The Effects of Worker Learning, Forgetting, and Heterogeneity on Assembly Line Productivity
Scott M. Shafer (),
David A. Nembhard () and
Mustafa V. Uzumeri ()
Additional contact information
Scott M. Shafer: Babcock Graduate School of Management, Wake Forest University, P.O. Box 7659, Winston-Salem, North Carolina 27109-7659
David A. Nembhard: Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Avenue, Madison, Wisconsin 53706-1572
Mustafa V. Uzumeri: Department of Management, Auburn University, 415 W. Magnolia Avenue, Auburn, Alabama 36849-5241
Management Science, 2001, vol. 47, issue 12, 1639-1653
Abstract:
The authors investigate through several simulations how patterns of learning and forgetting affect the operating performance of an assembly line. A unique aspect of this study is that a distribution of learning/forgetting behavior based on an empirical population of workers is used rather than assuming the same learning pattern for all employees. The paper demonstrates that modeling only central tendency and not the variations across workers tends to systematically underestimate overall productivity. The data used to estimate the parameters for the distribution of learning curves were collected from an assembly line that produces car radios. Analysis of the models fit to a population of workers reveals that higher levels of previous experience are positively correlated with higher steady-state productivity levels and negatively correlated with the learning rate. To further motivate the study, a conceptual model with several factors hypothesized to influence assembly line productivity is presented. Among key factors included in the model are the rate of worker learning, the size of the worker pool, task tenure, and the magnitude of worker forgetting. In controlled computer simulation experiments, each of these factors was found to be statistically significant, as were a number of the two-way interaction terms.
Keywords: Learning; Forgetting; Worker Heterogeneity; Simulation (search for similar items in EconPapers)
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (46)
Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.47.12.1639.10236 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:47:y:2001:i:12:p:1639-1653
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().