Multi-response optimization for machining GFRP composites using GRA and DFA

Natural fiber is a hairy like raw material which comes from natural sources such as animal, plant, and mineral fibers. Kenaf fiber known with scientific name as Hibiscus Cannabinus is one natural fibers which becoming popular as a reinforced for plastic composites material in the industrial application such as automobile, aircraft, and marine engineering. However, milling these materials present a few problems, which are surface roughness and delamination factors are appear during the machining process, associated with the characteristics of the material and the cutting parameter. The objective of evaluating the cutting parameters (spindle speed, feed rate, and depth of cut), the influence of the fibers under surface roughness (Ra) and delamination factor (Fd). In this research study, Response Surface Methodology (RSM) was used to conduct the experiment. In addition, this method established considering milling with prefixed cutting parameters using HSS end mill. The experiment result was analyzed using Design Expert software. It was found that the optimum parameters for the minimum surface roughness and delamination were spindle speed at 2000 rpm, feed rate at 300 mm/min, and depth of cut at 2.0 mm. The spindle speed and feed rate are the main factors influence the effect of surface roughness and delamination in kenaf fiber reinforced plastic. High spindle speed and low feed rate resulted in minimum surface roughness and delamination.KeywordsCompositeMillingSurface roughnessDelaminationRSM

Input parameter like the cutting fluid is one of the requirements for minimal surface roughness, cutting temperature, tool wear and optimal material removal rate coupled with improved machinability and productivity. The evaluation of the optimal factors of surface roughness, material removal rate, cutting temperature and tool wear in the turning of AISI Mild Steel with the use of eco-friendly fluids. Concerns has been raise globally about the non - biodegradability and non-recyclability of the conventional fluids in the research space. This prompted the research interest in replacing the mineral oil based fluids with eco-friendly cutting fluid such as castor seed oil based cutting fluid (CBCF). The locally sourced castor seed oil was investigated for its physiochemical properties as well as its fatty acid composition (FAC). The cutting fluid was formulated using ratio 1:9 of oil with additives to distilled water and then characterized. In turning of AISI 1020 Mild Steel, the evaluation of surface roughness, material removal rate, cutting temperature and tool wear under the CBCF compared to the mineral oil based cutting fluid (MBCF) were carried out using Taguchi experimental design and Grey Relational Analysis (GRA) for multi-response optimization. The formulated cutting fluid showed pH value of 8.47, viscosity of 0.830 mm2/s, good resistance to corrosion, good stability and milkfish in colour. From the GRA, the multi-response optimal factor combination under the CBCF is (1250 rev/min) spindle speed, (0.6 mm/rev) feed rate and (1.0 mm) depth of cut, all at level 3 while under the MBCF, it also shows (1250 rev/min) spindle speed, (0.6 mm/rev) feed rate and (1.0 mm) depth of cut all at level 3. The parameters from Taguchi and GRA results are in agreement with results from other vegetable oil based fluids and this study also contributes and improves the science of machining.

Due to the anisotropy carbon fibre reinforced polymer (CFRP) materials, problems such as poor surface quality of the hole wall and delamination often occur in the traditional hole-making process. In this study, the Taguchi method was used to design a CFRP spiral-milling experiment using uncoated and diamond-coated carbide cutters. The analysis of variance and signal-to-noise ratio analysis were used to study the influence of process parameters on the surface roughness and delamination factors. Prediction models for surface roughness and delamination factors were established using improved particle-swarm neural network. The results showed that the diamond-coated milling cutters are more suitable for CFRP processing. The order of importance of the process parameters is as follows: axial-feed speed > horizontal-feed speed > spindle speed > revolution radius. The prediction model for the surface roughness and delamination factors developed in this study achieves high accuracy.

Prediction of drilling induced delamination and circularity deviation in GFRP nanocomposites using deep neural network

The paper focuses on the cutting behavior of Glass Fiber Reinforced Polymer (GFRP) composites and GNP–GFRP composites that contain varying amounts of Graphene Nano Platelets (GNP). GFRP composites are increasingly being used in a variety of industrial applications due to their excellent mechanical properties, such as high strength, stiffness, and low weight. However, their machining and cutting behavior can be challenging due to the presence of the reinforcing fibers. Therefore, the study aims to investigate the machining behavior of GFRP composites and the effect of adding GNP on their cutting behavior. The effect of different parameters such as cutting speed, feed rate and reinforcement rate on cutting forces and delamination factor is investigated. In addition, the tensile strength and fatigue behavior of the composite materials with the best and worst delamination factors were also determined. Addition of up to 0.2 wt.% of GNP to GFRP composites resulted in an increase in cutting forces and delamination factor when drilling GFRP composites. While the cutting force and delamination factor decreased with the increase in cutting speed, the cutting force and delamination factor increased with the increase in the feed rate. Analysis of variance (ANOVA) was performed to determine the effects of drilling parameters and reinforcement ratio on cutting force and delamination factor according to full factorial experimental design. The most efficient factor on the cutting forces is found to be feed rate (84.97%), followed by the reinforced rate (6.48%) and cutting speed (6.13%). The most efficient factor on the delamination factor is determined to be feed rate for (44.49%), followed by the reinforced rate (29.20%) and cutting speed (21.73%).

