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.

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.

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.

Experimental investigation and analysis of factors influencing delamination and surface roughness of hybrid GFRP laminates using Taguchi technique

2016 ◽  
Vol 45 (6) ◽  
pp. 463-475 ◽  
Author(s):  
M.P. Jenarthanan ◽  
A. Lakshman Prakash ◽  
R. Jeyapaul
Keyword(s):  
Surface Roughness ◽  
Experimental Investigation ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
End Mill ◽  
Content Type ◽  
Cutting Parameter ◽  
Gfrp Composite ◽  
Solid Carbide

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

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.

Surface Roughness Model when Machining Aluminum Nitride Ceramic with Two Flute Square End Micro Grain Solid Carbide End Mill

2013 ◽  
Vol 747 ◽  
pp. 282-286 ◽  
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
K.A. Abou-El-Hossein ◽  
D. Sujan
Keyword(s):  
Surface Roughness ◽  
Aluminum Nitride ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
End Mill ◽  
Roughness Model ◽  
Solid Carbide

This research presents the performance of Aluminum Nitride ceramic in end milling using two flute square end micro grain solid carbide end mill under dry cutting. Surface finish is one of the important requirements in the machining process. This paper describes mathematically the effect of cutting parameters on surface roughness in end milling process. The quadratic model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using the response surface methodology (RSM). Design of experiments approach was employed in developing the surface roughness model in relation to cutting parameters. The predicted results are in good agreement with the experimental results within the specified range of cutting conditions. Experimental results showed surface roughness increases with increase in the cutting speed, feed rate, and the axial depth of cut.

Multi-objective optimization in end-milling of glass fiber reinforced polymer composites using desirability functional analysis and grey relational analysis

2017 ◽  
Vol 13 (3) ◽  
pp. 391-408
Author(s):  
M.P. Jenarthanan ◽  
Venkata Sai Sunil Gujjalapudi ◽  
Venkatraman V.
Keyword(s):  
End Milling ◽  
Orientation Angle ◽  
Composite Plates ◽  
Helix Angle ◽  
Machining Parameters ◽  
Content Type ◽  
Glass Fiber Reinforced ◽  
Gfrp Composite ◽  
Fiber Orientation Angle ◽  
Grey Relational

Purpose 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). Design/methodology/approach 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. Findings 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. Originality/value Multi-objective optimization in end-milling of GFRP composites using DFA and GRA has not been performed yet.

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.

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.

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