Connector-based approach to assembly planning using a genetic algorithm

Assembly planning refers to the task where planners arrange a specific assembly sequence according to the product design description as well as to their particular heuristics in putting together all the components of a product. In assembly planning, one needs to take into consideration the relations...

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Bibliographic Details
Published in:International journal of production research Vol. 42; no. 11; pp. 2243 - 2261
Main Authors: Tseng, H.-E., Li, J.-D., Chang, Y.-H.
Format: Journal Article
Language:English
Published: London Taylor & Francis Group 01.06.2004
Taylor & Francis LLC
Subjects:
Assembly lines
Genetic algorithms
Object oriented programming
Operations research
Planning
Production planning
Studies
ISSN:0020-7543, 1366-588X
Online Access:Get full text
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Summary:Assembly planning refers to the task where planners arrange a specific assembly sequence according to the product design description as well as to their particular heuristics in putting together all the components of a product. In assembly planning, one needs to take into consideration the relationships between components such as the geometric limitation factor before the precedence sequence is set up for assembly. This deliberation will contribute strongly to lower the production cost. Unlike traditional studies where the liaison graph goes with a genetic algorithm, an attempt is made to solve problems in assembly planning by using a genetic algorithm under the connector-based environment. Such a connector-based genetic algorithm takes a more realistic view. The key point in this approach to assembly planning is to combine the connector concept and characteristics of a genetic algorithm using object-oriented programming; thus, the programming language C++ is used to develop the mechanism of the algorithm. Finally, a stapler and a computer hard disk were used as practical examples to illustrate the possibility of such an idea. Consequently, in terms of assembly planning, it is feasible to create a genetic algorithm based on the connector's engineering features.
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ISSN:0020-7543
1366-588X
DOI:10.1080/0020754042000203894