Terahertz wave (T-ray) scanning applications are one of the most promising tools for nondestructive evaluation. T-ray scanning applications use a T-ray technique to measure the thickness of both thin Shim stock films and GFRP (glass fiber-reinforced plastics) composites, of which the samples were selected because the T-ray method could penetrate the non-conducting samples. Notably, this method is nondestructive, making it useful for analyzing the characteristics of the materials. Thus, the T-ray thickness measurement can be found for both non-conducting Shim stock films and GFRP composites. In this work, a characterization procedure was conducted to analyze electromagnetic properties, such as the refractive index. The obtained estimates of the properties are in good agreement with the known data for poly methyl methacrylate (PMMA) for acquiring the refractive index. The T-ray technique was developed to measure the thickness of the thin Shim stock films and the GFRP composites. Our tests obtained good results on the thickness of the standard film samples, with the different thicknesses ranging from around 120 μm to 500 μm. In this study, the T-ray method was based on the reflection mode measurement, and the time-of-flight (TOF) and resonance frequencies were utilized to acquire the thickness measurements of the films and GFRP composites. The results showed that the thickness of the samples of frequency matched those obtained directly by time-of-flight (TOF) methods.

Optimization of Drilling Characteristics using Grey Relational Analysis (GRA) in Medium Density Fiber Board (MDF)

In this study, custom-fabricated multiwalled carbon nanotube (MWCNT)-reinforced and unreinforced glass fiber-reinforced polymer (GFRP) composites were used. These composites were manufactured via the vacuum-assisted resin transfer molding technique to ensure high-quality, consistent material properties. The study investigates the effects of MWCNT reinforcement ratios, cutting speeds, and feed rates on the drilling performance of GFRP composites. Key processing indicators such as surface roughness (SR), delamination, and thrust force were evaluated. A full factorial design comprising 27 experimental runs was employed. Variance analysis (ANOVA) and the Taguchi method were used for single-response optimization, revealing that the MWCNT reinforcement ratio had the greatest effect on delamination, while feed rate predominantly influenced thrust force. Cutting speed and feed rate were both found to significantly affect SR. For multiobjective optimization, the Criteria Importance Through Intercriteria Correlation-based weighting method was integrated with the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approach. The optimal parameters identified through this methodology were further refined using Taguchi signal-to-noise ratio analysis. According to the VIKOR analysis, feed rate emerged as the most influential factor, with a contribution ratio of 28.48%. The optimal drilling parameters correspond to Experiment No. 10, which involved a 0.5% MWCNT reinforcement ratio, a cutting speed of 25 m/min and a feed rate of 0.10 mm/rev (A 2 B 1 C 1 ). Under these conditions, the delamination factor (D₀) was 1.234, thrust force (F) was 82.03 N, and SR (Ra) was 1.575 µm. This integrated methodology provides a robust framework for optimizing drilling parameters in nanocomposite materials.

Study and analysis of drilling parameters using TLBO algorithm on GFRP composites

Composites are now being used to replace traditional metallic structures in a variety of industries that including aerospace, aircraft, and military, that demand structural materials of high stiffness-to-weight and strength-to-weight ratios. This work is aimed at investigation on drilling process parameters of a hybrid composite. A hybrid composite is prepared with Epoxy as matrix with Jute and Glass fibre reinforced material. It is attempted to investigate the delamination tendency of hybrid composite along with optimization of drilling parameters. The two parameters considered are speed and feed rate. Each of this is considered at 3 levels. Response characteristics are thrust force, torque, delamination factor. L9 orthogonal array will be considered for experimentation. Standard Analysis is performed to discriminate significant and insignificant factors. Optimized process parameters are obtained for each of response characteristics. The objective is to optimize drilling process parameters of a hybrid compositeTaguchi’s L9 3-level orthogonal array was employed in this work. Entropy weighted multivariate loss function optimizes the multi-responses with a single desired response for drilled hybrid composites at the common factor level. Spindle speed and feed rate operate as control elements, the responses are dependent on torque, thrust force, and delamination. Medium spindle speeds with smaller feed rates enhance drilling success, according to the findings. The results also showed that spindle speed has a higher influence on the quality of holes drilled.

