An experimental design approach using TOPSIS method for the selection of computer-integrated manufacturing technologies

被引:120
作者
Ic, Yusuf Tansel [1 ]
机构
[1] Baskent Univ, Fac Engn, Dept Ind Engn, TR-06810 Ankara, Turkey
关键词
Decision making; MADM; TOPSIS; Design of experiment; Computer-integrated manufacturing technologies; ATTRIBUTE DECISION-MAKING; GREY RELATIONAL ANALYSIS; PERFORMANCE-MEASUREMENT; ROBOT SELECTION; PRODUCTION LINE; SUPPORT-SYSTEM; SIMULATION; CRITERIA; MODEL; OPTIMIZATION;
D O I
10.1016/j.rcim.2011.09.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The selection of Computer-Integrated Manufacturing (CIM) technologies becomes more complex as the decision makers in the manufacturing organization have to assess a wide range of alternatives based on a set of attributes. Although, a lot of Multi-Attribute Decision-Making (MADM) methods are available to deal with selection applications, this paper aims to explore the applicability of an integrated TOPSIS and DoE method to solve different CIM selection problems in real-time industrial applications. Four CIM selection problems, which include selection of (a) an industrial robot, (b) a rapid prototyping process, (c) a CNC machine tool and (d) plant layout design, are considered in this paper. TOPSIS method and Design of Experiment (DoE) are used together to identify critical selection attributes and their interactions of all these cases by fitting a polynomial to the experimental data in a multiple linear regression analysis. This mathematical model development process involves TOPSIS experiments with the model. The regression meta-model greatly reduced the cost, time and amount of the calculation step in application the TOPSIS model. Application results were validated and shown that they provide good approximations to four decision making problem's results in the literature. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:245 / 256
页数:12
相关论文
共 45 条
[1]  
[Anonymous], 1998, MULTIPLE CRITERIA DE, DOI DOI 10.1007/978-1-4471-3020-8
[2]   Ranking of enterprises based on multicriterial analysis [J].
Babic, Z ;
Plazibat, N .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 1998, 56-7 :29-35
[3]   Attribute based specification, comparison and selection of a robot [J].
Bhangale, PP ;
Agrawal, VP ;
Saha, SK .
MECHANISM AND MACHINE THEORY, 2004, 39 (12) :1345-1366
[4]   MULTI-OBJECTIVE CONTRACTOR'S RANKING BY APPLYING THE MOORA METHOD [J].
Brauers, Willem Karel M. ;
Zavadskas, Edmundas Kazimieras ;
Turskis, Zenonas ;
Vilutiene, Tatjana .
Journal of Business Economics and Management, 2008, 9 (04) :245-255
[5]   A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method [J].
Byun, HS ;
Lee, KH .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2005, 26 (11-12) :1338-1347
[7]   Selection of industrial robots using compromise ranking and outranking methods [J].
Chatterjee, Prasenjit ;
Athawale, Vijay Manikrao ;
Chakraborty, Shankar .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2010, 26 (05) :483-489
[8]   An application of fuzzy set theory to the external performance evaluation of distribution centers in logistics [J].
Y.-C. Chen .
Soft Computing, 2002, 6 (1) :64-70
[9]   Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation [J].
Cheng, CH ;
Lin, Y .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2002, 142 (01) :174-186
[10]   A fuzzy TOPSIS method for robot selection [J].
Chu, TC ;
Lin, YC .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2003, 21 (04) :284-290