Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Robotics and Computer-Integrated Manufacturing
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This paper presents a prototype object-oriented intelligent disassembly sequence planner for maintenance. A novel disassembly representation scheme known as disassembly constraint graph (DCG) has been proposed and implemented as a prototype system in this work. Using the DCG, all the possible disassembly operations that are needed for the maintenance of certain components or subassemblies can be deduced. Subsequently, a sequence-based optimisation technique, genetic algorithms, is employed to generate near optimal disassembly sequence from all the feasible combination of these disassembly operations. Based on the DCG, an object-oriented intelligent disassembly sequence planner for maintenance has been developed. The prototype system comprises three modules each having a set of objects. Users are able to view the entire disassembly process in accordance to the near optimal sequence generated by the planner via a graphical user interface. Two case studies, which are used to illustrate the effectiveness of the planner, are presented.