scholarly journals Optimum combination of machining parameters during drilling of Aluminium 7075 alloys using Grey based Taguchi approach

2020 ◽  
Vol 4 (3) ◽  
pp. 227-238
Author(s):  
Reddy Sreenivasulu ◽  
Ch. Srinivasa Rao
Keyword(s):  
Value Added ◽  
Influential Factors ◽  
Optimal Combination ◽  
Performance Characteristics ◽  
Burr Formation ◽  
Production Cycle ◽  
Drilling Process ◽  
Machining Parameters ◽  
Burr Size ◽  
Grey Relational

From ancient days to till today manufacturing industries, especially making of holes on the parts during drilling process for precision assembling of parts facing problems with burr formation. Drilling operation is one of the finishing operation in the production cycle, removing of burrs during drilling process is a time consuming and non-value added process to the manufacturing sector. So reducing the size of burrs is the main aim of the present study. In the present work, optimization of burr size is considered during drilling of aluminium 7075 alloy. From Grey relational grades of responses selected optimal combination of parameters to attain multiple performance characteristics of responses with a corresponding higher grey relational grade. For identifying the most significant input parameters that influence the output responses ANOVA is conducted. Finally, observations reveals that feed rate, point and clearance angles are the most influential factors on burr size and also experimental results divulge that the lower the thrust force causes to decrease the burr height. The proposed approach is helpful to the budding entrepreneurs in the related areas to select optimal combination of drilling parameters to attain multiple performance characteristics of responses especially in burr size to prevent the post finishing operations.

scholarly journals Development of a user-friendly drilling evaluation database system of CFRP

2018 ◽  
Vol 25 (6) ◽  
pp. 1205-1217
Author(s):  
Gong Dong Wang ◽  
Nan Li ◽  
Tian Peng ◽  
Ying Chi Li ◽  
Xu Hai Xiong ◽  
...  
Keyword(s):  
Classification Tree ◽  
Database System ◽  
Influential Factors ◽  
Standard Theory ◽  
Production Cycle ◽  
Drilling Process ◽  
Tree Model ◽  
Drilling Parameters ◽  
User Friendly ◽  
3D Evaluation

AbstractThe drilling process of carbon fiber reinforced plastics (CFRP) is the main secondary processing in the entire production cycle. However, there is no standard theory that could be used to estimate the hole quality and to quantify the assessment. Therefore, in this article, several influential factors of drilling quality, such as drilling parameters and materials, were utilized to establish the classification tree model. A comprehensive evaluation model [three-dimensional (3D) evaluation factor] was presented to measure and quantify the quality of the hole. Then a series of experiments were designed based on existing conditions. Further, a mathematical software (Origin) was used to fit and analyze the relationships of the drilling parameters and the 3D evaluation factor. Then a user-friendly drilling database system of CFRP was established based on the historical data of drilling experiments and the fitting function. In addition, in order to contrast the optimization results of the fitting function, the drilling experiments have been conducted, and the results have verified that the drilling database system could optimally predict the drilling schemes with a minor error.

A review of mechanical drilling on fiber metal laminates

2020 ◽  
pp. 002199832095774
Author(s):  
Eduardo Pires Bonhin ◽  
Sarah David-Müzel ◽  
Manoel Cléber de Sampaio Alves ◽  
Edson Cocchieri Botelho ◽  
Marcos Valério Ribeiro
Keyword(s):  
Mechanical Properties ◽  
Cutting Parameters ◽  
Burr Formation ◽  
Drilling Process ◽  
Machining Parameters ◽  
Specific Mass ◽  
Fiber Metal Laminates ◽  
Dimensional Error ◽  
Main Method ◽  
Fiber Metal

The use of fiber metal laminates (FML) in aeronautics components has been increased in the last years, mainly due to the gain in mechanical properties combined with low specific mass. However, in the assembly of these materials on the structures to which they will be attached, mechanical screwing is still the main method used, which requires the performance of drilling processes. Something it is very complicated for these materials and can cause damage that compromises the performance. Therefore, this work aims to approach and summarize the evolution of the mechanical drilling process on FML developed in the last years. By the work, the main problems that occur during the drilling of these materials are punctually approached, such as delamination, burr formation, dimensional error, poor roughness, and tool wear. In addition, it is presented how these problems are affected by the machining parameters (cutting parameters, geometry, material/coating tool, and cutting environment), as well as suggestions for minimizing process problems. Thus, the article intends to provide as much information as possible available in the literature, seeking to help researchers gain a comprehensive view of the mechanical drilling of fiber metal laminates.

