A hybrid multiple‐criteria decision‐making approach for selecting optimal automotive brake friction composite

Singh, Tej

doi:10.1002/mdp2.266

Cited by 25 publications

(14 citation statements)

References 31 publications

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“…AHP calculations are logical and easy to perform. A key step in the approach is to construct the pairwise comparison matrix ( Singh, 2021 ). Recall that if criterion A is more important (or as important) as criterion B , we need to enter a weight that indicates how many times more important criterion A is compared to criterion B , and automatically enter its inverse in the transpose position.…”

Section: Resultsmentioning

confidence: 99%

Integrated TOPSIS-COV approach for selecting a sustainable PET waste management technology: A case study in Qatar

Al-Thani

Al‐Ansari

Haouari

2022

Heliyon

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Section: Resultsmentioning

confidence: 99%

Integrated TOPSIS-COV approach for selecting a sustainable PET waste management technology: A case study in Qatar

Al-Thani

Al‐Ansari

Haouari

2022

Heliyon

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“…MADM approaches are the systematic ways for determining the importance of attributes (material properties) by examining a specific application and selecting the best candidate material, while eliminating the inappropriate alternatives [35,36]. Various MADM approaches, such as AHP, GRA, CRITIC, TOPSIS, VIKOR, SAW, MEW, COPRAS, PSI and ELECTRE, etc., have been created to assist in rating material alternatives and picking the best one [37][38][39][40][41][42][43][44]. Among them, MABAC and CRITIC are two popular ones.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm

et al. 2022

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Based on the criteria importance through inter-criteria correlation (CRITIC) and the multi-attributive border approximation area comparison (MABAC), a decision-making algorithm was developed to select the optimal biocomposite material according to several conflicting attributes. Poly(lactic acid) (PLA)-based binary biocomposites containing wood waste and ternary biocomposites containing wood waste/rice husk with an overall additive content of 0, 2.5, 5, 7.5 and 10 wt.% were manufactured and evaluated for physicomechanical and wear properties. For the algorithm, the following performance attributes were considered through testing: the evaluated physical (density, water absorption), mechanical (tensile, flexural, compressive and impact) and sliding wear properties. The water absorption and strength properties were found to be the highest for unfilled PLA, while modulus performance remained the highest for 10 wt.% rice husk/wood-waste-added PLA biocomposites. The density of PLA biocomposites increased as rice husk increased, while it decreased as wood waste increased. The lowest and highest density values were recorded for 10 wt.% wood waste and rice husk/wood-waste-containing PLA biocomposites, respectively. The lowest wear was exhibited by the 5 wt.% rice husk/wood-waste-loaded PLA biocomposite. The experimental results were composition dependent and devoid of any discernible trend. Consequently, prioritizing the performance of PLA biocomposites to choose the best one among a collection of alternatives became challenging. Therefore, a decision-making algorithm, called CRITIC–MABAC, was used to select the optimal composition. The importance of attributes was determined by assigning weight using the CRITIC method, while the MABAC method was employed to assess the complete ranking of the biocomposites. The results achieved from the hybrid CRITIC–MABAC approach demonstrated that the 7.5 wt.% wood-waste-added PLA biocomposite exhibited the optimal physicomechanical and wear properties.

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“…These are statistical methods used to tackle complex decision-making problems utilising a finite number of qualities and options [ 31 ]. MCDM approaches include AHP (analytic hierarchy process), MOORA (multiple objective optimisation on the basis of ratio analysis), TOPSIS (a technique for the ordering of preference by similarity to ideal solution), VIKOR (vise kriterijumska optimizacija kompromisno resenje), MABAC (multi-attributive border approximation area comparison), SAW (simple additive weighting), MEW (multiplicative exponent weighting), and COPRAS (complex proportional assessment) have been effectively deployed to tackle a variety of decision-making problems [ 32 , 33 , 34 , 35 , 36 , 37 ]. Among them, MOORA and AHP are very popular.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Ceramic Based Hip Implant Composites Using Hybrid AHP-MOORA Approach

Singh

Goswami²,

Patnaik

et al. 2022

Materials

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Designing excellent hip implant composite material with optimal physical, mechanical and wear properties is challenging. Improper hip implant composite design may result in a premature component and product failure. Therefore, a hybrid decision-making tool was proposed to select the optimal hip implant composite according to several criteria that are probably conflicting. In varying weight proportions, a series of hip implant composite materials containing different ceramics (magnesium oxide, zirconium oxide, chromium oxide, silicon nitride and aluminium oxide) were fabricated and evaluated for wear and physicomechanical properties. The density, void content, hardness, indentation depth, elastic modulus, compressive strength, wear, and fracture toughness values were used to rank the hip implant composites. It was found that the density and void content of the biocomposites remain in the range of 3.920–4.307 g/cm3 and 0.0021–0.0089%, respectively. The composite without zirconium oxide exhibits the lowest density (3.920 g/cm3), while the void content remains lowest for the composite having no chromium oxide content. The highest values of hardness (28.81 GPa), elastic modulus (291 GPa) and fracture toughness (11.97 MPa.m1/2) with the lowest wear (0.0071 mm3/million cycles) were exhibited by the composites having 83 wt.% of aluminium oxide and 10 wt.% of zirconium oxide. The experimental results are compositional dependent and without any visible trend. As a result, selecting the best composites among a group of composite alternatives becomes challenging. Therefore, a hybrid AHP-MOORA based multi-criteria decision-making approach was adopted to choose the best composite alternative. The AHP (analytic hierarchy process) was used to calculate the criteria weight, and MOORA (multiple objective optimisation on the basis of ratio analysis) was used to rank the composites. The outcomes revealed that the hip implant composite with 83 wt.% aluminium oxide, 10 wt.% zirconium oxide, 5 wt.% silicon nitride, 3 wt.% magnesium oxide, and 1.5 wt.% chromium oxide had the best qualities. Finally, sensitivity analysis was conducted to determine the ranking’s robustness and stability concerning the criterion weight.

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A hybrid multiple‐criteria decision‐making approach for selecting optimal automotive brake friction composite

Cited by 25 publications

References 31 publications

Integrated TOPSIS-COV approach for selecting a sustainable PET waste management technology: A case study in Qatar

Integrated TOPSIS-COV approach for selecting a sustainable PET waste management technology: A case study in Qatar

Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC–MABAC-Based Decision-Making Algorithm

Optimal Design of Ceramic Based Hip Implant Composites Using Hybrid AHP-MOORA Approach

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