Robotic Assembly Sequence Generation Using Improved Fruit Fly Algorithm

Abstract

Assembly plays a key role in manufacturing, which requires effective assembly sequence to upsurge product quality. In early 90s investigators started research on assembly sequence planning (ASP) problem to obtain the best sequences for the industrial assemblies. At the starting stages, mathematical models are applied to generate feasible sequences. Further, researchers applied artificial intelligence (AI) techniques to achieve the optimal assembly sequences because of its less search space consumption during execution. Meanwhile, few of the researchers developed computer-aided design (CAD)-based and knowledge-based approaches to generate the best sequences, which consume more search space during execution of the algorithm. Keeping the above considerations in mind and the advantages with artificial intelligence techniques, in this paper, fruit fly algorithm with improvement is proposed to generate optimal robotic assembly sequences. This algorithm is developed mainly based on how fruit fly can identify the fruits based on smell. The developed algorithm is applied to the different industrial products to check the enactment of the algorithm.