Surface roughness model and parametric optimization in machining of GFRP composite: Taguchi and Response surface methodology approach

Parida, A.K.; Routara, Bharat Chandra; Bhuyan, Rajesh Kumar

doi:10.1016/j.matpr.2015.07.247

Cited by 34 publications

(21 citation statements)

References 15 publications

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“…The RSM is a combination of statistical and mathematical procedures devoted to the development of mathematical models for analysis and optimization. It is applied to develop a relationship between the response factors and the significant parameters [24]. In this study, the RSM is devoted to the obtaining a regression equation describing the response parameters as a function of the independent process factors.…”

Section: Response Surface Methodologymentioning

confidence: 99%

Optimization of machining parameters in turning of Inconel 718 Nickel-base super alloy

Frifita

Salem

Haddad

et al. 2020

Mechanics & Industry

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The high hardness and low thermal diffusivity along with the tremendous strength at high temperatures has rendered the nickel-base super alloys Inconel 718 one of the most difficult to cut material. It possesses a wide range of applications including aerospace as well as chemical and petrochemical industries, and is primarily used in the manufacture of aircraft gas turbines, space vehicles, nuclear power systems, and medical equipment. The present study is mainly focused on the cutting parameters optimization that leads to minimum surface roughness, cutting force and power, specific energy and maximum productivity during the turning of the molded Inconel 718 using a carbide cutting tool. The analysis of variance (ANOVA) method is applied to identify the cutting parameters that most influence the response criteria, and the response surface methodology (RSM) along with the desirability function (DF) approaches are further used to develop the prediction model that addresses the optimization procedure. The different parameters are considered one at a time in order to evaluate the sensitivity of the response (OFAT). This procedure led to identify the nose radius (rε), the feed rate (f), the depth of cut (ap) and the cutting speed (Vc) as the most significant factors on both the surface roughness and the cutting forces. Furthermore, the product (f × ap) and the cutting speed (Vc) were found to be the most dominant factors on the specific energy.

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Section: Response Surface Methodologymentioning

confidence: 99%

Optimization of machining parameters in turning of Inconel 718 Nickel-base super alloy

Frifita

Salem

Haddad

et al. 2020

Mechanics & Industry

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“…Parida et al made a study about optimization of surface roughness in machining GFRP composite. They planned experiments according to L27 orthogonal array and found optimum levels of parameters by Taguchi method [6]. Tosun et al studied the effect of cutting tool, spindle speed and feed rate on surface roughness of AA7075-T6 in milling process.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Surface Roughness of Cutting Parameters in T6 Aluminum Alloy Milling Process

Özsoy

2019

International Journal of Computational and Experimental Science and Engineering

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In this study, optimum machining conditions were determined by investigating the surface roughness of the 7075-T6 aluminum alloy milling, depending on the spindle speed (rpm), feed per tooth (Fz-mm/tooth) and the cooling type parameters. Taguchi experiment design method was used to save time and cost. Experiments were based on the Taguchi L16 orthogonal array and signal/noise (S/N) ratios were used in the evaluation of the test results. Optimum surface roughness values were determined with Taguchi optimization. In addition, variance analysis and regression analysis were performed. Confirmation tests were conducted to verify the work. As a result of the confirmation tests, it was found that the surface roughness optimization in the milling of the 7075-T6 aluminium alloy was successfully applied.

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“…The finite element (FE) simulation, the Taguchi technique, and the analysis of variance (ANOVA) techniques were carried out by Thipprakmas to investigate the degree of importance of V-ring indenter parameters 12 . A. K. Parida et al applied response surface methodology (RSM) to determine the optimum machining conditions leading to minimum surface roughness in drilling of GFRP composite 13 . The experimental plan and analysis is based on the Taguchi L 27 orthogonal array taking spindle speed (N), feed (f) and diameter of drill bit (d) as important parameters.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Curing Cycle Optimization for Glass Fabric/Epoxy Composites Using Poisson Regression and Genetic Algorithm

et al. 2018

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In this study, a multi-parameter design of experiments, using Taguchi method, has been conducted in order to investigate the optimum curing conditions for glass fabric/epoxy laminated composites, followed by a statistical analysis and genetic algorithm optimization. Heating rate a, temperature T 1 and duration h 1 were treated as independent variables in a L 25 Taguchi orthogonal array addressing five levels each. Tensile load and flexural strength were examined as pre-selected quality objectives. The results of the analysis of variance performed showed that the significant parameters for both tensile and flexural strength were temperature and duration, at a 95% confidence level. The estimation of the curing parameters for optimum tensile and flexural performance was achieved with an error considerably lower than 1%. The Poisson regression analysis was introduced to achieve a highly accurate regression model, with R 2 greater than 97% for both optimization criteria. Finally, these two regression models were converted into a two-fold function for maximizing both criteria, and used as fitness function for a multi-objective optimization genetic algorithm.

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Surface roughness model and parametric optimization in machining of GFRP composite: Taguchi and Response surface methodology approach

Cited by 34 publications

References 15 publications

Optimization of machining parameters in turning of Inconel 718 Nickel-base super alloy

Optimization of machining parameters in turning of Inconel 718 Nickel-base super alloy

Experimental Investigation of Surface Roughness of Cutting Parameters in T6 Aluminum Alloy Milling Process

Multi-Objective Curing Cycle Optimization for Glass Fabric/Epoxy Composites Using Poisson Regression and Genetic Algorithm

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