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Fusing Multi-Attribute Decision Models for Decision Making to Achieve Optimal Product Design


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[1] Olabanji, O.M., Reconnoitering the suitability of fuzzified weighted decision matrix for design process of a reconfigurable assembly fixture. International Journal of Design Engineering. 8(1): p. 38-56, 2018.10.1504/IJDE.2018.096248Search in Google Scholar

[2] Renzi, C. and F. Leali, A multicriteria decision-making application to the conceptual design of mechanical components. Journal of Multi-Criteria Decision Analysis. 23(3-4): p. 87-111, 2016.10.1002/mcda.1569Search in Google Scholar

[3] Renzi, C., F. Leali, M. Pellicciari, A.O. Andrisano, and G. Berselli, Selecting alternatives in the conceptual design phase: an application of Fuzzy-AHP and Pugh’s Controlled Convergence. International Journal on Interactive Design and Manufacturing (IJIDeM). 9(1): p. 1-17, 2015.Search in Google Scholar

[4] Renzi, C., F. Leali, and L. Di Angelo, A review on decision-making methods in engineering design for the automotive industry. Journal of Engineering Design. 28(2): p. 118-143, 2017.10.1080/09544828.2016.1274720Search in Google Scholar

[5] Olabanji, O.M. and K. Mpofu, Comparison of weighted decision matrix, and analytical hierarchy process for CAD design of reconfigurable assembly fixture, in Procedia CIRP. 2014. p. 264-269.10.1016/j.procir.2014.10.088Search in Google Scholar

[6] Yeo, S., M. Mak, and S. Balon, Analysis of decision-making methodologies for desirability score of conceptual design. Journal of Engineering Design. 15(2): p. 195-208, 2004.10.1080/09544820310001642191Search in Google Scholar

[7] Girod, M., A. Elliott, N.D. Burns, and I. Wright, Decision making in conceptual engineering design: an empirical investigation. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 217(9): p. 1215-1228, 2003.Search in Google Scholar

[8] Derelöv, M., On Evaluation of Design Concepts: Modelling Approaches for Enhancing the Understanding of Design Solutions. 2009, Linköping University Electronic Press.Search in Google Scholar

[9] Nikander, J.B., L.A. Liikkanen, and M. Laakso, The preference effect in design concept evaluation. Design studies. 35(5): p. 473-499, 2014.10.1016/j.destud.2014.02.006Search in Google Scholar

[10] Jugulum, R. and D.D. Frey, Toward a taxonomy of concept designs for improved robustness. Journal of Engineering Design. 18(2): p. 139-156, 2007.10.1080/09544820600731496Search in Google Scholar

[11] Mattson, C.A. and A. Messac, Pareto frontier based concept selection under uncertainty, with visualization. Optimization and Engineering. 6(1): p. 85-115, 2005.10.1023/B:OPTE.0000048538.35456.45Search in Google Scholar

[12] Hambali, A., S. Sapuan, A. Rahim, N. Ismail, and Y. Nukman, Concurrent decisions on design concept and material using analytical hierarchy process at the conceptual design stage. Concurrent Engineering. 19(2): p. 111-121, 2011.10.1177/1063293X11408138Search in Google Scholar

[13] Sa’Ed, M.S. and M.Y. Al-Harris, New product concept selection: an integrated approach using data envelopment analysis (DEA) and conjoint analysis (CA). International Journal of Engineering & Technology. 3(1): p. 44, 2014.Search in Google Scholar

[14] Hambali, A., S. Sapuan, N. Ismail, and Y. Nukman, Application of analytical hierarchy process in the design concept selection of automotive composite bumper beam during the conceptual design stage. Scientific Research and Essays. 4(4): p. 198-211, 2009.Search in Google Scholar

[15] Radhakrishnan, R. and D.A. McAdams, A methodology for model selection in engineering design. Journal of mechanical design. 127(3): p. 378-387, 2005.10.1115/1.1830048Search in Google Scholar

[16] Green, G. and G. Mamtani, An integrated decision making model for evaluation of concept design. Acta Polytechnica. 44(3) 2004.10.14311/582Search in Google Scholar

