Line Balancing With Task Learning Effects

Abstract

In this paper we show how the learning effects of the individual tasks can be incorporated in the initial design of the stations so that the system may not experience large idle times. We account for the learning effects in assigning tasks to stations by linking the task assignment to the formation of dynamic (in time) bottleneck stations. The station design problem is modeled as a dynamic recursive optimization with computational complexity of O( M²N), where Mis the number of tasks and Nthe number of production units. Using a computer simulation for a system designed by using our task assignment procedure, we compare the system idle times with/without ignoring the learning effects.

Notes

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