10.4102/ojvr.v79i1.407 | © 2012 Bronwyn C. Cloete, André Bester | This work is licensed under CC Attribution 4.0
Submitted: 27 January 2012 | Published: 02 November 2012

About the author(s)

Bronwyn C. Cloete, Western Cape Provincial Veterinary Laboratory, Histology Section, South Africa
André Bester, Department of Industrial and Systems Engineering, Cape Peninsula University of Technology, Bellville Campus, South Africa

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Reliable results represent the pinnacle assessment of quality of an analytical laboratory, and therefore variability is considered to be a critical quality problem associated with the selenium analysis method executed at Western Cape Provincial Veterinary Laboratory (WCPVL). The elimination and control of variability is undoubtedly of significant importance because of the narrow margin of safety between toxic and deficient doses of the trace element for good animal health. A quality methodology known as Lean Six Sigma was believed to present the most feasible solution for overcoming the adverse effect of variation, through steps towards analytical process improvement. Lean Six Sigma represents a form of scientific method type, which is empirical, inductive and deductive, and systematic, which relies on data, and is fact-based. The Lean Six Sigma methodology comprises five macro-phases, namely Define, Measure, Analyse, Improve and Control (DMAIC). Both qualitative and quantitative laboratory data were collected in terms of these phases. Qualitative data were collected by using quality-tools, namely an Ishikawa diagram, a Pareto chart, Kaizen analysis and a Failure Mode Effect analysis tool. Quantitative laboratory data, based on the analytical chemistry test method, were collected through a controlled experiment. The controlled experiment entailed 13 replicated runs of the selenium test method, whereby 11 samples were repetitively analysed, whilst Certified Reference Material (CRM) was also included in 6 of the runs. Laboratory results obtained from the controlled experiment was analysed by using statistical methods, commonly associated with quality validation of chemistry procedures. Analysis of both sets of data yielded an improved selenium analysis method, believed to provide greater reliability of results, in addition to a greatly reduced cycle time and superior control features. Lean Six Sigma may therefore be regarded as a valuable tool in any laboratory, and represents both a management discipline, and a standardised approach to problem solving and process optimisation.


Improvement; Lean Six Sigma; Quality; Selenium Analysis; Statistical Validation


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