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.

Multi-objective optimisation on end milling of hybrid fibre-reinforced polymer composites using GRA

2017 ◽  
Vol 46 (3) ◽  
pp. 194-202 ◽  
Author(s):  
M.P. Jenarthanan ◽  
Raahul Kumar S ◽  
Vinoth S
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Helix Angle ◽  
Inspection System ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
End Mill ◽  
Content Type ◽  
Gfrp Composite ◽  
Solid Carbide

Purpose This study aimed to develop a mathematical model for delamination and surface roughness during end milling by using grey relational analysis (GRA) 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. Design/methodology/approach The Four factors, three levels Taguchi orthogonal array design in GRA is used to conduct the experimental investigation. The Shop Vision inspection system is used to measure the width of maximum damage of the machined hybrid GFRP composite. The Shop Handysurf E-35A surface roughness tester is used to measure the surface roughness of the machined hybrid GFRP composite. “Minitab 14” is used to analyse the data collected graphically. Analysis of variance is conducted to validate the model in determining the most significant parameter. Findings The GRA is used to predict the input factors influencing the delamination and surface roughness on the machined surfaces of the hybrid GFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. Analysis on the influences of the entire individual input machining parameters on the delamination and surface roughness has been conducted using GRA. Originality/value Effect of milling of the hybrid GFRP composite on delamination and surface roughness with various helix angle solid carbide end mill has not been analysed yet using the GRA technique.

Mathematical modeling of delamination factor on end milling of hybrid GFRP composites through RSM

2016 ◽  
Vol 45 (5) ◽  
pp. 371-379 ◽  
Author(s):  
M.P. Jenarthanan ◽  
A. Lakshman Prakash ◽  
R. Jeyapaul
Keyword(s):  
End Milling ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
End Mill ◽  
Gfrp Composites ◽  
Content Type ◽  
Gfrp Composite ◽  
Solid Carbide ◽  
Mill Cutter

Purpose This paper aims to develop a mathematical model for delamination during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut and feed rate) influence the output response (delamination) in machining of hybrid glass fibre reinforced plastic (GFRP; abaca and glass) composite using solid carbide end mill cutter. Design/methodology/approach Three factors, three levels Box–Behnken design in RSM is used to carry out the experimental investigation. Shop microscope Mitutoyo TM-500 is used to measure the width of maximum damage of the machined hybrid GFRP composites. 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. Findings The RSM is used to predict the input factors influencing the delamination on the machined surfaces of hybrid GFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. Analysis on the influences of the entire individual input machining parameters on the delamination has been carried out using RSM. Originality/value Effect of milling of hybrid GFRP composite on delamination with solid carbide end mill has not been analysed yet using RSM.

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.

Optimization of process parameters on machining force and MRR during end milling of GFRP composites using GRA

2018 ◽  
Vol 15 (3) ◽  
pp. 407-413
Author(s):  
Jenarthanan MP ◽  
Prasanna Kumar Reddy Gavireddy ◽  
Chetan Sai Gummadi ◽  
Surya Ramesh Mandapaka
Keyword(s):  
Process Parameters ◽  
Fibre Orientation ◽  
Orientation Angle ◽  
Helix Angle ◽  
Depth Of Cut ◽  
Gfrp Composites ◽  
Content Type ◽  
Optimization Of Process Parameters ◽  
Machining Force ◽  
Fibre Orientation Angle

Purpose 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). Design/methodology/approach 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. Findings 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. Originality/value Optimization of process parameters on machining force and MRR during endmilling of GFRP composites using GRA has not been attempted previously.

Experimental investigation and analysis of machinability behaviour of hybrid GFRP composites during end milling

2016 ◽  
Vol 45 (3) ◽  
pp. 206-214
Author(s):  
M.P. Jenarthanan ◽  
A. Lakshman Prakash ◽  
R. Jeyapaul
Keyword(s):  
Surface Roughness ◽  
Experimental Investigation ◽  
Response Surface ◽  
End Milling ◽  
Surface Model ◽  
End Mill ◽  
Gfrp Composites ◽  
Content Type ◽  
Gfrp Composite ◽  
Solid Carbide

Purpose This paper aims to develop a mathematical model for analysing surface roughness during end milling by using response surface methodology (RSM) and to determine how the input parameters (cutting speed, depth of cut and feed rate) influence the output parameter (surface roughness) in the machining of hybrid glass fibre reinforced plastic (GFRP; Abaca and Glass) composite by using solid carbide end mill cutter. Design/methodology/approach Three factors and a three-level Box–Behnken design in RSM were used to carry out the experimental investigation. Handysurf E-35A was used to measure the surface roughness of the machined hybrid GFRP composites. The “Design Expert 8.0” was used to analyse the data collected graphically. Analysis of variance was carried out to validate the model and determine the most significant parameter. Findings The response surface model was used to predict the input factors influencing the surface roughness of the machined surfaces of hybrid GFRP composite at different cutting conditions with a chosen range of 95 per cent confidence intervals. Analysis of the influences of the entire individual input machining parameters on the surface roughness carried out using RSM. Originality/value The effect of the milling of hybrid GFRP composite on the surface roughness with solid carbide end mill by using RSM has not been analysed yet.

