Grey relational analysis for optimization of wear parameters and surface roughness on nano composite coating

Raghavendra, C. R.; Basavarajappa, S.; Sogalad, Irappa

doi:10.1016/j.jics.2021.100171

Cited by 8 publications

(4 citation statements)

References 41 publications

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“…GRA has been used in many fields, including engineering, economics, and management, to solve complex problems and optimize systems. In the context of FGMs, GRA can be used to optimize the properties of the material by determining the optimal distribution of the constituent materials along the thickness of the material [53,54]. Functionally graded composites are materials that have varying properties and composition along their length or thickness, which can result in improved performance and functionality [55,56].…”

Section: Grey Relational Analysismentioning

confidence: 99%

Optimization and Characterization of Centrifugal-Cast Functionally Graded Al-SiC Composite Using Response Surface Methodology and Grey Relational Analysis

et al. 2023

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In this study, an optimization approach was employed to determine the optimal main parameters that improve the performance of functionally graded composites manufactured using a combination of stirring and horizontal centrifugal casting. Pure aluminum reinforced with silicon carbide particles was used as the material for the composites. The effects of key input parameters such as mold speed, pouring temperature, stirring speed, and radial distance were optimized using a combination of grey relational analysis and response surface methodology. The statistical significance of the predicted grey relational grade model was assessed through an analysis of variance to identify the appropriate main parameters. The results showed that radial distance had the greatest impact on the performance of the composites, followed by pouring temperature. The optimal combination of main parameters was determined to be a mold speed of 1000 rpm, a pouring temperature of 750 °C, a stirring speed of 150 rpm, and a radial distance of 1 mm. Confirmation tests using these optimal values resulted in a 54.69% improvement in the grey relational grade.

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Section: Grey Relational Analysismentioning

confidence: 99%

Optimization and Characterization of Centrifugal-Cast Functionally Graded Al-SiC Composite Using Response Surface Methodology and Grey Relational Analysis

et al. 2023

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“…This optimization problem was solved using the gray relation analysis (GRA) method (Raghavendra et al 2021). Table 12 presents the alternatives for wear parameters and their criteria, based on which alternatives were ranked.…”

Section: Optimization Of Wear Parameter For Composite Coatingmentioning

confidence: 99%

Optimization of Wear Parameters for Duplex-TiAlN Coated MDC-K Tool Steel Using Fuzzy MCDM Techniques

Kumar

Maity

Patnaik

2022

Oper. Res. Eng. Sci. Theor. Appl.

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The present work evaluates the effects of different tribological process parameters on the measured responses such as hardness, coefficient of friction, surface roughness, wear mass loss and wear depth of duplex-TiAlN coated MDC-K tool steel material. The considered tribological process parameters are load, sliding velocity, and sliding distance. A full factorial design with 27 experimental runs is employed and based on the response values, an optimal combination of the tribological process parameters is subsequently determined. Different multi-objective optimization techniques, like overall evaluation criteria and fuzzy-based multi-criteria decisionmaking methods (fuzzy evaluation based on distance from the average solution, fuzzy technique for order of preference by similarity to ideal solution, and fuzzy complex proportional assessment) are utilized to identify the optimal intermixes of the considered tribological process parameters. Sensitivity analysis with respect to changing weights of the responses is performed to validate the derived rankings of the trials, whereas the results of analysis of variance revealed the most significant parameters were influencing the responses. In addition to this, two different published problems related to optimization of wear parameters were solved using the proposed method to check its capability.

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“…Recently, the application of the Taguchi method, GRA, and Topsis has received increasing attention and has become extremely relevant in various research fields. These methods have proven to be extremely effective tools for process optimization, decision-making, and product quality improvement [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…Raghavendra et al optimized wear parameters and surface roughness on composite coatings using response surface methodology (RSM) based GRA [9]. Analysis of variance (ANOVA) analysis found that normal load has the greatest influence on wear rate and pin temperature, which are 36.88% and 61.26%, respectively.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Tribological Characteristics for Aluminum Composite Using Taguchi Grey and TOPSIS Approaches

Gajević,

Marković,

Milojević

et al. 2024

Lubricants

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In this study, a multi-objective optimization regarding the tribological characteristics of the hybrid composite with a base material of aluminum alloy A356 as a constituent, reinforced with a 10 wt.% of silicon carbide (SiC), size 39 µm, and 1, 3, and 5 wt.% graphite (Gr), size 35 µm, was performed using the Taguchi method, gray relational analysis (GRA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making methods. Tribological tests were carried out on a “block on disc” type tribometer with lubrication. Load, sliding speed, and graphite mass concentration were analyzed as input parameters. As output parameters, wear rate and coefficient of friction were calculated. An analysis of variance (ANOVA) was conducted to identify all parameters that have a significant influence on the output multi-response. It was found that the normal load has the highest influence of 41.86%, followed by sliding speed at 32.48% and graphite addition at 18.47%, on the tribological characteristics of composites. Multi-objective optimization determined that the minimal wear rate and coefficient of friction are obtained when the load is 40 N, the sliding speed is 1 m/s, and the composite contains 3 wt.% Gr. The optimal combination of parameters achieved by GRA was also confirmed by the TOPSIS method, which indicates that both methods can be used with high reliability to optimize the tribological characteristics. The analysis of worn surfaces using scanning electron microscopy revealed adhesive and delamination wear as dominant mechanisms.

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Grey relational analysis for optimization of wear parameters and surface roughness on nano composite coating

Cited by 8 publications

References 41 publications

Optimization and Characterization of Centrifugal-Cast Functionally Graded Al-SiC Composite Using Response Surface Methodology and Grey Relational Analysis

Optimization and Characterization of Centrifugal-Cast Functionally Graded Al-SiC Composite Using Response Surface Methodology and Grey Relational Analysis

Optimization of Wear Parameters for Duplex-TiAlN Coated MDC-K Tool Steel Using Fuzzy MCDM Techniques

Multi-Objective Optimization of Tribological Characteristics for Aluminum Composite Using Taguchi Grey and TOPSIS Approaches

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