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.Learning, Forgetting, Worker Heterogeneity, Simulation
In this paper we describe an approach that enables managers to systematically describe patterns of skill learning in large populations of front-line workers. The method fits individualized learning curves to the work performance histories of every member of a population. The resulting set of 'best-fit' parameter estimates represents a parsimonious summary of the many learning behaviors that are taking place. A case study demonstrated the descriptive power of the model using electronically collected data on 3874 episodes of individual learning in a large US manufacturing firm. q 1998 Elsevier Science B.V. All rights reserved. 0272-6963r98r$ -see front matter q 1998 Elsevier Science B.V. All rights reserved.Ž. PII: S 0 2 7 2 -6 9 6 3 9 7 0 0 0 1 7 -X
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