[17] Saridakis, K.M. and A.J. Dentsoras, Soft computing in engineering design–A review. Advanced Engineering Informatics. 22(2): p. 202-221, 2008.10.1016/j.aei.2007.10.001Search in Google Scholar

[18] Okudan, G.E. and R.A. Shirwaiker. A multi-stage problem formulation for concept selection for improved product design. in 2006 Technology Management for the Global Future-PICMET 2006 Conference. IEEE 2006.10.1109/PICMET.2006.296850Search in Google Scholar

[19] Akay, D., O. Kulak, and B. Henson, Conceptual design evaluation using interval type-2 fuzzy information axiom. Computers in Industry. 62(2): p. 138-146, 2011.10.1016/j.compind.2010.10.007Search in Google Scholar

[20] Mardani, A., A. Jusoh, K. Nor, Z. Khalifah, N. Zakwan, and A. Valipour, Multiple criteria decision-making techniques and their applications–a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja. 28(1): p. 516-571, 2015.10.1080/1331677X.2015.1075139Search in Google Scholar

[21] Xiao, A., S.S. Park, and T. Freiheit. A comparison of concept selection in concept scoring and axiomatic design methods. in Proceedings of the Canadian Engineering Education Association (CEEA). 2007.Search in Google Scholar

[22] Roy, B. and D. Vanderpooten, The European School of MCDA: Emergence, Basic Features and Current Works. Journal of Multi-Criteria Decision Analysis. 5(1): p. pp. 22-38, 1996.Search in Google Scholar

[23] Roy, B., Main Sources of Inaccurate Determination, Uncertainty and Imprecision in Decision Models. Mathl. Comput. Modelling12(10-11): pp. 1245-1254, 1989.Search in Google Scholar

[24] Ho, W., X. Xu, and P.K. Dey, Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of operational research. 202(1): p. 16-24, 2010.Search in Google Scholar

[25] Okudan, G.E. and S. Tauhid, Concept selection methods–a literature review from 1980 to 2008. International Journal of Design Engineering. 1(3): pp. 243-277, 2008.10.1504/IJDE.2008.023764Search in Google Scholar

[26] Belton, V. and T. Stewart, MULTIPLE CRITERIA DECISION ANALYSIS: An Integrated Approach. 2002: Springer Science+Business Media Dordrecht. pp. 13-52; ISBN 978-1-4615-1495-4 (eBook).Search in Google Scholar

[27] Ortiz-Barrios, M.A., B. Kucukaltan, D. Carvajal-Tinoco, D. Neira-Rodado, and G. Jiménez, Strategic hybrid approach for selecting suppliers of high-density polyethylene. Journal of Multi-Criteria Decision Analysis. 24(5-6): pp. 296-316, 2017.10.1002/mcda.1617Search in Google Scholar

[28] Alarcin, F., A. Balin, and H. Demirel, Fuzzy AHP and Fuzzy TOPSIS integrated hybrid method for auxiliary systems of ship main engines. Journal of Marine Engineering & Technology. 13(1): pp. 3-11, 2014.Search in Google Scholar

[29] Nazam, M., J. Xu, Z. Tao, J. Ahmad, and M. Hashim, A fuzzy AHP-TOPSIS framework for the risk assessment of green supply chain implementation in the textile industry. International Journal of Supply and Operations Management. 2(1): pp. 548, 2015.Search in Google Scholar

[30] Balin, A., H. Demirel, and F. Alarcin, A novel hybrid MCDM model based on fuzzy AHP and fuzzy TOPSIS for the most affected gas turbine component selection by the failures. Journal of Marine Engineering & Technology. 15(2): pp. 69-78, 2016.10.1080/20464177.2016.1216252Search in Google Scholar

[31] Glaize, A., A. Duenas, C. Di Martinelly, and I. Fagnot, Healthcare decision-making applications using multicriteria decision analysis: A scoping review. Journal of Multi-Criteria Decision Analysis, 26(1-2): pp. 62-83. 2019.10.1002/mcda.1659Search in Google Scholar

[32] Zeynali, M., M.H. Aghdaie, N. Rezaeiniya, and S.H. Zolfani, A hybrid fuzzy multiple criteria decision making (MCDM) approach to combination of materials selection. African Journal of Business Management. 6(45): pp. 11171-11178, 2012.Search in Google Scholar

