1,279 research outputs found
Multi-objective optimization in machining of GFRP and MMC composites: two case experimental research
Composite materials like GFRP and MMCs having more importance in various manufacturing industries mainly in aerospace and automotive industries and many engineering application, because of their unique mechanical properties as compare to the conventional material. Drilling is the most common machining process in manufacturing industries for assembly of components but drilling of composite may possesses many difficulties such as fiber pull out, delamination and circularity etc. which affects the quality of drilled hole. To overcome these difficulties the effect of machining parameters on different machining responses should be investigated for attaining high product quality as well as satisfactory machining process performance. Therefore, the main objective of this dissertation is to investigate the various machining performance characteristics with different machining condition in drilling of GFRP and MMCs composites by using various integrated multi objective optimization methodologies. In this presented thesis, Deng’s similarity method integrated with Taguchi, TOPSIS integrated with Taguchi method (in drilling of GFRP composite) and PCA-Grey method integrated with Taguchi, Grey-TOPSIS Integrated with Taguchi method (in drilling of MMCs), have been implemented for obtaining the optimal machining conditions
Tribological Properties of Polymer Composites Using Non Traditional Optimization Technique: a review
Specific wear rate of composite materials plays a significant role in industry. The processes to measure it are both time and cost consuming. It is essential to suggest a modeling method to predict and analyze the effectiveness of parameters of specific wear rate. Nowadays, computational methods such as Grey Relational Analysis (GRA), Artificial Neural Network (ANN), Fuzzy Inference System (FIS) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as applicable tools from modeling point of view. The objective of using ANN, ANFIS is also to apply this tool for systematic parameter studies in the optimum design of composite materials for specific applications. In the present review, various principles of the neural network approach for predicting certain properties of polymer composite materials are discussed. The aim of this review is to promote more consideration of using GRA, ANN and ANFIS in the field of polymer composite property prediction and design
Hybrid Taguchi-GRA-CRITIC Optimization Method for Multi-Response Optimization of Micro-EDM Drilling Process Parameters
In this study, an attempt is made to investigate how the operational parameters such as capacitance, voltage, feed rate, and rotating speed affect the material removal rate, tool wear, overcut, and taper angle for micro-EDM drilling of aluminium 6061 utilizing brass C360 electrode. A novel Taguchi-GRA-CRITIC hybrid optimization methodology is used to obtain the optimal combination of micro-EDM drilling process parameters. The experiment was designed using the Taguchi L18 orthogonal array, and responses were recorded for each experiment. Grey Relational Analysis (GRA) is applied to improve the multi-response of the planned experiment. The weighting values corresponding to various responses are determined using CRITIC (criterion importance through intercriteria correlation) analysis. The hybrid methodology determines the best combination of process parameters for different responses. ANOVA was used to discover the most critical parameters. Finally, confirmation experiments were conducted with optimal parameters to identify improvement in grey relational grade over the initial parameters. The study\u27s findings indicate that, compared to the initial process parameter setting, the grey relational grade (GRG) increased by 92.36% with the optimal parameter setting
Multi-Response Optimization in Drilling of MWCNTs Reinforced GFRP Using Grey Relational Analysis
The present work concentrates on the use of Grey Relational Analysis for optimizing the drilling parameters like weight percentage of multi-wall carbon-nanotube (MWCNTs), cutting speed and feed rate on the thrust force and the delamination factor in the drilling of GFRP composites. Full factorial design is utilized for the trial. Analysis of variance (ANOVA) is applied to determine the significance of drilling parameters on multi-response. Considering the multi-response optimization results, which are acquired from the largest Grey Relational Grade (GRG), it is determined that optimal parameters are 1 wt. % MWCNTs, cutting speed 25 m/min, and feed rate 0.10 mm/rev to minimize concurrently thrust force and delamination factor. It is provided that the percentage development in GRG with the multi-response optimization is 50.53%. It is clearly indicated that the quality characteristics are crucially developed using this approach in the drilling of GFRP. According to the results of ANOVA of the GRG, the crucial factor is feed rate. Validation experiment was confirmed by computing the confidence level within the interval width. Eventually, results of validation experiment with the optimum drilling conditions settings have indicated that the proposed model develops overall performance of drilling process
Mathematical Modeling for Radial Overcut on Electrical Discharge Machining of Incoloy 800 by Response Surface Methodology
AbstractIn the present study, Response surface methodology is applied for prediction of radial overcut in die sinking electrical discharge machining (EDM) process for Incoloy 800 superalloy with copper electrode. The current, pulse-ontime, pulse-off time and voltage are considered as input process parameters to study the ROC. The experiments were planned as per central composite design (CCD) method. After conducting 30 experiments, a mathematical model was developed to correlate the influences of these machining parameters and ROC. The significant coefficients were obtained by performing ANOVA at 5% level of significance. From the obtained results,It was found that current and voltage have significant effect on the radial overcut. The predicted results based on developed models are found to be in good agreement with the The predicted values match the experimental results reasonably well with the coefficient of determination 0.9699 for ROC
A review on conventional and nonconventional machining of SiC particle-reinforced aluminium matrix composites
