Relative Ratio Method for Material Selection Problem with Interval Numbers

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Abstract:

Material selection is an important research aspect for manufacturing companies. To select a best material, many different tools are used to measure the candidate materials for many influence factors and in different situations, which will give a range of values. These measure values can be depicted with interval numbers. Then the material selection problem is actually a multi-attribute decision making (MADM) problem. Then this paper we will propose a MADM method based on the relative ratio method for the material selection problem. Coefficient of variation method will be used to determine the evaluation indexes’ weight. Finally, a practical example is presented to demonstrate the effectiveness and feasibility of the proposed method.

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29-32

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August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] H. C. Liu, L. X. Mao, Z. Y. Zhang and P. Li. Induced aggregation operators in the VIKOR method and its application in material selection. Applied Mathematical Modelling, Vol. 37 (2013), pp.6325-6338.

DOI: 10.1016/j.apm.2013.01.026

Google Scholar

[2] A. Shanian and O. Savadogo. A material selection model based on the concept of multiple attribute decision making. Materials and Design Vol. 27 (2006), pp.329-337.

DOI: 10.1016/j.matdes.2004.10.027

Google Scholar

[3] K. Maniya and M.G. Bhatt. A selection of material using a novel type decision making method: preference selection index method. Materials and Design Vol. 31 (2010), pp.1785-1789.

DOI: 10.1016/j.matdes.2009.11.020

Google Scholar

[4] L. Anojkumar, M. Ilangkumaran and V. Sasirekha. Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications, Vol. 41 (2014), pp.2964-2980.

DOI: 10.1016/j.eswa.2013.10.028

Google Scholar

[5] A. H. Peng and X. M. Xiao. Material selection using PROMETHEE combined with analytic network process under hybrid environment. Materials and Design, Vol. 47 (2013), pp.643-652.

DOI: 10.1016/j.matdes.2012.12.058

Google Scholar

[6] R. Khorshidi and A. Hassani. Comparative analysis between TOPSIS and PSI methods of materials selection to achieve a desirable combination of strength and workability in Al/SiC composite. Materials and Design, Vol. 52 (2013), pp.999-1010.

DOI: 10.1016/j.matdes.2013.06.011

Google Scholar

[7] M. R. Mansor, S. M. Sapuan, E. S. Zainudin, A. A. Nuraini and A. Hambali. Hybrid natural and glass fibers reinforced polymer composites material selection using Analytical Hierarchy Process for automotive brake lever design. Materials and Design, Vol. 51 (2013).

DOI: 10.1016/j.matdes.2013.04.072

Google Scholar

[8] T. W. Liao. A fuzzy multicriteria decision-making method for material selection. Journal of Manufacturing Systems, Vol. 15 (1996), pp.1-12.

DOI: 10.1016/0278-6125(96)84211-7

Google Scholar

[9] A. S. Milani and A. Shanian. Gear material selection with uncertain and incomplete data. Material performance indices and decision aid model. International Journal of Mechanics and Materials in Design, Vol. 3 (2006), pp.209-222.

DOI: 10.1007/s10999-007-9024-4

Google Scholar

[10] P. Chatterjee and S. Chakraborty. Material selection using preferential ranking methods. Materials and Design, Vol. 35 (2012), pp.384-393.

DOI: 10.1016/j.matdes.2011.09.027

Google Scholar

[11] A. Jahan and K. L. Edwards. VIKOR method for material selection problems with interval numbers and target-based criteria. Materials and Design, Vol. 47 (2013), pp.759-765.

DOI: 10.1016/j.matdes.2012.12.072

Google Scholar

[12] R. J. Girubha and S. Vinodh. Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Materials and Design, Vol. 37 (2012), pp.478-486.

DOI: 10.1016/j.matdes.2012.01.022

Google Scholar

[13] Q. Z. Hu and W. H. Zhang. Study and Application of Interval Number Theory. (Science Press, Beijing 2010).

Google Scholar

[14] Y. Zhang and Z. P. Fan. A method for interval multiple attribute decision making with partial attribute weight information, Journal of Harbin Institute of Technology, Vol. 40 (2008), pp.1673-1675.

Google Scholar

[15] Z.S. Xu. Uncertain Multiple Attribute Decision Making Methods and Applications. (Tsinghua University Press, Beijing 2004).

Google Scholar

[16] B.H. Men and C. Liang. Attribute recognition model-based variation coefficient weight for evaluating water quality, Journal of Harbin Institute of Technology, Vol. 37 (2005), pp.1373-1375.

Google Scholar

[17] A. S. Milani, A. Shanian, R. Madoliat and J. A. Nemes. The effect of normalization norms in multiple attribute decision making models: a case study in gear material selection. Structural and Multidisciplinary Optimization, Vol. 29 (2005).

DOI: 10.1007/s00158-004-0473-1

Google Scholar