Lookup NU author(s): Teerawut Tunnukij,
Professor Christian Hicks
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The first step in solving facility layout design problems involves cell formation. The objective is to group part families and machines so that they can be assigned to independent manufacturing cells. However, in many cases, there are machines/parts that cannot be exclusively assigned to independent manufacturing cells. These are known as exceptional elements (EEs), which create inter-cell flow. This can reduce the benefits of a cellular manufacturing system. This paper proposes a new approach for identifying exceptional machines and incorporating them into sub-cells that are shared between independent cells. The sub-cells process exceptional parts. This clustering approach provides information on which exceptional machines should be placed near together in a cellular layout in order to reduce the inter-cell part distance travelled by exceptional parts. Previous research by the authors has developed an Enhanced Grouping Genetic Algorithm (EnGGA) that identifies independent manufacturing cells. It was found that the EnGGA performed better than other methods. This paper presents a two-stage algorithm that employs the EnGGA to identify independent manufacturing cells and then applies a local search heuristic to identify potential sub-cells that contain the EEs. The grouping efficacy measure was modified in order to take into account sub-cells. The quality of the solutions was compared to the best solutions produced by the EnGGA. The new algorithm produced better solutions than the EnGGA and other methods whenever EEs were found.
Author(s): Tunnukij T, Hicks C
Editor(s): Grubbstron, RW; Hinterhuber, H
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Fifteenth International Working Seminar on Production Economics
Year of Conference: 2008