Efficient techniques of information collection and analysis are essential to all quality and productivity improvement studies. Most established concepts of quality control are passive in nature, intended more for the maintenance of the status quo than for purposeful changes. Statistical experiment design methodologies constitute an active approach which can provide the kind of understanding of process and product characteristics that is needed for managing changes during design and manufacture. Systematic planning of data collection and analysis by these methodologies is a prerequisite for the attainment of higher productivity, as it enables the investigator to identify and evaluate important variables quickly, replacing the conventional single‐variable procedures by a far more efficient approach. The major features and potential applications of experiment design are outlined in a non‐technical language for the appreciation of managers.
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1 September 1988
Review Article|
September 01 1988
STATISTICAL METHODOLOGIES FOR QUALITY AND PRODUCTION IMPROVEMENT Available to Purchase
T.N. Goh
T.N. Goh
Industrial and Systems Engineering Department, National University of Singapore
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Publisher: Emerald Publishing
Online ISSN: 1758-5783
Print ISSN: 0263-5577
© MCB UP Limited
1988
Industrial Management & Data Systems (1988) 88 (9-10): 21–24.
Citation
Goh T (1988), "STATISTICAL METHODOLOGIES FOR QUALITY AND PRODUCTION IMPROVEMENT". Industrial Management & Data Systems, Vol. 88 No. 9-10 pp. 21–24, doi: https://doi.org/10.1108/eb057523
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