Access the full text.
Sign up today, get DeepDyve free for 14 days.
R. Sokal, P. Sneath (1965)
Principles of numerical taxonomy
H. Seifoddini, Manucher Djassemi (1991)
The production data-based similarity coefficient versus Jaccard's similarity coefficient, 21
H. Seifoddini (1989)
Single linkage versus average linkage clustering in machine cells formation applicationsComputers & Industrial Engineering, 16
S. Mitrofanov (1961)
SCIENTIFIC PRINCIPLES OF GROUP TECHNOLOGY
R.G. Askin, A. Vakharia
Group technology planning and operation
F.R.E. Durie
A survey of group technology and its potential for user application in the UK
H. Seifoddini, M. Djassemi (1995)
Merits of the production volume based similarity coefficient in machine cell formationJournal of Manufacturing Systems, 14
E.S. Buffa, G.C. Armour, T.E. Vollman
Allocating facilities with CRAFT
R. Lee, J. Moore (1967)
CORELAP: Computerized relationship layout planning
P. Jaccard
Nouvelles recherches sur la distribution florale
A. Carrie (1973)
Numerical taxonomy applied to group technology and plant layoutInternational Journal of Production Research, 11
J.A. Tompkins, Y.A. Bozer, J.A. White, J.M.A. Tanchoco
Facilities Planning
R. Francis, L. McGinnis, John White (1991)
Facility Layout and Location: An Analytical Approach
M. Groover (1987)
Automation, Production Systems, and Computer-Integrated Manufacturing
J. Burbidge (1963)
Production flow analysisProduction Engineer, 50
J. King (1980)
Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithmInternational Journal of Production Research, 18
Ying-Chin Ho, C. Lee, C. Moodie (1993)
Two sequence-pattern, matching-based, flow analysis methods for multi-flowlines layout designInternational Journal of Production Research, 31
E. John, A. Davies, A. Thomas (2009)
A note on ‘Modified Hamiltonian chain: a graph theoretic approach to group technology’ after S. K. Mukhopadhyay, K. Ramesh Babu and K. V. Vijai SaiInternational Journal of Production Research, 47
J. McAuley (1972)
Machine grouping for efficient productionProduction Engineer, 51
D. Raman, S. Nagalingam, G. Lin (2009)
Towards measuring the effectiveness of a facilities layoutRobotics and Computer-integrated Manufacturing, 25
M. Anderberg (1973)
Cluster Analysis for Applications
P. Swamidass (2000)
Encyclopedia of Production and Manufacturing Management
J.M. Seehof, W.O. Evans
Automated layout design program
E. John, J. Hammond (1999)
A Weighted Flow-Distance Measure for Machine Layout DesignThe International Journal of Advanced Manufacturing Technology, 15
Yong Yin, K. Yasuda (2006)
Similarity coefficient methods applied to the cell formation problem: A taxonomy and reviewInternational Journal of Production Economics, 101
Purpose – Using the weighted similarity coefficient (WSC) technique in the design of manufacturing facilities provides the system designer with a suitable method for the creation of efficient manufacturing cells. The formation of such well designed machine cells will then hopefully ensure that the achievable cost reduction benefits, in terms of lower operational costs incurred via the transfer of components between machines, are obtained by companies that wish to use cellular manufacturing in their approach to production operations. The aim of this paper is to outline and evaluate the application of a particular WSC equation to the formulation and design of cellular manufacturing systems. Design/methodology/approach – By using a pragmatic approach, the paper chronicles the design and development of a particular weighted similarity coefficient as a means of defining a possibly useful methodology for cell design in manufacturing systems. The technique outlined is subsequently evaluated for its generic nature, applicability and effectiveness via the use of previously published synthetic production data and a comparison with the results of several alternative approaches. Findings – The development of the proposed weighted similarity coefficient to manufacturing cellular design is outlined in the paper and the appropriateness of the technique is subsequently evaluated in order that the benefits obtainable by its use to a host organisation are highlighted. In addition, the results show how the approach can lead to useful improvements in cellular manufacturing performance if adopted by manufacturing system designers and implemented in their designs. Practical implications – The design, development and application of the WSC proposed and its use in manufacturing cellular design provides a simple yet highly effective approach to achieving useful improvements in production system performance through improved work‐part transfer efficiency and associated cost savings. The paper offers practising manufacturing managers and engineers a technique whereby manufacturing cell productive efficiency and output can be improved whilst at the same time achieving a reduction in operational costs. Originality/value – The paper focuses on the proposed WSC technique which contributes to the existing knowledge base on production cell design and may also provide impetus, guidance, support and encouragement for designers to achieve improved output performance and reduced costs in their manufacturing system designs.
International Journal of Productivity and Performance Management – Emerald Publishing
Published: Sep 20, 2011
Keywords: Cellular manufacturing; Similarity coefficient; Facilities design; Manufacturing systems; Research and development; Production improvement
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.