Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool

2006 ◽  
Vol 21 (8) ◽  
pp. 846-852 ◽  
Author(s):  
K. Palanikumar ◽  
L. Karunamoorthy ◽  
R. Karthikeyan
Keyword(s):  
Performance Optimization ◽  
Machining Parameters ◽  
Gfrp Composites

Analysis and optimisation of machinability behavior of GFRP composites using fuzzy logic

2015 ◽  
Vol 11 (1) ◽  
pp. 102-119 ◽  
Author(s):  
Jenarthanan Poornachary Mugundhu ◽  
Suresh Subramanian ◽  
Ajay Subramanian
Keyword(s):  
Fuzzy Logic ◽  
Machining Process ◽  
Depth Of Cut ◽  
Work Piece ◽  
Mechanical And Thermal Properties ◽  
Machining Parameters ◽  
End Mill ◽  
Gfrp Composites ◽  
Content Type ◽  
Useful Life

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Originality/value – Multi-response optimisation of machinability behaviour of GFRP composites using fuzzy logic has not been attempted previously.

scholarly journals Multi-Performance Optimization in Electrical Discharge Machining of Al2O3 Ceramics Using Taguchi Base AHP Weighted TOPSIS Method

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1647
Author(s):  
Yue-Peng Zeng ◽  
Chiang-Lung Lin ◽  
Hong-Mei Dai ◽  
Yan-Cherng Lin ◽  
Jung-Chou Hung
Keyword(s):  
Process Parameters ◽  
Performance Optimization ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Statistical Technique ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Relative Closeness ◽  
Machining Parameter

The main application of electrical discharge machining in ceramic processing is limited to conductive ceramics. However, the most commonly used non-conductive potteries in modern industry, such as aluminum oxide (Al2O3), also reveal the limitations of choosing a suitable process. In this study, Taguchi based TOPSIS coupled with AHP weight method to optimize the machining parameters of EDM on Al2O3 leads to better multi-performance. The results showed that the technique is suitable for tackling multi-performance machining parameter optimization. The adhesive foil had a significant impact on material removal rate, electrode wear rate, and surface roughness, according to the findings. In addition, the response graph of relative closeness is used to determine the optimal combination levels of machining parameters. A confirmation test revealed a good agreement between predicted and experimental preference values at an optimum combination of the input parameters. The suggested experimental and statistical technique is a simple, practical, and reliable methodology for optimizing EDM process parameters on Al2O3 ceramics. This approach might be utilized to optimize and improve additional process parameters in the future.

Optimization of Machining Parameters during Drilling of 7075 Aluminium Alloy

2012 ◽  
Vol 248 ◽  
pp. 20-25
Author(s):  
Abolfazl Golshan ◽  
Danial Ghodsiyeh ◽  
Soheil Gohari ◽  
Amran Bin Ayob ◽  
B.T. Hang Tuah Baharudin
Keyword(s):  
Aluminum Alloy ◽  
Performance Optimization ◽  
High Performance ◽  
Cutting Speed ◽  
Drilling Process ◽  
Machining Parameters ◽  
Algorithm Optimization ◽  
Drilling Parameters ◽  
Drill Diameter ◽  
Selection Of

Proper selection of drilling parameters is one of the significant challenges in drilling process. In this study, a new method for selection of optimal machining parameters during drilling operation is investigated. The present study deals with multiple-performance optimization of machining characteristics during drilling of 7075 aluminum alloy. The most commonly-used material in aerospace industry is aluminum alloy with zinc as the primary alloying element. The drilling parameters used for this experiment include cutting speed, feed rate and drill diameter while the two output parameters are surface roughness and dimension error. These outputs are specified to be optimized as a measure of process performance. The statistical model is generated from linear polynomial equations which are developed from different output responses when the machining parameters are changed. The Non-dominated Sorting Genetic Algorithm optimization results show high performance in solving the present problem.

Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with principal component analysis

2017 ◽  
Vol 13 (1) ◽  
pp. 58-70 ◽  
Author(s):  
M.P. Jenarthanan ◽  
R. Gokulakrishnan ◽  
B. Jagannaath ◽  
P. Ganesh Raj
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Principal Component ◽  
Helix Angle ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
End Mill ◽  
Gfrp Composites ◽  
Content Type ◽  
Machining Force

Purpose The purpose of this paper is to find out the optimum machining parameters using Taguchi technique with principal component analysis (PCA) during end milling of GFRP composites. Design/methodology/approach In multi-objective optimization, weight criteria of each objective are important for producing better and accurate solutions. This method has been employed for simultaneous minimization of surface roughness, cutting force and delamination factor. Experiments were planned using Taguchi’s orthogonal array with the machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate and depth of cut were optimized with considerations of multiple response characteristics, including machining force, surface roughness and delamination as the responses. PCA is adopted to find the weight factors involved for all objectives. Finally analysis of variance concept is employed on multi-SN ratio to find out the relative significance of machining parameter in terms of their percentage contribution. Findings The multi-SN ratio is achieved by the product of weight factor and SN ratio to the performance characteristics in the utility concept. The results show that a combination of machining parameters for the optimized results has helix angle of 35°, machining speed of 4,000 m/min, feed rate of 750 mm/rev and depth of cut of 2.0 mm. Originality/value Effect of milling of GFRP composites on delamination factor, surface roughness and machining force with various helix angle solid carbide end mill has not been analysed yet using PCA techniques.

Soft Computing Applications in Drilling of GFRP Composites: A Review

2013 ◽  
Vol 766 ◽  
pp. 99-107
Author(s):  
V.S. Senthil Kumar ◽  
C. Ezilarasan
Keyword(s):  
Surface Roughness ◽  
Composite Structures ◽  
Thrust Force ◽  
Optimization Techniques ◽  
Machining Parameters ◽  
Automotive Electronics ◽  
Gfrp Composites ◽  
Machining Processes ◽  
Nsga Ii ◽  
Reinforced Plastics

Glass fiber reinforced plastics (GFRP) are finding increased applications in various engineering fields such as aerospace, automotive, electronics and other industries. Among the various machining processes, drilling is the important process, mainly used in joining of composite structures. As a consequence, the number of authors have discussed on the aspects concerning the machiniability of GFRP composites. In this study, a review has been done on the machinability of drilling of GFRP composites through the various aspects such as tool materials and geometry, machining parameters and their influence on thrust force, torque, surface roughness, delamination factor and hole damage. Additionally, the modeling of the machining parameters on drilling of GFRP composites using response surface methodology (RSM), artificial neural network (ANN), fuzzy logic, NSGA-II etc., have been discussed. The results indicated that the thrust force, torque and surface roughness need to be controlled simultaneously for delamination free drilling. Further, there is a need to create a multi-response optimization in drilling of GFRP composites using different optimization techniques for obtaining optimum results of thrust force, torque, surface roughness and delamination free drilling.

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