Open AccessModified direct clustering algorithm for group formation in cellular manufacturing
Author(s) -
G C Potdar,
Sagar U. Sapkal,
A S Shivade
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1049/1/012019
Subject(s) - cellular manufacturing , cluster analysis , group technology , algorithm , computer science , scope (computer science) , canopy clustering algorithm , reduction (mathematics) , task (project management) , cure data clustering algorithm , correlation clustering , data mining , engineering , artificial intelligence , mathematical optimization , mathematics , manufacturing engineering , geometry , systems engineering , programming language
In cellular manufacturing system formation of machine-part families is an important task. Cellular manufacturing systems deals with various clustering algorithms which are particularly relevant to the problem of machine component group formation. In this paper, case study from well-known gearbox manufacturing company is considered where there is scope for using cellular manufacturing system. Company is manufacturing the gearbox varying from single stage reduction to four stage reduction. A modified direct clustering algorithm is proposed and is applied after the initial incidence matrix derived from direct clustering algorithm. This algorithm overcomes the problem arises during application of direct clustering algorithm and gives the optimum solution. The algorithm is specifically designed to deal with large amount of data during realistic situations. The results of proposed algorithm are compared with well-known existing algorithms and it is found that the proposed algorithm gives the better solution than the existing algorithms under consideration.