Abstract
The problem of Robot Selection is of great relevance in the present times of automation. Traditionally such problems were addressed using conventional techniques of Multi Criteria Decision Making such as The Analytic Hierarchy Process (AHP) and The Multi Attribute Utility Theory (MAUT). This paper proposes a methodology for solving common Robot Selection problems using a modification of the conventional AHP by incorporating ‘Fuzzy Linguistic Variables’ in place of numbers. The methodology encapsulates creation of Fuzzy Interface for conversion of input and output variables into suitable linguistic variables. Further, employing the fuzzification process by assigning the linguistic variables to numerical values of the membership functions and formulating suitable decision rules, the procedure culminates into the defuzzification process for converting fuzzy output into crisp value and obtaining the result in the form of Fuzzy Score. The proposed model is explained using a numerical example. The paper also presents a validation of the proposed methodology over real world problems and provides directions for future research towards the end.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
L Abdel-Malek (1986) ArticleTitleA Framework for the Robotic Assembly of Parts with General Geometries International Journal of Production Research 24 1025–1041
V. P. Agrawal V. Khohl S. Gupta (1991) ArticleTitleComputer Aided Robot Selection: The Multiple Attribute Decision Making Approach International Journal of Production Research 29 1629–1644
D. E. Booth M. Khouja M. Hu (1992) ArticleTitleA Robust Multivariate Procedure for Evaluation and Selection of Industrial Robots International Journal of Operations and Production Management 12 15–24 Occurrence Handle10.1108/01443579210009023
D. Driankov H. Hellendoorn M. Reinfrank (1996) An Introduction to Fuzzy Control Narosa Publishing House India
D. Dubois H. Prade (1980) Fuzzy Sets and Systems: Theory and Application. Academic New York
Chon-Huat Goh (1997) ArticleTitleAnalytic Hierarchy Process for Robot Selection Journal of Manufacturing Systems 16 IssueID5 381–386
Mikell P. Groover Weiss Mitchell Roger N. Nagel N. G. Odrey (1986) Industrial Robotics: Technology, Programming and Applications McGraw Hill Inc New York
Kapoor, Vikas and Zulekha Banu. (2002). “Multi Criteria Decision Making and ‘Fuzzy’ Analytic Hierarchy Process – A Comparative Study,” February 15–17, 2002, in National Seminar on ‘Soft Computing & Its Engineering Applications’, Department of Electrical Engineering, Faculty of Engineering, J.N.V. University, Jodhpur, India.
Kapoor, Vikas and S. S. Tak. (1999). “Application of Fuzzy Approach to Facilities Planning – A Case Study (Part 1 & 2)”, August 3–6,1999, International Conference on Advances in Materials and Processing Technology, (AMPT-99) & 16th Annual Conference of The Irish Manufacturing Committee, (IMC-16), Dublin City University, Ireland.
Kapoor, Vikas. (1998). Application of Fuzzy Approach To Facilities Planning, An Unpublished Masters’ Thesis (Dissertation) Under the guidance of Prof. (Dr.) S.S. Tak, Dept. of Production & Industrial Engg., M.B.M. Engg. College, Jodhpur, India.
A. Kaufmann M. M. Gupta (1985) Introduction to Fuzzy Arithmetic Van Nostrand Reinhold Reinhold Co New York
Ralph L. Keeney Howard Raiffa (1993) Decisions with Multiple Objectives: Preferences and Value Tradeoffs Cambridge University Press Cambridge
M. Khouja D. E. Booth (1995) ArticleTitleFuzzy Clustering Procedure for Evaluation and Selection of Industrial Robots Journal of Manufacturing Systems 14 IssueID4 244–251
M. Khouja O. Offodile (1994) ArticleTitleThe Industrial Robots Selection Problem: A Literature Review and Directions for Future Research IIE Transaction 26 IssueID4 50–61
T. Liao Warren (1996) ArticleTitleA Fuzzy Multicriteria Decision-Making Method for Material Selection Journal of Manufacturing Systems 15 IssueID1 1–12
A. Mehrez O. F. Offodile (1994) ArticleTitleA Statistical Economic Framework For Evaluating the Effect of Robot Repeatability on Profit IIE Transactions 26 101–110
B. O. Nnaji M. Yannacoupoulou (1988) ArticleTitleA Utility Theory Based Robot Selection and Evaluation for Electronics Assembly Computers & Industrial Engineering 14 IssueID4 477–493
S. Y. Nof H. Lechtman (1982) ArticleTitleRobot Time and Motion Provides Means for Evaluating Alternative Work Methods Industrial Engineering 14 38–48
O. F. Offodile B. K. Lambert R. A. Dudek (1987) ArticleTitleDevelopment Of A Computer Aided Robot Selection Procedure (CARSP) International Journal of Production Research 25 1109–1121
T. L. Saaty (1988) Multicriteria Decision Making: The Analytic Hierarchy Process McGraw-Hill Inc New York
E. Triantaphyllou S. H. Mann (1994) ArticleTitleA Computational Evaluation of the Original and Revised Analytic Hierarchy Process Computers and Industrial Engineering 26 IssueID3 609–618 Occurrence Handle10.1016/0360-8352(94)90054-X
L. A. Zadeh (1965) ArticleTitleFuzzy Sets Information and Control 8 IssueID3 338–353 Occurrence Handle10.1016/S0019-9958(65)90241-X
L. A. Zadeh (1975) ArticleTitle“The Concept of Linguistic Variable and its Application to Approximate Reasoning, Parts 1 and 2,” Information Sciences 8 199–249 Occurrence Handle10.1016/0020-0255(75)90036-5
L. A. Zadeh (1976) ArticleTitleConcept of a Linguistic Variable and its Application to Approximate Reasoning, Part 3 Information Sciences 9 43–80 Occurrence Handle10.1016/0020-0255(75)90017-1
Author information
Authors and Affiliations
Corresponding author
Additional information
Additional support was provided by the National Science Foundation.
Rights and permissions
About this article
Cite this article
Kapoor, V., Tak, S.S. Fuzzy Application to the Analytic Hierarchy Process for Robot Selection. Fuzzy Optim Decis Making 4, 209–234 (2005). https://doi.org/10.1007/s10700-005-1890-3
Issue Date:
DOI: https://doi.org/10.1007/s10700-005-1890-3