A genetic algorithm for solving an assembly sequence problem
Research output: Contribution to journal › Article › peer-review
If a product has more than one component, then it must be assembled. The complexity of assembling a product is often subject to the number of assembly components that lead to possible assembly sequences in various forms. Also, it is widely understood that efficiency of assembling a product by reducing assembly times (therefore costs) is vital particularly for small manufacturing companies to survive in an increasingly competitive market. Ideally, it is helpful for determining an optimal assembly sequence of a product at the early design stage. Nevertheless, it may find inefficient using the heuristic approaches in acquisition of a quick solution in terms of an optimal assembly sequence with a minimal assembly time. By contrast, the study indicates that the genetic algorithm (GA) can be used as a cost-effective way for solving an assembly sequence optimisation problem of a product. This paper presents an investigation into a GA used for solving an assembly sequence problem of a ball pen. The study demonstrates that it can provide a quick solution in obtaining an optimal or near-optimal assembly sequence of the product for a small-sized company.
|Journal||Applied Mechanics and Materials|
|Early online date||16 Oct 2017|
|Publication status||Published - Oct 2017|
|Event||2nd International Conference on Applied Engineering, Materials and Mechanics - Tianjin, China|
Duration: 14 Apr 2017 → 17 Apr 2017