Abstract
Material selection is an important problem attracting theoretical and practical interest. Nowadays, a lot of materials and alloys are designed. In most alloys some properties are good and in compliance with the requirements, but some of them are not acceptable. Generally, for material selection methods it is necessary to have unique synergy of theoretical knowledge and practical experiences data. Scientists used and developed some selection methods due to all of these.
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References
Frang, M.: Quantitative Methods of Material Selection. Handbook of Material Selection (2002)
Ashby, M.: Materials Selection in Mechanical Design. Butterworth-Heinemann, Oxford (2010)
Cebon, D., Ashby, M.: Data systems for optimal material selection. Adv. Mat. Process. 161(6), 51–54 (2003)
Jahan, A., Edwards, K.L.: Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design. Butterworth-Heinemann, Oxford (2016)
Ashby, M.: Multi-objective optimization in material design and selection. Acta Materilia 48, 359–369 (2000)
Jahan, A., Ismail, M.Y., Sapuan, S.M., Mustapha, F.: Material screening and choosing methods – a review. Mater. Des. 31, 696–705 (2010)
Cavallini, C., Giorgetti, A., Citti, P., Nicolaie, F.: Integral aided method for material selection based on quality function deployment and comprehensive VIKOR algorithm. Mater. Des. 47, 27–34 (2013)
Zafarani, H.R., Hassani, A., Bagherpour, E.: Achieving a desirable combination of strength and workability in Al/SiC composites by AHP selection method. J. Alloy. Compd. 589, 295–300 (2014)
Shimin, V.V., Shah, V.A., Lokhande, M.M.: Material selection for semiconductor switching devices in electric vehicles using Analytic Hierarchy Process (AHP) method. In: IEEE International Conference on Intelligent Control and Energy Systems (ICPEICES) (2016)
Kiong, S.C., et al.: Decision making with the Analytical Hierarchy Process (AHP) for material selection in screw manufacturing for minimizing environmental impacts. Appl. Mech. Mater. 315, 57–62 (2013)
Athawale, V.M., Chakraborty, S.: Material selection using multi-criteria decision-making methods: a comparative study. In: Proceedings of Institution of Mechanical Engineers, Part L, vol. 226, no. 4, pp. 267–286 (2012). Journal of Materials: Design and Applications
Flywheels move from steam age technology to Formula 1: Jon Stewart (2012)
Jee, D.-H., Kang, K.-J.: A method for optimal material selection aided with decision making theory. Mater. Des. 21(3), 199–206 (2000)
Rai, D., Jha, G.K., Chatterjee, P., Chakraborty, S.: Material selection in manufacturing environment using compromise ranking and regret theory-based compromise ranking methods: a comparative study. Univ. J. Mater. Sci. 1(2), 69–77 (2013)
Chatterjee, P., Chakraborty, S.: Material selection using preferential ranking methods. Mater. Des. 35, 384–393 (2012)
Jahan, A., Bahraminasab, M., Edwards, K.L.: A target-based normalization technique for materials selection. Mater. Des. 35, 647–654 (2012)
Kl, E.: Selecting materials for optimum use in engineering components. Mater. Des. 26, 469–474 (2005)
Fayazbakhsh, K., Abedian, A., Manshadi, B.D., Khabbaz, R.S.: Introducing a novel method for materials selection in mechanical design using Z-transformation in statistics for normalization of material properties. Mater. Des. 30, 4396–4404 (2009)
Chatterjee, P., Athawale, V.M., Chakraborty, S.: Materials selection using complex proportional assessment and evaluation of mixed data methods. Mater. Des. 32, 851–860 (2011)
Milani, A.S., Shanian, A., Madoliat, R., Nemes, J.A.: The effect of normalization norms in multiple attribute decision making methods: a case study in gear material selection. Struct. Multidisc. Optim. 29, 312–318 (2005)
Jeya Girubha, R., Vinodh, S.: Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Mater. Des. 37, 478–486 (2012)
Ahn, K.K., Kha, N.B.: Modeling and control of shape memory alloy actuators using Preisach model, genetic algorithm and fuzzy logic. Mechatronics 18, 141–152 (2008)
Xue, Y.-X., You, J.-X., Lai, X.-D., Liu, H.-C.: An interval-valued intuitionistic fuzzy MABAC approach for materialselection with incomplete weight information. Appl. Soft Comput. 38, 703–713 (2016)
Gul, M., Celik, E., Gumus, A.T., Guneri, A.F.: A fuzzy logic based PROMETHEE method for material selection problems. Beni-Suef Univ. J. Basic Appl. Sci. 7, 68–79 (2018)
Zhu, X.F.: A web-based advisory system for process and material selection in concurrent product design for a manufacturing environment. Adv. Manuf. Technol. 25, 233–243 (2005)
Welling, D.A.: A fuzzy logic material selection methodology for renewable ocean energy applications by proquest, Umi Dissertation Publishing (2011)
Zadeh, L.A.: A note on Z-numbers. Inf. Sci. 181, 2923–2932 (2011)
Babanli, M.B., Huseynov, V.M.: Z-number-based alloy selection problem. In: 12th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2016, Vienna, Austria, vol. 102, pp. 183–189 (2016). Procedia Computer Science
Jahan, A., Ismail, M.Y., Shuib, S., Norfazidah, D., Edwards, K.L.: An aggregation technique for optimal decision-making in materials selection. Mater. Des. 32, 4918–4924 (2011)
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Babanli, M.B. et al. (2019). Material Selection Methods: A Review. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_123
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