Article ID: | iaor2006277 |
Country: | United States |
Volume: | 36 |
Issue: | 1 |
Start Page Number: | 159 |
End Page Number: | 186 |
Publication Date: | Feb 2005 |
Journal: | Decision Sciences |
Authors: | Sinha Kingshuk K., Field Joy M. |
Keywords: | time series & forecasting methods |
The widespread recognition of the detrimental effects of high yield variation in advanced manufacturing technology settings, both in terms of cost and management of production processes, underscores the need to develop effective strategies for reducing yield variation. In this article, we report the findings of a longitudinal field study in an electromechanical motor assembly plant where we examined how the application of process knowledge by production work teams can reduce yield variation. We propose and provide an operationalization of a strategy to identify the sequence of particular types of actions – actions to control the mean followed by actions to control the variance – that work teams should pursue over time to apply process knowledge for reducing yield variation. The results of our empirical analysis show that yield variation was significantly reduced on three of the four production lines at the manufacturing plant that served as our research site. Differences in strategies for applying process knowledge help explain the different results on each of the production lines.