Investigation on Switching Structure Material Selection for RF-MEMS Shunt Capacitive Switches Using Ashby, TOPSIS and VIKOR

Deshmukh, Deepankar; Angira, Mahesh

doi:10.1007/s42341-018-00094-3

Cited by 19 publications

(15 citation statements)

References 8 publications

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“…To test the effectiveness of the proposed method, the following MADM methods are considered. Method 1: RSR 22 , 23 Method 2: SAW 1, 2 , 17 , 24 Method 3: WPM 1 , 2 Method 4: TOPSIS 1 , 2 , 4 , 6–11 , 16 , 17 , 24–29 , 33 Method 5: GRA 1 , 2 , 24 , 28–31 Method 6: VIKOR 1 , 2 , 4 , 9 , 11 , 32–34 Method 7: PROMETHEE 1 , 2 , 12 , 14 Method 8: The MADM method combined with different MADM methods 3 Method 9: The MADM method based on the traditional semi-circular constellation graph Method 10: The MADM method based on the quadrant circular constellation graph …”

Section: Methodsmentioning

confidence: 99%

“…10 applied the decision models including EXPROM2, TOPSIS and VIKOR methods to select the optimal material for tool holder used in hard milling. Deshmukh and Angira 11 utilized three MADM methods (Ashby, TOPSIS and VIKOR) to select the most promising material for switching structure of RF-MEMS shunt capacitive switches. Peng and Xiao 12 applied the PROMETHEE method and analytic network process (ANP) to select the optimal material for a journal bearing.…”

Section: Introductionmentioning

confidence: 99%

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A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

Yang¹,

Kim²,

Ji-Yon³

2021

Proceedings of the Institution of Mechanical Engineers, Part L:

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Traditional constellation graphical method maps a multidimensional data into a 2D graph. In this paper, the drawback of the traditional semi-circular constellation graph is considered and a quadrant circular constellation graph is proposed to overcome the drawback. Moreover, a new materials selection MADM (multi-attribute decision making) method is proposed based on the quadrant circular constellation graph. This method is applied to select the best magnesium alloy material for automotive wheels. The numerical and graphical results show that AZ91 is the optimal material among the alternative materials such as AZ91, AM60, AM50, AZ31, ZE41, EZ33, ZE63 and ZC63. The result is compared with the results from the previous MADM methods from the viewpoint of Spearman’s rank correlation and deviation. Additionally, a sensitivity analysis to attribute weights is performed to test the robustness of the proposed method. Experimental results demonstrate that the proposed method is superior to the previous MADM methods. The proposed method is not only quantitative but also intuitive method. It could be widely used to materials selection problems in engineering practice.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

Yang¹,

Kim²,

Ji-Yon³

2021

Proceedings of the Institution of Mechanical Engineers, Part L:

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“…Radio Frequency Micro Electro Mechanical Systems (RF-MEMS) is a promising technology for implementing passive devices in future wireless communication systems (Deshmukh & Angira, 2019). Switches have drawn more attention due to their frequent use in many cases in wireless communication systems.…”

Section: ) Multi-objective Optimization In the Materials Selection Of Rf-mems Shunt Capacitive Switchesmentioning

confidence: 99%

“…Ashby's method is difficult to be applied in cases which involve multiple criteria of selection (Ashby, 2000;Ashby et al, 2004;Zheng et al, 2021). Deshmukh et al employed the multi-objective optimization (MOO) techniques of TOPSIS and VIKOR to perform the material selection of the switching structure for RE-MEMS shunt capacitive switches (Deshmukh & Angira, 2019). However, there exist inherent problems of additive algorithms and subjective factors in the MADM, AHP, MOORA, TOPSIS and VIKOR due to their fatal scaling or normalization processes (Zheng et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Application of probability-based multi-objective optimization in material engineering

Zheng¹

2022

Vojnotehnički glasnik

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Introduction/purpose: Althought many methods have been proposed to deal with the problem of material selection, there are inherent defects of additive algorithms and subjective factors in such algorithms. Recently, a probability-based multi-objective optimization was developed to solve the inherent shortcomings of the previous methods, which introduces a novel concept of preferable probability to reflect the preference degree of the candidate in the optimization. In this paper, the new method is utilized to conduct an optimal scheme of the switching material of the RF-MEMS shunt capacitive switch, the sintering parameters of natural hydroxyapatite and the optimal design of the connecting claw jig. Methods: All performance utility indicators of candidate materials are divided into two groups, i.e., beneficial or unbeneficial types for the selection process; each performance utility indicator contributes quantitatively to a partial preferable probability and the product of all partial preferable probabilities makes the total preferable probability of a candidate, which transfers a multi-objective optimization problem into a single-objective optimization one and represents a uniquely decisive index in the competitive selection process. Results: Cu is the appropriate material in the material selection for RF - MEMS shunt capacitive switches; the optimal sintering parameters of natural hydroxyapatite are at 1100°C and 0 compaction pressure; and the optimal scheme is scheme No 1 for the optimal design of a connecting claw jig. Conclusion: The probability-based multi-objective optimization can be easily used to deal with an optimal problem objectively in material engineering.

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“…Çalıskan et al [Çalıskan, Kursuncu, Kurbanoglu et al (2013)] applied decision models including EXPROM2, TOPSIS and VIKOR methods to select best material for the tool holder used in hard milling. Deshmukh et al [Deshmukh and Angira (2019)] utilized three material selection methodologies to select the most promising material for switching structure of RF-MEMS shunt capacitive switches. The Ashby, TOPSIS and VIKOR methods were used to select the best material.…”

Section: Introductionmentioning

confidence: 99%

Materials Selection Method Combined with Different MADM Methods

Yang¹,

Chon²,

Choe³

et al. 2019

Journal on Artificial Intelligence

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Materials selection is a multiple attribute decision making (MADM) problem. A lot of MADM methods are applicable to materials selection, and it may produce considerable differences between the results of materials selection. But it is unknown which MADM method is better. So it is desirable to decide reasonable final result of materials selection in consideration of the individual results from different MADM methods. In this paper, materials selection method combined with different MADM methods is proposed. The method is based on final ranks of alternative materials, where the final ranks are determined from the ranks of the alternative materials using different MADM methods. This method is applied to select optimal magnesium alloy material for automobile wheels. This method may be widely used to select optimal material in engineering practice.

show abstract

Investigation on Switching Structure Material Selection for RF-MEMS Shunt Capacitive Switches Using Ashby, TOPSIS and VIKOR

Cited by 19 publications

References 8 publications

A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

Application of probability-based multi-objective optimization in material engineering

Materials Selection Method Combined with Different MADM Methods

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