AbstractAmong the various types of metal matrix composites, SiC particle-reinforced aluminum matrix composites (SiCp/Al) are finding increasing applications in many industrial fields such as aerospace, automotive, and electronics. However, SiCp/Al composites are considered as difficult-to-cut materials due to the hard ceramic reinforcement, which causes severe machinability degradation by increasing cutting tool wear, cutting force, etc. To improve the machinability of SiCp/Al composites, many techniques including conventional and nonconventional machining processes have been employed. The purpose of this study is to evaluate the machining performance of SiCp/Al composites using conventional machining, i.e., turning, milling, drilling, and grinding, and using nonconventional machining, namely electrical discharge machining (EDM), powder mixed EDM, wire EDM, electrochemical machining, and newly developed high-efficiency machining technologies, e.g., blasting erosion arc machining. This research not only presents an overview of the machining aspects of SiCp/Al composites using various processing technologies but also establishes optimization parameters as reference of industry applications
Multi-objective optimization of carbon/glass hybrid composites with newly developed resin (NDR) using gray relational analysis
Purpose: It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle, stacking sequence, different resins and thickness of composite laminates has been carried out. The focus of this research work is on the optimization of the design variables like stacking angle, stacking sequence, different resins and thickness of composite laminates which affect the mechanical properties of hybrid composites. For this purpose, the Taguchi technique and the method of gray relational analysis (GRA) are used to identify the optimum combination of design variables. In this case, the effect of the abovementioned design variables, particularly of the newly developed resin (NDR) on mechanical properties of hybrid composites has been investigated. Design/methodology/approach: The Taguchi method is used for design of experiments and with gray relational grade (GRG) approach, the optimization is done. Findings: From the experimental analysis and optimization study, it was seen that the NDR gives excellent bonding strength of fibers resulting in enhanced mechanical properties of hybrid composite laminates. With the GRA method, the initial setting (A3B2C4D2) was having GRG 0.866. It was increased by using a new optimum combination (A2B2C4D1) to 0.878. It means that there is an increment in the grade by 1.366%. Therefore, using the GRA approach of analysis, design variables have been successfully optimized to achieve enhanced mechanical properties of hybrid composite laminates. Originality/value: This is an original research work
Factor Selection in Drilling Unidirectional Carbon Fiber Reinforced Plastic Composite Plates with The HSS Drill Bit Using Analytic Hierarchy Process
The present state of competition within the plastic composite industry calls for efficiency to be competitive. However, in the drilling of carbon-fiber-reinforced plastic (CFRP) composites, the process engineer still lacks knowledge of the priority of parameters as parameters are chosen at random, and resources are deployed without justification on their importance and strength. Consequently, production crises and productivity losses persist. In this article, the analytic hierarchy process (AHP) method is deployed to evaluate the weights of criteria in a CFRP composite drilling operation. The establishment of the decision, alternatives, and criteria is accomplished, and pairwise comparisons are conducted to allow the computation of the importance weight of each criterion. The weight is then established. The proposed approach was illustrated with experimental data from the literature with a plastic drilling case. Six criteria were chosen as crucial in determining the drilling parameters of CFRP composites. The results reveal the following: thrust force (0.413), torque (0.253), eccentricity (0.151), surface roughness (0.115), delamination at entry (0.037) and delamination at exit (0.030). In a validation exercise to ascertain the consistency of the analysis, a consistent analysis was obtained. The novelty of the article is using the AHP approach on the drilling of CFRP composites. Practically, these results impact operator training, indicating that attention should be focused on thrust force control. The industrial applications of CFRP composites include the basic structures of automobiles, ships, and airplanes
Multi-Response Enhancement of Drilling Process Parameters for AM 60 Magnesium Alloy as per the Quality Characteristics utilizing Taguchi-Ranking Algorithm and ANOVA
: This investigation shows the improvement of Drilling
parameters on AM-60 Mg alloy made with the help of Gravity Die
Casting and with reactions upheld symmetrical cluster with Grey
relational analysis - GRA. Which Focuses on the streamlining of
Drilling constraints utilizing the system to get least surface
Roughness (Ra), Tool Wear, Cutting Time, Power Requirement
and Torque and Max MRR. Concentrates on the optimization of
drilling constraints utilizing the procedure to get minimum
surface roughness (Ra), Thrust Force, Burr size and Circularity
Error. An amount of drilling experiments remained conducted
mistreatment the L9 OA on CNC Machining Center. The trails
remained achieved on Mg alloy block cutting tool of an ISO
460.1-1140-034A0-XM GC3 of 12 mm diameter with Tool Angle
140 degrees, used throughout the experimental work beneath dry
cutting conditions. This experimental study results like Ra, TF,
CE, and BZ were analyzed. GRA & ANOVA was utilized to effort
out the principal essential Spindle speed, feed rate, Titanium
Coated for Drill Bits (TiN, TiAN, TiCN) with 0.020 in Coating
Thickness manipulating the Reaction. The essential and
collaboration effect of the data influences on the ordinary
responses remain analyzed. The standard qualities and projected
values are truly near
The Study of Optimal Molding of a LED Lens with Grey Relational Analysis and Molding Simulation
Injection molding technology is known as the most widely used method in mass production of plastic products. To meet the quality requirements, a lot of methods were applied in optimization of injection molding process parameter. In this study the optimization based on Taguchi orthogonal array and Grey relational analysis (GRA) is used to optimize the injection molding process parameters on a LED lens. The four process parameters are: packing pressure, injection speed, melt temperature and mold temperature. The multi-response quality characteristics are total displacement, volumetric shrinkage, and thermal residual stress. The optimal molding parameters are packing pressure (90 MPa), injection speed (300 mm/sec), melt temperature (270 °C) and mold temperature (90 °C). The luminous uniformity of the LED is 92.61 % and the viewing angle of the LED is 124.76°. Among the four factors, packing pressure plays the key role in reducing total displacement, volumetric shrinkage, and thermal residual stress
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