Modeling simultaneous worker learning and forgetting in dual resource constrained systems

✍ Scribed by Hemant V Kher; Manoj K Malhotra; Patrick R Philipoom; Timothy D Fry

• Book ID: 104339828
• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 285 KB
• Volume: 115
• Category: Article
• ISSN: 0377-2217
• DOI: 10.1016/s0377-2217(98)00190-8

✦ Synopsis

This paper addresses issues related to modeling worker learning and forgetting eects in Dual Resource Constrained (DRC) systems. The learn-forget-learn (LFL) model of Carlson and Rowe (Carlson, J.C., Rowe, A.J., 1976. Industrial Engineering 8, 40±47) is used to critically evaluate several worker training related issues that are associated with the learning and forgetting phenomenon. A numerical analysis is performed on the LFL model within a DRC system to gain insights into the nature of relationships between the extent of worker ¯exibility, forgetting rates, attrition rates, and ¯exibility acquisition policies. Results suggest that in the presence of higher attrition and forgetting rates, a worker may not be able to achieve full eciency in as little as two dierent departments. Thus acquiring even incremental worker ¯exibility under such conditions may be infeasible. We also show that managers can use dierent ¯exibility acquisition policies designed in this study to reduce relearning losses and consequently improve the system performance.