An optimal design for process quality improvement: modelling and application
- 6 October 2003
- journal article
- research article
- Published by Taylor & Francis Ltd in Production Planning & Control
- Vol. 14 (7), 603-612
- https://doi.org/10.1080/09537280310001626197
Abstract
Existing research works on process quality improvement focus largely on the linkages between quality improvement cost and production economics such as set-up cost and defect rate reduction. This paper deals with the optimal design problem for process improvement by balancing the sunk investment cost and revenue increments due to the process improvement. We develop an optimal model based on Taguchi cost functions. The model is validated through a real case study in automotive industry where the 6-sigma DMAIC methodology has been applied. According to this research, the management can adjust the investment on prevention and appraisal costs on quality improvement that enhances process capability, reduces product defect rate and, as a result, generates remarkable financial return.Keywords
This publication has 11 references indexed in Scilit:
- Production economics and process quality: A Taguchi perspectiveInternational Journal of Production Economics, 2001
- An Application of Yield Management to the Hotel Industry Considering Multiple Day StaysOperations Research, 1995
- Process quality improvement and setup reduction in dynamic lot-sizingInternational Journal of Production Research, 1993
- Yield Management at American AirlinesInforms Journal on Applied Analytics, 1992
- Lot sizes and setup frequency with learning in setups and process qualityEuropean Journal of Operational Research, 1989
- Dynamic Process ImprovementOperations Research, 1989
- A Quality Control Model with Learning EffectsOperations Research, 1988
- Production Learning and Quality ControlIIE Transactions, 1987
- Poor-Quality CostPublished by Taylor & Francis Ltd ,1987
- Optimal Lot Sizing, Process Quality Improvement and Setup Cost ReductionOperations Research, 1986