Input and output scaling in advanced manufacturing technology: theory and application

This paper suggests new data envelopment analysis (DEA) models for input and output scaling in advanced manufacturing technology (AMT). For a given group of AMT observations using the traditional DEA models, it is not possible to evaluate the units when a specified input (or specified output) is required to be scaled for all units. The paper provides theoretical results for obtaining the relationship between the original AMT observations and the corresponding scaled data. Also, the paper uses numerical illustrations to show the usefulness of the suggested contribution.

[1]  K. Chin,et al.  Discriminating DEA efficient candidates by considering their least relative total scores , 2007 .

[2]  Subhash C. Ray.  Data Envelopment Analysis: Contents , 2004 .

[3]  Toshiyuki Sueyoshi,et al.  A unified framework for the selection of a Flexible Manufacturing System , 1995 .

[4]  Moutaz Khouja,et al.  The use of data envelopment analysis for technology selection , 1995 .

[5]  S. M. Shafer,et al.  Efficiency measurement of alternative machine component grouping solutions via data envelopment analysis , 1995 .

[6]  Kwai-Sang Chin,et al.  A new approach for the selection of advanced manufacturing technologies: DEA with double frontiers , 2009 .

[7]  Shian-Jong Chuu,et al.  Selecting the advanced manufacturing technology using fuzzy multiple attributes group decision making with multiple fuzzy information , 2009, Comput. Ind. Eng..

[8]  Reza Farzipoor Saen.  Technology selection in the presence of imprecise data, weight restrictions, and nondiscretionary factors , 2009 .

[9]  Hanif D. Sherali,et al.  Linear Programming and Network Flows , 1977 .

[10]  Erik Lindebo,et al.  Trends in the economic capacity of the Danish fishing fleet, 1996–2002 , 2004 .

[11]  Da Ruan,et al.  Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems , 2006, Inf. Sci..

[12]  R. Venkata Rao,et al.  Flexible Manufacturing System selection using an improved compromise ranking method , 2009 .

[13]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[14]  A Emrouznejad,et al.  Finding relevant search engines results: a minimax linear programming approach , 2010, J. Oper. Res. Soc..

[15]  Shiang-Tai Liu,et al.  A fuzzy DEA/AR approach to the selection of flexible manufacturing systems , 2008, Comput. Ind. Eng..

[16]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[17]  E. Ertugrul Karsak,et al.  Improved common weight MCDM model for technology selection , 2008 .

[18]  Subhash C. Ray,et al.  Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research , 2004 .

[19]  E. Ertugrul Karsak,et al.  Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data , 2008 .

[20]  Sanjay Sharma,et al.  Selection of a pull production control policy under different demand situations for a manufacturing system by AHP-algorithm , 2009, Comput. Oper. Res..

[21]  Gholam R. Amin,et al.  Optimal solution of technology selection model: a computational efficient form , 2009 .

[22]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[23]  Shunsuke Managi,et al.  Input and output biased technological change in US agriculture , 2004 .

[24]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[25]  Ali Azadeh,et al.  An integrated fuzzy DEA–fuzzy C-means–simulation for optimization of operator allocation in cellular manufacturing systems , 2010 .

[26]  Gholam R. Amin.  A note on “an improved MCDM DEA model for technology selection” , 2008 .

[27]  E. E. Karsak *,et al.  Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection , 2005 .