Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

Parida, A.K.; Routara, Bharat Chandra

doi:10.1155/2014/905828

Cited by 30 publications

(13 citation statements)

References 16 publications

(16 reference statements)

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“…have been often used to solve MCDM problems with high accuracy. Authors in [13,14] used the TOPSIS method to solve the MCDM problem. These researches show that TOPSIS could be applied to find the best alternative easily and quickly.…”

Section: Introductionmentioning

confidence: 99%

Cutting Parameter Optimization in Finishing Milling of Ti-6Al-4V Titanium Alloy under MQL Condition using TOPSIS and ANOVA Analysis

Nguyen

Dung

2021

Eng. Technol. Appl. Sci. Res.

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Titanium and its alloys give immense specific strength, imparting properties such as corrosion and fracture resistance, making them the right candidate for medical and aerospace applications. There is a wide range of engineering applications that use titanium alloys in a variety of forms. The cost of these alloys is slightly higher in comparison to other variants due to the problematic extraction of the molten process. To reduce costs, titanium alloy products could be made by casting, isothermal forging, radial swaging, or powder metallurgy, although these techniques require some kind of finishing machining process. Titanium and its alloys are difficult to machine due to skinny chips leading to a small cutting tool-workpiece contact area. The thermal conductivity of titanium alloys is too low and the stress produced is too large due to the small contact area, which results in very high cutting temperatures. This paper deals with the experimental study of the influence of the Minimum Quantity Lubricant (MQL) environment in the milling of Ti-6Al-4V alloy considering the optimization of surface roughness and production rate. Taguchi-based TOPSIS and ANOVA were used to analyze the results. The experimental results show that MQL with vegetable oil is successfully applied in the milling of Ti-6Al-4V. The research confirms the suitability of TOPSIS in solving the Multiple Criteria Decision Making (MCDM) issue, by choosing the best alternative at Vc=120m/min, fz=0.065mm/tooth, and ap=0.2mm, where the surface roughness and material removal rate are 0.41µm and 44.1492cm3/min respectively. Besides, ANOVA can be used to predict the best parameters set in the milling process based on the regression model. The parameters predicted by ANOVA analysis do not coincide with any implemented parameters

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Section: Introductionmentioning

confidence: 99%

Cutting Parameter Optimization in Finishing Milling of Ti-6Al-4V Titanium Alloy under MQL Condition using TOPSIS and ANOVA Analysis

Nguyen

Dung

2021

Eng. Technol. Appl. Sci. Res.

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“…In _____________ 1 Faculty of Mechanical Engineering, Hanoi University of Industry, Vietnam * E-mail: doductrung@haui.edu.vn https://doi.org/10.36897/jme/142599 this study, the weights of the criteria were determined by the Standard deviation method (SDM) [7]. Selecting the cutting parameters to simultaneously ensure the minimum surface roughness and the maximum material removal rate (MRR), where the weights of the parameters have been chosen by the decision-maker [8]. Selecting the cutting parameters to simultaneously ensure that the two parameters of the minimum values of the surface roughness (Ra and Rz) and maximum value of MRR, where the weights of the criteria were determined by the entropy method [9].…”

Section: Introductionmentioning

confidence: 99%

Application of TOPSIS an PIV Methods for Multi - Criteria Decision Making in Hard Turning Process

Trung¹

2021

Journal of Machine Engineering

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In this study, TOPSIS and PIV methods were applied for multi-criteria decision making in hard turning process. Experiments have been conducted in accordance with an experimental matrix designed by the Taguchi method with a total of twenty-seven experiments. At each experiment, the values of coolant concentration, nose radius, coolant flow, cutting velocity, feed rate and depth of cut have been changed. Surface roughness, flank wear and roundness error have been selected as output criteria. The weights of criteria have been determined by three methods, inclusive of Equal weight, ROC weight and Entropy weight. The combination of multi-criteria decisionmaking methods with three weighting methods gives six ranking options of the experiments. The purpose of ranking the experiments is to find the experiment at which the three output parameters are ensured to have the minimum value simultaneously.

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“…DF and GR analysis are employed to observe the significant process parameters. Arun Kumar Parida et al [7] investigated the GFRP composite by turning method to analyze the responses, namely SR and MRR. Taguchi method designed the parameters and analyzed them with the TOPSIS technique for finding the optimal process parameters.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach for Predition of Machining Performances of Glass Fiber Reinforced Plastic (Epoxy) Composites

Raveendran

Alagarsamy

Chanakyan

et al. 2021

Preprint

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In recent years, Glass Fiber Reinforced Plastic (GFRP) composites are more potential materials for usage in various structural applications in aerospace and automobile industries, owing to its favorable properties, such as light weight, specific strength, high elastic modulus and excellent corrosion resistance. This paper presents a new hybrid approach for multi-objective optimization of machining parameters on GFRP composite using Taguchi coupled grey relational (GR) and desirability function (DF) approach. The end milling of GFRP composite was performed as per Taguchi’s L16 orthogonal array by considering three input parameters: viz. cutting speed (V), feed rate (F) and depth of cut (D), each at four levels. The material removal rate (MRR), surface roughness (SR) and tool wear (TW) were chosen as output responses. The main effect plot was used to determine the optimum level of machining parameters on the multiple responses. Moreover, analysis of variance (ANOVA) were applied to examine the significance of the parameters. Based on the ANOVA results, it was been proved that the depth of cut was the most remarkable parameter, trailed by feed rate and cutting speed, respectively. Finally, the confirmation tests exhibited that the DA approach was employed better in terms of determining the optimum level of machining parameters as compared to GR analysis.

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Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

Cited by 30 publications

References 16 publications

Cutting Parameter Optimization in Finishing Milling of Ti-6Al-4V Titanium Alloy under MQL Condition using TOPSIS and ANOVA Analysis

Cutting Parameter Optimization in Finishing Milling of Ti-6Al-4V Titanium Alloy under MQL Condition using TOPSIS and ANOVA Analysis

Application of TOPSIS an PIV Methods for Multi - Criteria Decision Making in Hard Turning Process

A Hybrid Approach for Predition of Machining Performances of Glass Fiber Reinforced Plastic (Epoxy) Composites

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