Particle swarm optimisation in development of component families using classification and coding system: a case study in an Indian manufacturing firm

Component/part family identification is an NP class problem in the extent of group technology (GT). In preceding literature it has been evidenced that part family identification techniques are ordinarily grounded on production flow analysis which typically studies operational requirements, sequences and time required. Recently, various soft-computing-based techniques are heavily attempted to address such problems. However in designing of parts, process planning, these methods are not convenient. To accomplish such issues coding and classification-based techniques are believed to be extremely proficient. This article portrays a minimal and competent nature inspired heuristic approach based on particle swarm optimisation (PSO) to acquire effective component/part families; exploiting part coding scheme and the technique is verified on top of test data as well as industrial data. The simulation outcomes are assessed with the results achieved using simple heuristic clustering method. The experimental results recommend that the proposed method is more effective in terms of computational efficiency and has outperformed the heuristic technique with enhanced solution quality.