Particle swarm optimisation in development of component families using classification and coding system: a case study in an Indian manufacturing firm
by Tamal Ghosh; Pranab K. Dan
International Journal of Services and Operations Management (IJSOM), Vol. 13, No. 4, 2012

Abstract: 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.

Online publication date: Sat, 23-Aug-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Services and Operations Management (IJSOM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com