Operator Assignment Decisions in a Highly Dynamic Cellular Environment

Operator Assignment Decisions in a Highly Dynamic Cellular Environment

Gürsel A. Süer (Ohio University, USA) and Omar Alhawari (Royal Hashemite Court, Jordan)
Copyright: © 2012 |Pages: 19
DOI: 10.4018/978-1-61350-047-7.ch012

Abstract

Operators are assigned to operations in labor-intensive manufacturing cells using two assignment strategies: Max-Min and Max. The major concern is to see how these two approaches impact operators’ skill levels and makespan values in a multi-period environment. The impact is discussed under chaotic environment where sudden changes in product mix with different operation times are applied, and also under non-chaotic environment where same product mix is run period after period. In this chapter, operators’ skill levels are affected by learning and forgetting rates. The Max-Min strategy improved operators’ skill levels more significantly than Max in this multi-period study; particularly in chaotic environment. This eventually led to improved makespan values under Max-Min strategy.
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Background

In the literature, some researchers addressed areas related to this subject such as cell loading, operator assignment, skills, learning and forgetting rate and product sequencing. Süer (1996) discussed, in his paper, the subject of optimal operator assignment and cell loading in labor-intensive manufacturing cells. He stated that the operator assignment to cells influences production rate that each cell can produce. He proposed a two-phase methodology. In phase 1, he generated operator assignments for alternative manpower levels by using a mixed integer mathematical model. In phase 2, he found the optimal manpower levels for each cell and optimal product assignment to cells.

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