ANOVA and Response Surface Methodology for the Optimization of Fracture Toughness parameters on Jute Fabric-Epoxy composites using SENB specimens

Manjunatha, G.; Bharath, K. N.; Ganesh, D.B.; Kumar, Dharmesh; Shivprakash, P.; Harsha, H.M.

doi:10.1016/j.matpr.2017.09.052

Cited by 9 publications

(9 citation statements)

References 11 publications

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“…RSM is applied in many fields such as biology, chemistry, and engineering sciences to optimize the process parameters, [15][16][17] and some studies have incorporated RSM to explore the mechanical properties of polymer matrices. [18][19][20] Based on the literature, no systematic study has been conducted on A-short glass fiber/ epoxy composites. Furthermore, the simultaneous effect of different variables on the mechanical properties of epoxy-based composite materials is not yet well developed.…”

Section: Introductionmentioning

confidence: 99%

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Morphology, mechanical behavior, and prediction of A-glass/SiO₂/epoxy nanocomposite using response surface methodology

Saberian

Ghasemi

et al. 2018

Journal of Elastomers & Plastics

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Response surface methodology (RSM) is used to study the mechanical and morphological properties of glass fiber (GF)/epoxy composites. The Box–Behnken method was used to design the experiments and quantify the effects of GF content, glass fiber length (GFL), and silica nanoparticles (SiO2). Each variable consisted of three levels: GF (5, 10, and 15 wt%), GFL (3, 6, and 9 mm), and SiO2 (0, 0.75, and 1.5 wt%). Tensile tests were performed to obtain the tensile strength and elongation at break of the samples, and morphology properties were studied by a scanning electron microscope (SEM). The results showed that at high levels of GF, the tensile strength, and elongation at break decreased up to 42% and 30%, respectively. Although increasing the GFL from 6 mm to 9 mm deceased tensile strength by 13%, the elongation at break increased by 7%. The presence of SiO2 at medium level in the composites decreased the elongation but enhanced the tensile strength by 10%. In addition, RSM was employed to develop the mathematical model between process variables. The developed models were validated by the analysis of variance. The R2 obtained from analysis of variance results and normal probability plots showed that the experimental data had a good agreement with those predicted by the models (above 0.95 for all responses).

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Section: Introductionmentioning

confidence: 99%

“…RSM is applied in many fields such as biology, chemistry, and engineering sciences to optimize the process parameters, 15 –17 and some studies have incorporated RSM to explore the mechanical properties of polymer matrices. 18 –20…”

Section: Introductionmentioning

confidence: 99%

Morphology, mechanical behavior, and prediction of A-glass/SiO₂/epoxy nanocomposite using response surface methodology

Saberian

Ghasemi

et al. 2018

Journal of Elastomers & Plastics

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“…The K IC of the cured specimen was calculated as follows: KIC=Pmaxbd1/2ffalse(xfalse) x = a / d where P max , d, b, f(x), and a are the critical load for crack propagation, width of the specimen, thickness of the specimen, geometrical factor given by Equation (2), and pre-crack length, respectively [40]. ffalse(xfalse)=6x1/2false[1.99−xfalse(1−xfalse)false(2.15−3.93x+2.7x2false)false]2false(1+2xfalse)1−x3/2…”

Section: Methodsmentioning

confidence: 99%

Thermal and Mechanical Interfacial Behaviors of Graphene Oxide-Reinforced Epoxy Composites Cured by Thermal Latent Catalyst

Riaz

Park

2019

Materials

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A series of composites was prepared from a diglycidyl ether of bisphenol A (DGEBA) with different graphene filler contents to improve their mechanical performance and thermal stability. Graphene oxide (GO) and GO modified with hexamethylene tetraamine (HMTA) were selected as reinforcing agents. As a latent cationic initiator and curing agent, N-benzylepyrizinium hexafluoroantimonate (N-BPH) was used. The effect of fillers and their contents on the mechanical properties and thermal stability of the composites were studied. Fracture toughness improved by 23% and 40%, and fracture energy was enhanced by 1.94- and 2.27-fold, for the composites containing 0.04 wt.% GO and HMTA-GO, respectively. The gradual increase in fracture toughness at higher filler contents was attributed to both crack deflection and pinning mechanisms. Maximum thermal stability in the composites was achieved by using up to 0.1 wt.% graphene fillers.

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“…Taguchi technique is created to Genichi Taguchi. The framework assumes a statistical nature as it strives to lessen changes in the bottling process in an idea called the design of experiments (Manjunath et al, 2017). While pursuing the use of the Taguchi method in this work, the driving force was to attain the utmost safety conformity outcome with reduced experiments (Manjunath et al, 2017).…”

Section: Etp Techniciansmentioning

confidence: 99%

A Hybrid Control Chart-Taguchi Method for Control and Optimization of Safety Conformity

Martins

Oke

2020

IJIEEM

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In this paper, a hybrid control chart-Taguchi method (CCTM) is proposed to solve the control and optimization problem regarding safety conformity parameters for a bottling process plant (BPP). The CCTM fuses the conservative control charts, which monitor the safety conformity parameters to promote and maintain the uppermost grade of employees’ physical, social and mental well-being. The control chart result is placed in the Taguchi methodical phase of factor-level determination to cultivate an orthogonal array. Then, the inventive rational ability of the control chart is used to correct the process and hence, enhances the Taguchi method. Consequently, the CCTM can be intensely robust and statistically precise. The proposed CCTM was successfully used to solve the safety conformity problem involving the control and parametric optimization in a bottling process plant. The field data uncovers the ability of the proposed CCTM to control and optimize the bottling process plant parameters. Moreover, it showcases the results as better than an enormously stronger than the conventional Taguchi method.

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ANOVA and Response Surface Methodology for the Optimization of Fracture Toughness parameters on Jute Fabric-Epoxy composites using SENB specimens

Cited by 9 publications

References 11 publications

Morphology, mechanical behavior, and prediction of A-glass/SiO₂/epoxy nanocomposite using response surface methodology

Morphology, mechanical behavior, and prediction of A-glass/SiO₂/epoxy nanocomposite using response surface methodology

Thermal and Mechanical Interfacial Behaviors of Graphene Oxide-Reinforced Epoxy Composites Cured by Thermal Latent Catalyst

A Hybrid Control Chart-Taguchi Method for Control and Optimization of Safety Conformity

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ANOVA and Response Surface Methodology for the Optimization of Fracture Toughness parameters on Jute Fabric-Epoxy composites using SENB specimens

Cited by 9 publications

References 11 publications

Morphology, mechanical behavior, and prediction of A-glass/SiO2/epoxy nanocomposite using response surface methodology

Morphology, mechanical behavior, and prediction of A-glass/SiO2/epoxy nanocomposite using response surface methodology

Thermal and Mechanical Interfacial Behaviors of Graphene Oxide-Reinforced Epoxy Composites Cured by Thermal Latent Catalyst

A Hybrid Control Chart-Taguchi Method for Control and Optimization of Safety Conformity

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Morphology, mechanical behavior, and prediction of A-glass/SiO₂/epoxy nanocomposite using response surface methodology

Morphology, mechanical behavior, and prediction of A-glass/SiO₂/epoxy nanocomposite using response surface methodology