[33] Kundakcı, N., An integrated method using MACBETH and EDAS methods for evaluating steam boiler alternatives. Journal of Multi-Criteria Decision Analysis. 26(1-2): p. 27-34, 2019.10.1002/mcda.1656Search in Google Scholar

[34] Olabanji, O. and K. Mpofu, Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept. Heliyon, Elsevier. 6(1): p. 1-13, 2020.10.1016/j.heliyon.2020.e03182Search in Google Scholar

[35] Olabanji, O.M. and K. Mpofu, Adopting hybridized multicriteria decision model as a decision tool in engineering design. Journal of Engineering, Design and Technology. 18(2): p. 451-479, 2020.10.1108/JEDT-06-2019-0150Search in Google Scholar

[36] Velu, L.G.N., J. Selvaraj, and D. Ponnialagan, A new ranking principle for ordering trapezoidal intuitionistic fuzzy numbers. Complexity. 2017 2017.10.1155/2017/3049041Search in Google Scholar

[37] Singh, P., A Novel Method for Ranking Generalized Fuzzy Numbers. J. Inf. Sci. Eng. 31(4): p. 1373-1385, 2015.Search in Google Scholar

[38] Nieto-Morote, A. and F. Ruz-Vila, A fuzzy AHP multi-criteria decision-making approach applied to combined cooling, heating, and power production systems. International Journal of Information Technology & Decision Making. 10(03): p. 497-517, 2011.10.1142/S0219622011004427Search in Google Scholar

[39] Zamani, S., H. Farughi, and M. Soolaki, Contractor selection using fuzzy hybrid AHPVIKOR. International Journal of Research in Industrial Engineering. 2(4): p. 26-40, 2014.Search in Google Scholar

[40] Tian, J. and Z. Yan, Fuzzy analytic hierarchy process for risk assessment to general-assembling of satellite. Journal of applied research and technology. 11(4): p. 568-577, 2013.10.1016/S1665-6423(13)71564-5Search in Google Scholar

[41] Somsuk, N. and C. Simcharoen, A fuzzy AHP approach to prioritization of critical success factors for six sigma implementation: Evidence from the electronics industry in thailand. International Journal of Modeling and Optimization. 1(5): p. 432-437, 2011.Search in Google Scholar

[42] Muller, G. Concept selection: theory and practice. in White paper of SESG meeting. sl: Buskerud University College. 2009.Search in Google Scholar

[43] Muller, G., D. Klever, H.H. Bjørnsen, and M. Pennotti, Researching the application of Pugh Matrix in the sub-sea equipment industry, in CSER. 2011.Search in Google Scholar

[44] Musani, S. and A.A. Jemain. Ranking schools’ academic performance using a fuzzy VIKOR. in Journal of Physics: Conference Series. IOP Publishing 2015.10.1088/1742-6596/622/1/012036Search in Google Scholar

[45] Shemshadi, A., H. Shirazi, M. Toreihi, and M.J. Tarokh, A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications. 38(10): p. 12160-12167, 2011.Search in Google Scholar

[46] Opricovic, S., Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications. 38(10): p. 12983-12990, 2011.Search in Google Scholar

[47] Kim, Y. and E.-S. Chung, Fuzzy VIKOR approach for assessing the vulnerability of the water supply to climate change and variability in South Korea. Applied Mathematical Modelling. 37(22): p. 9419-9430, 2013.Search in Google Scholar

[48] Chang, T.-H., Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Information Sciences. 271: p. 196-212, 2014.Search in Google Scholar

[49] Bag, S., Fuzzy VIKOR approach for selection of big data analyst in procurement management. Journal of Transport and Supply Chain Management. 10(1): p. 1-6, 2016.10.4102/jtscm.v10i1.230Search in Google Scholar

[50] Afful-Dadzie, E., S. Nabareseh, Z.K. Oplatková, and P. Klímek, Model for assessing quality of online health information: A fuzzy VIKOR based method. Journal of Multi-Criteria Decision Analysis. 23(1-2): p. 49-62, 2016.Search in Google Scholar

eISSN:
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Language:
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Journal Subjects:
Computer Sciences, Artificial Intelligence, Software Development