Multiple Performance Optimization in WEDM Parameters Using Grey Relational Analysis

2015 ◽  
Vol 813-814 ◽  
pp. 357-361
Author(s):  
T. Rajmohan ◽  
Gopi Krishna ◽  
Ankit Kumar Singh ◽  
A.P.V. Swamy Naidu
Keyword(s):  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
304L Stainless Steel ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time

In this investigation, a new approach is based on Grey Relational Analysis and Taguchi method to optimize the machining parameters with multi performance characteristics in WEDM of 304L SS. Experiments are conducted using Taguchi Quality Concept, L9,3-level orthogonal array was chosen for experiments .The WEDM parameters namely pulse-on time (TON), pulse-off time (TOFF), and wire feed (WF) on material removal rate (MRR) .The Grey Relational Analysis with multiple performance characteristics indicates that the pulse-on time (TON), pulse-off time (TOFF) are the most significant factors . The optimum machining parameters have been identified by Grey relational analysis and significant contribution of parameters can be determined by analysis of variance (ANOVA). The confirmation test is also conducted to validate the test result. The results from this study will be useful for manufacturing engineers to select appropriate WEDM process parameters to machine 304L Stainless Steel.

Optimization of EDM Hole Drilling Parameters in Machining of MoSi2-SiC Intermetallic/Composites for Improving Geometrical Tolerances

2015 ◽  
Vol 14 (04) ◽  
pp. 259-272 ◽  
Author(s):  
L. Selvarajan ◽  
C. Sathiya Narayanan ◽  
R. Jeyapaul
Keyword(s):  
Ceramic Composites ◽  
Performance Characteristics ◽  
Drilling Process ◽  
Electrode Wear ◽  
Machining Parameters ◽  
New Approach ◽  
Drilling Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Dielectric Flushing

Intermetallic/ceramic composites with multiple responses are based on L18 orthogonal array with gray relational analysis (GRA). This paper presents a new approach for the optimization of drilling parameters on drilling MoSi 2– SiC composites. Optimal machining parameters can then be determined by the gray relational grade as the performance index. In this study, the sparking parameters namely current (I), pulse on time (t on ), pulse off time (t off ), spark gap and dielectric flushing pressure (P) are optimized with considerations of multiple performance characteristics including multi responses such as material removal rate (MRR), electrode wear rate (EWR), circularity (CIR), cylindricity (CYL), perpendicularity (PER). A gray relational grade obtained from the GRA is used to solve the electrical discharge machining (EDM) process with the multiple performance characteristics. Based on the gray relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in EDM drilling process can be improved effectively through the new approach.

Optimization of Multiple Performances for EDM in Gas Media Using Grey Relational Analysis

2014 ◽  
Vol 620 ◽  
pp. 173-178
Author(s):  
Fang Pin Chuang ◽  
Yan Cherng Lin ◽  
Han Ming Chow ◽  
A. Cheng Wang
Keyword(s):  
Grey Relational Analysis ◽  
Electrical Discharge Machining ◽  
Design Method ◽  
Removal Rate ◽  
Performance Characteristics ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational ◽  
Machining Parameter

The aim of this investigation is to optimize the multiple performance characteristics of electrical discharge machining (EDM) for SKD 61 tool steel in gas media using grey relational analysis. The three most important machining characteristics namely material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR) were considered as the measures of the performance characteristics. A series of experiments were conducted according to an L18 orthogonal array based on the Taguchi experimental design method. The observed data obtained from the experiments were evaluated to determine the optimization of machining parameters correlated with multiple performance characteristics through grey relational analysis. Moreover, analysis of variance (ANOVA) was conducted to explore the significant machining parameters crucially affecting the multiple performance characteristics. In addition, the optimal combination levels of machining parameters were also determined from the response graph of grey relational grades for each level of machining parameter.

Autoresonant Tuning and Control in Ultrasonic Vibration Assisted Drilling Process

2006 ◽  
Vol 505-507 ◽  
pp. 823-828 ◽  
Author(s):  
Yu Chieh Chen ◽  
Yunn Shiuan Liao ◽  
J.D. Fan
Keyword(s):  
Cutting Parameters ◽  
Milling Process ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Drilling Process ◽  
Side Milling ◽  
Relational Analysis ◽  
Radial Depth ◽  
Grey Relational ◽  
Optimal Cutting Parameters

This paper presents an optimal cutting-parameter design of heavy cutting in side milling for SUS304 stainless steel. The orthogonal array with relational analysis is applied to optimize the side milling process with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used as a performance index to determine the optimal cutting parameters. The selected cutting parameters are cutting speed, feed per tooth, axial depth of cut, and radial depth of cut, while the considered performance characteristics are tool life and metal removal rate. Experimental results have shown that cutting performance in the side milling process for heavy cutting can be significantly improved through this approach.

