A Genetic Algorithm Approach to End-of-life Disassembly Sequencing for Robotic Disassembly

End-of-life (EOL) processing options include reuse, remanufacturing, recycling and proper disposal. In almost all cases, a certain level of disassembly may be required due to possible changes in the original product structure. Thus, finding an optimal or near optimal disassembly sequence is crucial to increasing the efficiency of the process. Disassembly operations are labor intensive, can be costly, have unique characteristics and cannot be considered as reverse of assembly operations. Since the complexity of determining the best disassembly sequence increases as the number of parts of the product grow, an efficient methodology is reuired for disassembly sequencing. In this paper, we present a Genetic Algorithm for disassembly sequencing of EOL products. A numerical example is provided to demonstrate the functionality of the algorithm.