Modern engineering materials have seen remarkable development. Because conventional materials can no longer meet the needs of modern applications, numerous composites are being employed as viable alternatives. Drilling is the most important production step for most uses, and the resulting holes are high-stress zones that must be handled carefully. Scientists and engineers have long been interested in the challenge of finding the best combination of drilling settings for cutting-edge composite materials. As part of this research, AA2017/AlN composites with matrices made of AA2017 aluminium alloy and reinforcements made of 5, 10, and 15 wt % AlN were produced using stir casting. By experimenting with different input parameters, we were able to utilise the L9 OA to determine the best machining arrangement for drilling materials. The investigation focused on critical drilling characteristics, including burr height (H), thrust force (T), and surface roughness (SR), with a keen emphasis on sustainability.By considering the burr height (H), thrust force (T) and surface roughness (SR) and this work used grey relational analysis (GRA) to establish the optimum cutting parameters for drilling holes in the cutting-edge composite AA2017/AlN. The significance of different machining settings and their effect on the typical characteristics of the drilling were analysed using GRA. However, a confirmation experiment was conducted to ensure the highest quality outcomes. Test results and GRA indicate that the best grey relational grade is achieved with the following parameters: spindle speed (S) of 3500 rpm, feed rate (F) of 60 m/s, drill material (D) of Tungsten Carbide, and reinforcement (R) of 10%.. Analysis of variance (ANOVA) revealed statistically significant impacts on GRG from the drill material (29.08%), the feed rate (24.24%), and the spindle speed (19.52%). The error term was a function of the reinforcement percent and its interactions with all other parameters; however, the influence of the interaction between feed rate and drill material on GRG was small. The GRG is 0.856, which is higher than the prediction of 0.824. The calculated and measured values agree quite well and 3.7% is a negligible margin of error. The mathematical models for all reactions depending on the drill bits employed was also constructed.

Optimization of pyramid shaped single point incremental forming of AA5052 alloy sheet

In this work, the research efforts have been made to investigate the effect of important drilling parameters such as spindle speed and feed rate on effectiveness of process and quality of holes during drilling of difficult-to-machine Al/SiC metal matrix composite using diamond-coated cemented carbide tool. Thrust force, hole diameter, delamination factor, surface roughness, tool wear, and chip analysis of the drilled holes were investigated at different spindle speeds (3000–9000 rpm) as well as feed rates (0.05–0.2 mm/rev), respectively. The outcomes of this study reveal that thrust force varies directly with the feed rate, but inversely with the spindle speed. Both the hole diameter and the delamination factor shows a rough proportionality with the feed rate, although the rates of variation are slow at the high spindle speed combined with a high feed rate. Similarly, the hole surface roughness increases with the feed rate, while the moderate spindle speeds produce better surface roughness. Smaller chips were found for all spindle speed. Adhesive and abrasive wear mechanisms are prominent on drill bit and drill wear occurs on both drill tip and secondary cutting edge. Drilling at moderate spindle speeds of 5000 rpm and 7000 rpm is the most suitable for the hole drilling in the Al/SiC metal matrix composites.

Due to excellent properties such as high specific strength, high specific modulus, and corrosion resistance, Glass Fiber Reinforced Plastics (GFRP) find wide applications particularly in the aerospace and automotive industries. In order to fabricate structural components of GFRP to near-nett shape, machining of GFRP composites is necessary. Drilling is the most common machining operation for GFRP composites. The fiber pull-out, cracking of matrix during the entry and exit of drill, rapid tool wear, and hole shrinkage are problems associated with machining of GFRP. The present study attempts an innovative idea of improving the cutting performance of Tungsten carbide (WC) inserts (K-20) by post-sintering using microwave irradiation.

The selection of the optimal tool path strategy and appropriate cutting conditions, especially in the machining aspects of free form surfaces are important to achieve higher productivity. In this work, optimal tool path selection for machining concave surfaces is carried out to achieve minimum surface roughness (Ra), cutting forces and machining time in ball-end milling of aluminium alloy 6061 (Al 6061). Various tool path strategies including 3D offset, raster, concentric, radial zig-zag, zig, and concentric zig-zag are employed. The cutting parameters considered were feed rate, spindle speed and step over. Design of experiments (DoE) along with the statistical analysis of variance (ANOVA) and mean plots are used to determine the significant parameters and their levels for each tool path strategy. Conflicting results were obtained from the ANOVA and the mean plot analyses, to achieve optimum levels that led to lower surface roughness, cutting forces and machining time. It is observed that lower values of surface roughness and cutting forces are obtained with the low level of feed rate and step over in all six tool path strategies. However, high feed rate and step over the lead to decreased machining time. Hence, grey relational analysis is carried out considering multiple performance characteristics such as minimum surface roughness, cutting forces and machining time, and optimal combinations of the milling process parameters for each tool path strategies are identified.KeywordsBall-end millingTool path strategyAluminium alloy 6061Surface roughnessCutting forcesMachining timeGrey relation analysis