The Investigation of Prediction Surface Roughness from Machining Forces in End Milling Processes

2011 ◽  
Vol 486 ◽  
pp. 91-94 ◽  
Author(s):  
Jabbar Abbas ◽  
Amin Al-Habaibeh ◽  
Dai Zhong Su
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Irregular Waves ◽  
Depth Of Cut ◽  
End Mill ◽  
Machined Surface ◽  
Machining Forces ◽  
Mill Cutter

Surface roughness is one of the most significant parameters to determine quality of machined parts. Surface roughness is defined as a group of irregular waves in the surface, measured in micrometers (μm). Many investigations have been performed to verify the relationship between surface roughness and cutting parameters such as cutting speed, feed rate and depth of cut. To predict the surface produced by end milling, surface roughness models have been developed in this paper using the machining forces by assuming the end mill cutter as a cantilever beam rigidly or semi- rigidly supported by tool holder. An Aluminium workpiece and solid carbide end mill tools are used in this work. Model to predict surface roughness has been developed. Close relationship between machined surface roughness and roughness predicted using the measured forces signals.

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization by Response Surface Methodology

2011 ◽  
Vol 189-193 ◽  
pp. 1376-1381
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou El Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Ceramic ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents the prediction of a statistically analyzed model for the surface roughness,R_a of end-milled Machinable glass ceramic (MGC). Response Surface Methodology (RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is found that cutting speed is the most significant factor contributing to the surface roughness value followed by the depth of cut and feed rate. The surface roughness value decreases for higher cutting speed along with lower feed and depth of cut. Additionally, the process optimization has also been done in terms of material removal rate (MRR) to the model’s response. Ideal combinations of machining parameters are then suggested for common goal to achieve lower surface roughness value and higher MRR.

Surface Roughness Optimization in End Milling Using the Multi Objective Genetic Algorithm Approach

2012 ◽  
Vol 576 ◽  
pp. 103-106 ◽  
Author(s):  
Muataz H.F. Al Hazza ◽  
Erry Yulian Triblas Adesta ◽  
Muhammad Riza ◽  
M.Y. Suprianto
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
End Milling ◽  
Cutting Speed ◽  
Root Mean Square Roughness ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Machining Optimization

In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness is important for it is economical and mechanical issues. This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and minimum Root-mean-square roughness (Rq). The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed.

Effect of SiCp Reinforcement on Machinability of A356 Alloy Metal Matrix Composites

2016 ◽  
Vol 852 ◽  
pp. 142-148
Author(s):  
K. Jayakumar
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composites ◽  
Metal Matrix ◽  
End Milling ◽  
Cutting Speed ◽  
A356 Alloy ◽  
Experimental Result ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Matrix Composites

Machining of Aluminum Metal Matrix Composites (AMMCs) is a challenge for manufacturing industries due to their heterogeneous constituents which vary from soft matrix to hard reinforcements and their interfaces. To overcome the difficulties in machining of MMCs, researchers are continuously working to find the optimum process or machining parameters. In this work, End milling studies were carried out in A356 alloy powder-SiC particles (1 μm) in 0, 5, 10, 15 volume % reinforced AMMCs synthesised by vacuum hot pressing (VHP) route.The influence of machining parameters such as cutting speed, feed and depth of cut on the prepared composites in terms of surface roughness (Ra) and material removal rate (MRR) are measured from experimental study. Experiments were conducted as per Taguchi L16 orthogonal array with 4 factors and 4 levels.From the experimental result, it was identified that surface roughness varied from 0.214 μm to 4.115 μm and MRR varied from minimum of 1.11 cm3/min to maximum of 9.65 cm3/min. It is also observed that, MRR increased with increase in machining parameters and reinforcement quantity. Similarly, surface roughness decreased for increase of cutting speed, SiC particle (SiCp) reinforcement and increased for increase in feed and depth of cut. The optimum condition were observed in higher speed, lower feed and higher depth of cut on MMC with higher SiC content (15%) for getting higher machinability.

Processing and End Milling Behavioural Study of A356-SiCp Composite

2012 ◽  
Vol 710 ◽  
pp. 338-343 ◽  
Author(s):  
K. Jayakumar ◽  
Jose Mathew ◽  
M.A. Joseph ◽  
R. Suresh Kumar ◽  
P. Chakravarthy
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
End Milling ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Pressing Method ◽  
Reinforced Composite ◽  
Effect Of Particle Size

Machining process such as milling receives less attention in the study of machinability of composites due to its interrupted cutting and the complexity of the process. In the present study, A356 aluminium alloy powder reinforced with 10 volume % SiC particles of various sizes (1,12.5 and 25 µm) were synthesized by vacuum hot pressing method and the effect of particle size on the composites were analysed for its mechanical properties and machinability. End milling of these composites were carried out and the surface roughness and resultant cutting force were analysed with the change of machining parameters and varying SiC particle sizes. The minimum cutting force and surface roughness were obtained for a finer particle (1 µm) reinforced composite with higher cutting speed, low feed and depth of cut.

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