scholarly journals A fuzzy logic based PROMETHEE method for material selection problems

2018 ◽  
Vol 7 (1) ◽  
pp. 68-79 ◽  
Author(s):  
Muhammet Gul ◽  
Erkan Celik ◽  
Alev Taskin Gumus ◽  
Ali Fuat Guneri
Keyword(s):  
Fuzzy Logic ◽  
Material Selection ◽  
Selection Problems ◽  
Promethee Method

Material Selection Using a Novel Multiple Attribute Decision Making Method

2012 ◽  
pp. 252-266
Author(s):  
R. V. Rao ◽  
B. K. Patel
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Maker ◽  
Design Process ◽  
Material Selection ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Selection Problem ◽  
Multiple Attribute ◽  
Selection Of

Selection of a most appropriate material is a very important task in design process of every product. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel multiple attribute decision making (MADM) method for solving the material selection problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Two examples are presented to illustrate the potential of the proposed method.

A Fuzzy Logic Based Rocket Launch Tube’s DFMEA

2011 ◽  
Vol 87 ◽  
pp. 119-122
Author(s):  
Tosapolporn Pornpibunsompop ◽  
Attapon Charoenpon ◽  
Ekaratch Pankaew
Keyword(s):  
Fuzzy Logic ◽  
Failure Modes ◽  
Mechanical Load ◽  
Material Selection ◽  
Early Stage ◽  
Rule Base ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Potential Failure ◽  
Launch Tube

DFMEA is a significantly efficient tool to systematically evaluate risk in early stage of product design and development but some of knowledge and information are uncertain and imprecise. This research focuses on fuzzy logic approach to diminish weaknesses and applies to launch tube’s DFMEA. The methodology started from determine membership function of severity, occurrence, and detection and provide fuzzy rule base to arranged category of risk. Afterwards, center average index was selected as defuzzifier for risk value representation. Consequently, the prioritization based on risk value was done and chosen the first five risk value of potential failure modes to analyze causes then recommended appropriate actions. After application of fuzzy logic approach, the most vital potential failure mode is damaged launch tube due to detention force which is rated as first and second priority depending on potential cause or mechanism. The third priority is launch tube distortion. The mechanical load calculation and proper material selection are the recommended actions for overcoming those potential failure modes.

scholarly journals Some Interval 2-Tuple Linguistic Harmonic Mean Operators and Their Application in Material Selection

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Meng-Meng Shan ◽  
Jian-Xin You ◽  
Hu-Chen Liu
Keyword(s):  
Group Decision ◽  
Material Selection ◽  
Aggregation Operators ◽  
Harmonic Mean ◽  
Linguistic Variables ◽  
Practical Application ◽  
Linguistic Information ◽  
Selection Problems ◽  
Operational Laws ◽  
Multiple Attribute

We investigate the multiple attribute group material selection problems in which the attribute values take the form of interval 2-tuple linguistic information. Firstly, some operational laws and possibility degree of interval 2-tuple linguistic variables are introduced. Then, we develop some interval 2-tuple linguistic aggregation operators called interval 2-tuple hybrid harmonic mean (ITHHM) operator, induced interval 2-tuple ordered weighted harmonic mean (I-ITOWHM) operator, and induced interval 2-tuple hybrid harmonic mean (I-ITHHM) operator and study some desirable properties of the I-ITOWHM operator. In particular, all these operators can be reduced to aggregate 2-tuple linguistic variables. Based on the I-ITHHM and the ITWHM (interval 2-tuple weighted harmonic mean) operators, an approach to multiple attribute group decision-making with interval 2-tuple linguistic information is proposed. Finally, a practical application to material selection problem is given to verify the developed approach and to demonstrate its practicality and effectiveness.

scholarly journals Optimizing Material Selection Using a Hybridized Multi-attribute Decision Making Model

2021 ◽  
Vol 16 ◽  
pp. 404-421
Author(s):  
Eslam Mohammed Abdelkader ◽  
Abobakr Al-Sakkaf ◽  
Ghasan Alfalah
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Material Selection ◽  
Rank Correlation ◽  
Multi Criteria Decision Making ◽  
Numerical Examples ◽  
Selection Problems ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Selection Of

Material selection is a very entangled and decisive stage in the design and development of products. There are large numbers of on hand and newly developed materials available in the market. In addition, inability to select the correct materials adversely affects the reputation and profitability of the company. Thus, designers need to study and trace the performance of available materials with appropriate functionalities. Thus, this research aims at establishing an efficient and systematic platform for the optimum selection of materials while accommodating the designated conflicting performance requirements. The developed model encompasses designing a hybrid decision support system in an attempt to circumvent the shortcomings of single multi-criteria decision making-based (MCDM) models. First, the objective relative importance weights of attributes are interpreted capitalizing on Shannon entropy algorithm. Then, an integrated model that encompasses the utilization of six different types of multi-criteria decision making algorithms is designed to create a reliable selection of material alternatives. The utilized MCDM algorithms comprise weighted product method (WPM), simple additive weighting (SAW), additive ratio assessment (ARAS), new combinative distance-based assessment (CODAS), complex proportional assessment (COPRAS) and technique for order of preference by similarity to ideal solution (TOPSIS). Afterwards, COPELAND algorithm is exploited to generate a consensus and distinct ranking of material alternatives. Eventually, Spearman’s rank correlation analysis is used to evaluate the rankings obtained from the MCDM algorithms. Five numerical examples in diverse fields of material selection are tackled to examine the features and efficiency of the developed integrated model. Results illustrated that the developed model was able to solve the five material selection problems efficiently. On the other hand, no individual MCDM algorithm was able to solve all the assigned material selection problems. For instance, CODAS and TOPSIS only succeeded in solving one and two material selection problems, respectively. It was also inferred that notable differences and perturbations are encountered between the rankings of MCDM algorithms in the first, third, fourth and fifth numerical examples, which necessitates the implementation of COPELAND algorithm. It was also revealed that the highest correlation lied between COPRAS and WPM with an average Spearman’s rank correlation coefficient of 92.67%. On the other hand, the correlation between TOPSIS and CODAS attained the lowest rank with an average Spearman’s rank correlation coefficient of 18.95%. Results also demonstrated that COPRAS accomplished the highest Spearman’s rank correlation coefficient with 59.54%. Hence, it is the most efficient MCDM algorithm among the five algorithms which can serve as a reference for solving material selection problems. It can be also deduced that CODAS and TOPSIS are not advised to be implemented in solving similar material selection problems.

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