Abstract
The integration of quality improvement and manufacturing system management has emerged as a promising research topic in recent years. Since operators performance variation can be reflected in product quality, workforce performance evaluation should be conducted with quality-based metrics to improve product quality as well as manufacturing system productivity. In this article, a methodology incorporating regression modeling and multiple comparisons is proposed to aid the performance evaluation. The effects of other impacting factors that contribute to operators performance variation are quantified with a robust zero-inflated Poisson regression model. The model coefficients are analyzed with multiple hypothesis tests to identify underperforming machines. Two statistical charts used in multiple comparisons are adopted for identifying underperforming operators. A case study with data from a real-world production system and a simulation experiment are presented to demonstrate the proposed methodology.
Original language | English (US) |
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Pages (from-to) | 644-657 |
Number of pages | 14 |
Journal | IIE Transactions (Institute of Industrial Engineers) |
Volume | 45 |
Issue number | 6 |
DOIs | |
State | Published - Jun 1 2013 |
Keywords
- Performance evaluation
- analysis of means
- zero-inflated Poisson regression
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering