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The purpose of this paper is to optimise the process parameters, namely, fibre orientation angle, helix angle, spindle speed, and feed rate in milling of glass fibre-reinforced plastic (GFRP) composites using grey relational analysis (GRA) and desirability function analysis (DFA).

In this work, experiments were carried out as per the Taguchi experimental design and an L27 orthogonal array was used to study the influence of various combinations of process parameters on surface roughness and delamination factor. As a dynamic approach, the multiple response optimisation was carried out using GRA and DFA for simultaneous evaluation. These two methods are best suited for multiple criteria evaluation and are also not much complicated.

The process parameters were found optimum at a fibre orientation angle of 15°, helix angle of 25°, spindle speed of 6,000 rpm, and a feed rate of 0.04 mm/rev. Analysis of variance was employed to classify the significant parameters affecting the responses. The results indicate that the fibre orientation angle is the most significant parameter preceded by helix angle, feed rate, and spindle speed for GFRP composites.

An attempt to optimise surface roughness and delamination factor together by combined approach of GRA and DFA has not been previously done.

In milling process the surface roughness and delamination are the most important performance characteristics, which are influenced by many factors like fibre orientation angle, helix angle, feed rate and spindle speed. The selection of these parameters at optimum level plays a vital role in getting minimum surface roughness and delamination factor. The purpose of this paper is to present multi-objective optimisation of Computer Numerical Control milling parameters using Grey-Taguchi method to get minimum surface roughness and delamination factor in machining of glass fibre reinforced plastics (GFRP) composites used in automotive, aircraft and manufacture of space ships.

The experiments are designed and conducted based on Taguchi's L₂₇ orthogonal array by taking fibre orientation angle, helix angle, feed rate and spindle speed at three levels and responses are surface roughness and delamination factor. Taguchi's signal-to-noise (S/N) ratio are determined based on their performance characteristics. A Grey relation grade is obtained by using S/N ratio. Based on Grey relational grade value, optimum levels of parameters have been identified by using response table and response graph.

Optimum levels of parameters for GFRP composites have been identified by using response table and response graph and the significant contributions of controlling parameters are estimated using analysis of variance.

The combined effect of fibre orientation angle and helix angle during milling of GFRP composites using Grey relational analysis has not been previously attempted for analysis.

The purpose of this paper is to develop a mathematical model for surface roughness and delamination through response surface methodology (RSM) and analyse the influences of the entire individual input machining parameters (cutting speed, fibre orientation angle, depth of cut and feed rate) on the responses in milling of glass fibre reinforced plastics (GFRP) composites with solid carbide end mill cutter coated with PCD.

Four factors, five level central composites and a rotatable design matrix in response surface methodology were employed to carry out the experimental investigation. “Design Expert 8.0” software was used for regression and graphical analysis of the data were collected. The optimum values of the selected variables were obtained by solving the regression equation and by analyzing the response surface contour plots. Analysis of variance (ANOVA) was applied to check the validity of the model and for finding the significant parameters.

The developed second order response surface model was used to calculate the surface roughness and delamination of the machined surfaces at different cutting conditions with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.

The effect of fibre orientation during milling of GFRP laminates using RSM has not been previously attempted for analysis.

Glass fibre reinforced plastics (GFRP) contain two phases of materials with drastically distinguished mechanical and thermal properties, which brings in complicated interactions between the matrix and the reinforcement during machining. Surface quality and dimensional precision will greatly affect parts during their useful life especially in cases where the components will be in contact with other elements or materials during their useful life. The purpose of this paper is to discuss the application of the Taguchi method with fuzzy logic to optimise the machining parameters for machining of GFRP composites with multiple characteristics.

The machining tests were performed on a CNC milling machine using solid carbide (K10) End mill cutting tool with three different helix angles. Experiments were planned using Taguchi’s orthogonal array with the cutting conditions prefixed.

The machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate, depth of cut, and work piece fibre orientation (specially applied to the GFRP composites) were optimised with considerations of multiple response characteristics, including machining force, material removal rate, and delamination. The results from confirmation runs indicated that the determined optimal combination of machining parameters improved the performance of the machining process.

Multi-response optimisation of machinability behaviour of GFRP composites using fuzzy logic has not been attempted previously.

This paper aims to investigate the effect and parametric optimization of process parameters during milling of glass fibre-reinforced plastics (GFRP) composites using grey relational analysis (GRA).

Experiments are conducted using helix angle, spindle speed, feed rate, depth of cut and fibre orientation angle as typical process parameters. GRA is adopted to obtain grey relational grade for the milling process with multiple characteristics, namely, machining force and material removal rate (MRR). Analysis of variance is performed to get the contribution of each parameter on the performance characteristics.

It is observed that helix angle and fibre orientation angle are the most significant process parameters that affect the milling of GFRP composites. The experimental results reveal that the helix angle of 45°, spindle speed of 3000 rpm, feed rate of 1000 mm/min, depth of cut of 2 mm and fibre orientation angle of 15° is the optimum combination of lower machining force and higher MRR. The experimental results for the optimal setting show that there is considerable improvement in the process.

Optimization of process parameters on machining force and MRR during endmilling of GFRP composites using GRA has not been attempted previously.

This paper aims to study the comparison between a response surface methodology (RSM) and artificial neural network (ANN) in the modelling and prediction of surface roughness during endmilling of glass-fibre-reinforced polymer composites.

Aiming to achieve this goal, several milling experiments were performed with polycrystalline diamond inserts at different machining parameters, namely, feed rate, cutting speed, depth of cut and fibre orientation angle. Mathematical model is created using central composite face-centred second-order in RSM and the adequacy of the model was verified using analysis of variance. ANN model is created using the back propagation algorithm.

With regard to the machining test, it was observed that feed rate is the dominant parameter that affects the surface roughness, followed by the fibre orientation. The comparison results show that models provide accurate prediction of surface roughness in which ANN performs better than RSM.

The data predicted from ANN are very nearer to experimental results compared to RSM; therefore, this ANN model can be used to determine the surface roughness for various fibre-reinforced polymer composites and also for various machining parameters.

The fiber reinforced polymer composites are becoming more critical because of their exceptional mechanical properties and lightweight structures. Fused filament fabrication (FFF) is a three-dimensional (3D) printing technique that can manufacture composite structures. However, the effect of impact performance on the structural integrity of FFF made composites compared to the pre-preg composites is a primary concern for the practical usage of 3D printed parts. Therefore, this paper aims to investigate the effect of different processing parameters on the impact performance of 3D printed composites.

This paper investigates the impact of build orientation, fiber stacking sequence and fiber angle on the impact properties. Two build orientations, three fiber stacking sequences and two different fiber angles have been selected for this study. Charpy impact testing is carried out to investigate the impact energy absorption of the parts. Onyx as a matrix material and two different types of fibers, that is, fiberglass and high strength high temperature (HSHT) fiberglass as reinforcements, are used for the fabrication.

Results indicate that build orientation and fiber angle largely affect the impact performance of composite parts. The composite part built with XYZ orientation, 0º/90º fiber angle and B type fiber stacking sequence resulted into maximum impact energy. However, comparing both types of fiber reinforcement, HSHT fiberglass resulted in higher impact energy than regular fiberglass.

This study evaluates the damage modes during the impact testing of the 3D printed composite parts. The impact energy absorbed by the composite samples during the impact testing is measured to compare the effect of different processing conditions. The investigation of different types of fiberglass reinforced with Onyx material is very limited for the FFF-based process. The results also provide a database to select the different parameters to obtain the required impact properties.

The paper aims to develop a mathematical model for delamination and surface roughness during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut, helix angle and feed rate) influence the output response (delamination and surface roughness) in machining of hybrid glass fibre reinforced plastic (GFRP; Abaca and Glass) composite using solid carbide end mill cutter.

Four-factor, three-level Taguchi orthogonal array design in RSM is used to carry out the experimental investigation. The “Design Expert 8.0” is used to analyse the data collected graphically. Analysis of variance is carried out to validate the model and for determining the most significant parameter.

The feed rate is the cutting parameter which has greater influence on delamination (88.39 per cent), and cutting speed is the cutting parameter which has greater influence on surface roughness (53.42 per cent) for hybrid GFRP composite materials. Both surface roughness and delamination increase as feed rate increases, which means that the composite damage is larger for higher feed rates.

Effect of milling of hybrid GFRP composite on delamination and surface roughness with various helix angles of solid carbide end mill has not been analysed yet using RSM.

The purpose of this paper is to originate a statistical model for delamination factor, surface roughness, machining force and also to determine and compare the effects of machining parameters (spindle speed, fiber orientation angle, helix angle and feed rate) on the output responses during end-milling of glass fiber reinforced polymers (GFRP) by using desirability functional analysis (DFA) and grey relational analysis (GRA).

Based on Taguchi’s L27 orthogonal array, milling experiments were carried on GFRP composite plates employing solid carbide end mills with different helix angles. The machining parameters were optimized by an approach based on DFA and GRA, which were useful tools for optimizing multi-response considerations, namely, machining force, surface roughness and delamination factor. A composite desirability index was obtained for multi-responses using individual desirability values from DFA. Based on this index and grey relational grade the optimum levels of parameters were identified and significant contribution of parameters was ascertained by analysis of variance.

Fiber orientation angle (66.75 percent) was the significant parameter preceded by feed rate (15.05 percent), helix angle (7.76 percent) and spindle speed (0.30 percent) for GFRP composite plates.

Multi-objective optimization in end-milling of GFRP composites using DFA and GRA has not been performed yet.

The determination of stress intensity factors (SIF) is of fundamental importance in prediction of brittle failure using linear elastic fracture mechanics. The presence of a crack in the vicinity of another crack induces an interaction effect. The purpose of this paper is to determine the SIF for an orthotropic lamina subjected to uniaxial loading and containing two cracks. The solution is obtained for one crack being horizontal and located in the centre of lamina while the other crack is inclined to first one. The effect of angle of the second crack, fibre angle is studied. Also, for the case of two parallel cracks, effect of eccentricity in x and y directions is observed.

Boundary collocation method is used and stress functions satisfying governing equations in the domain and ensuring stress singularity at the crack tips are defined. The boundary condition on the edges of lamina and the crack is satisfied to determine the complex coefficients in the stress functions.

For the given fibre angle, orientations of second crack which result in increase/decrease in the SIF at the most dangerous crack tip are found out.

Boundary collocation method which is simple and efficient is extended for studying two crack problem in orthotropic materials.