Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/10802
Title: A neural network-based approach for part family classification for a reconfigurable manufacturing system
Authors: Hasan F.
Jain P.K.
Published in: International Journal of Operational Research
Abstract: The design of RMS initiates with the classification of parts into families, after which reconfiguration of the system is carried out to cater new part families. It is important that parts must be grouped into logical families based on similarities either in manufacturing or design attributes. Generally, production system maintains a large database of existing part families, and once any new part comes in, the efforts must be focused on deciding upon an appropriate existing part family in which the new part may be grouped with. In literature, most of the approaches are based on part family formation from beginning with no consideration of how the existing part family database can be utilised to decide upon a suitable existing part family for a new part. This paper proposed a neural network classification-based approach for such classification. The developed methodology is explained with the help of a numerical illustration. Copyright © 2016 Inderscience Enterprises Ltd.
Citation: International Journal of Operational Research (2016), 25(2): 143-168
URI: https://doi.org/10.1504/IJOR.2016.073954
http://repository.iitr.ac.in/handle/123456789/10802
Issue Date: 2016
Publisher: Inderscience Enterprises Ltd.
Keywords: Back-propagation algorithm
Neural network
Part family
RMS
ISSN: 17457645
Author Scopus IDs: 7005439513
7402520507
Author Affiliations: Hasan, F., Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
Jain, P.K., Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, 247667, India
Corresponding Author: Hasan, F.; Department of Mechanical and Industrial Engineering, Indian Institute of Technology RoorkeeIndia; email: faisalhasan123@rediffmail.com
Appears in Collections:Journal Publications [ME]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.