Material Selection Using TOPSIS Combined with Grey Relation Analysis

2014 ◽  
Vol 540 ◽  
pp. 476-479 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Problem ◽  
Grey Relation Analysis ◽  
Real Material ◽  
Selection Decisions ◽  
Multi Attribute Decision Making ◽  
Relation Analysis ◽  
Optimal Material ◽  
Grey Relation ◽  
Selection Of

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Material selection problem is a multi-attribute decision making (MADM) problem, which has several evaluation attributes. The selection decisions are complex, as material selection is more challenging today. This paper proposes a new MADM method for material selection problem. Combining the TOPSIS with grey relation analysis, the method proposed a comprehensive value to evaluate and select the best alternative. A real material selection case is used to demonstrate that the proposed method is effectiveness and feasibility.

Research on Material Selection with Multi-Attribute Decision Method and G1 Method

2014 ◽  
Vol 952 ◽  
pp. 20-24 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Topsis Method ◽  
Attribute Weight ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Optimal Material ◽  
Selection Of ◽  
Better Than

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Many factors (attributes) need to be considered in material selection process, and thus material selection problem is a multi-attribute decision making (MADM) problem. This paper proposes a new MADM method for material selection problem. G1 method does not need to test consistency of the judgment matrix. Thus it is better than AHP. In this paper, firstly, we use the G1 method to determine the attribute weight. Then TOPSIS method is used to calculate the closeness of the candidate materials with respect positive solution. A practical material selection case is used to demonstrate the effectiveness and feasibility of the proposed method.

Grinding Wheel Abrasive in Material Selection Using Fuzzy Grey Relation Analysis Method

2014 ◽  
Vol 1022 ◽  
pp. 18-21 ◽  
Author(s):  
Jian Hua Leng
Keyword(s):  
Material Selection ◽  
Influence Factors ◽  
Selection Problem ◽  
Variation Method ◽  
Grinding Wheel ◽  
Analysis Method ◽  
Grey Relation Analysis ◽  
Abrasive Material ◽  
Relation Analysis ◽  
Grey Relation

Material selection is an important step of product design process. There are often several influence factors in the grinding wheel abrasive material selection problem. This article will put forward a fuzzy grey relation analysis method to the grinding wheel abrasive material selection problem which influences factor (evaluation attribute) values expressed with triangular fuzzy numbers. The Coefficient of variation method will be adopted to determine the evaluation attributes’ weight. Finally, an example is used to analysis the effectiveness and feasibility of the proposed method.

Grey Relation Analysis Method for Material Selection Problem with Interval Numbers

2014 ◽  
Vol 1014 ◽  
pp. 492-496 ◽  
Author(s):  
Lian Wu Yang
Keyword(s):  
Decision Making ◽  
Material Selection ◽  
Selection Problem ◽  
Variation Method ◽  
Analysis Method ◽  
Grey Relation Analysis ◽  
Interval Numbers ◽  
Attribute Weights ◽  
Relation Analysis ◽  
Grey Relation

Material selection is an important step in the product design process. Material selection problem contains many influence factors, and thus it is actually a multi-attribute decision making problem. In some situations, measure values cannot or unsuitable to be depicted by crisp numbers. Interval number is a suitable selection in these situations, and for the material selection problem with interval numbers, a new decision making method is developed based on grey relation analysis method. The attribute weights will be determined by the coefficient of variation method. Finally, a practical example is used to illustrate the effectiveness and feasibility of the proposed method.

Research on Multi-Attribute Decision Making Using Grey Relation Analysis, Information Axiom and Fuzzy Preferences

2008 ◽  
Vol 44-46 ◽  
pp. 587-594 ◽  
Author(s):  
Xian Fu Cheng
Keyword(s):  
Decision Making ◽  
Information Content ◽  
Data Series ◽  
Grey Relation Analysis ◽  
Fuzzy Preferences ◽  
Information Axiom ◽  
Multi Attribute Decision Making ◽  
Relation Analysis ◽  
Grey Relation ◽  
The Ideal

The grey relation analysis is a kind of quantitative analysis method based on factors compared. The information axiom of axiomatic design provides a mean of evaluation by comparing the information content of several alternatives, based on which a new method for multi-attribute decision making is proposed. First, according to decision matrix of all decision making criteria, the ideal alternative composed of the best reference data series among all alternatives is constructed. Then the information content is used to evaluate the relation grade between an individual alternative and the ideal alternative. The fuzzy preferences are utilized to determine the weight of each criterion. The total information content of every alternative is calculated, and arrayed in order, so the optimal alternative can be selected. For requirements of evaluation, the calculation formula of information content is amended. Finally, an example is given to illustrate the effectiveness and feasibility of the proposed method.

Fuzzy grey relation analysis on torque influence factors of alternating current electrodyna-mometer

2013 ◽  
Vol 26 (8) ◽  
pp. 693-698 ◽  
Author(s):  
Zhigang Zhang ◽  
Guixiang Zhang ◽  
Teng Liu ◽  
Cheng Qian ◽  
Yuanwang Deng
Keyword(s):  
Influence Factors ◽  
Alternating Current ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Grey Relation
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