Study on Burr Formation in Face Milling of Stainless Steel with Chamfered Cutting Tool

2008 ◽  
Vol 53-54 ◽  
pp. 83-88 ◽  
Author(s):  
Lu Lu Jing ◽  
Qing Long An ◽  
Ming Chen
Keyword(s):  
Stainless Steel ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Face Milling ◽  
Cutting Edge ◽  
Burr Formation ◽  
Maximum Height ◽  
Machining Parameters ◽  
Burr Size ◽  
Exit Burr

Due to the properties such as high strength and high toughness, burr was commonly produced in the machining of stainless steel 1Cr18Ni9Ti, especially when a chamfered cutting tool was used. This study investigated the effects of chamfering geometry of cutting edge and machining parameters on burr formation and presented active control methods to minimize burr size on the exit end based on the experimental research in milling of 1Cr18Ni9Ti. Experiments of face milling with various cutting edge geometric features were conducted. Maximum height and thickness of exit burr and exit side burr were measured. As a result, a proper chamfering geometry that combined the advantages of enhancing the cutting edge strength and obtaining favorable burr types was presented. The experimental results also showed that a relatively high cutting speed was helpful in reducing burr formation; proper medium feed rate and axial depth were favorable for the minimization of burr size. This research is beneficial for precise machining of stainless steel.

Determination of Optimum Parameters for Multi-Performance Characteristic in Turning of Al 6061-6% ZrB2 in-situ Metal Matrix Composite Using Grey Relational Analysis

2012 ◽  
Vol 2 (1) ◽  
pp. 11-29 ◽  
Author(s):  
A. Mahamani ◽  
N. Muthukrishnan ◽  
V. Anandakrishnan
Keyword(s):  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Grey Relational Analysis ◽  
Feed Rate ◽  
Metal Matrix ◽  
Performance Characteristics ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational

In-situ aluminum matrix composite is the innovation of high performance material technology and it has superior interfacial integrity and thermodynamic stability between the matrix and reinforcement. During synthesis, the ZrB2 particle is formed by exothermic reaction within the aluminum melt. As a result, small, fine and oxide free reinforcements are formed. Excessive temperature released from in-situ chemical reaction will facilitate the homogeneous distribution of particles in entire shape of the composites. Making the engineering components from this composite material require machining operations. Therefore, addressing the machinability issues of the composite is very important. This paper proposes an approach to optimize the machining parameters in turning of Al 6061-6% ZrB2 in-situ Metal Matrix Composite (MMC) with multiple performance characteristics by using grey relational analysis. The effect of in-situ ZrB2 reinforcement particles on machinability behavior need to be studied. The machining parameters, namely cutting speed, feed rate and depth of cut are optimized with considerations of multiple performance characteristics including surface roughness, tool wear and cutting force. It is concluded that the feed rate has the strongest effect. The confirmation experiment indicates that there is a good agreement between the estimated value and experimental value of the Grey relational grade.

The Use of the Taguchi-Grey Based to Optimize High Speed End Milling with Multiple Performance Characteristics

2006 ◽  
Vol 505-507 ◽  
pp. 835-840 ◽  
Author(s):  
Shen Jenn Hwang ◽  
Yunn Lin Hwang ◽  
B.Y. Lee
Keyword(s):  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

This paper presents a new approach for the optimization of the high speed machining (HSM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters such as cutting speed, feed rate and axial depth of cut are optimized under the multiple performance characteristics including, tool life, surface roughness, and material removal rate(MMR). As shown experimental results, machining performance in the HSM process can be improved effectively through this approach.

Machining Parameters Optimization for WEDM Based on Grey Relational Analysis

2013 ◽  
Vol 401-403 ◽  
pp. 1385-1392 ◽  
Author(s):  
Shi Ping Zhang ◽  
Yi Chao Ding ◽  
Wen Li Zhang
Keyword(s):  
Grey Relational Analysis ◽  
Parameters Optimization ◽  
Performance Characteristics ◽  
Pulse Interval ◽  
Machining Parameters ◽  
Machining Time ◽  
Relational Analysis ◽  
Machining Parameters Optimization ◽  
Grey Relational ◽  
Wedm Process

This paper presents an effective approach for the optimization of the wire electric discharge machining (WEDM) process with multiple performance characteristics based on the grey relational analysis. Twenty five experimental runs based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The response table and response graph for each level of the machining parameters were obtained from the grey relational grade. In this study, the machining parameters such as the machining voltage, the number of power amplifier tube, pulse width and pulse interval are optimized with consideration of multiple-performance characteristics, such as machining time and surface roughness. It is clearly shown that the above performance characteristics in WEDM process can be improved effectively through this approach. keywords: WEDM; grey relational analysis; parameter optimization; performance characteristics

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