scholarly journals Optimization of Nozzle Inclination and Process Parameters in Air-Shielding Electrochemical Micromachining

Micromachines ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 846 ◽  
Author(s):  
Minghuan Wang ◽  
Yongchao Shang ◽  
Kailei He ◽  
Xuefeng Xu ◽  
Guoda Chen
Keyword(s):  
Process Parameters ◽  
Optimal Parameter ◽  
Test Method ◽  
Electrochemical Micromachining ◽  
Machining Performance ◽  
Relational Analysis ◽  
High Efficient ◽  
Grey Relational Grade ◽  
Orthogonal Test Method ◽  
Grey Relational

Microstructures on metal surfaces with diameters of tens to hundreds of micrometers and depths of several micrometers to tens of micrometers can improve the performance of engineering parts. Air-shielding electrochemical micromachining (AS-EMM) is a promising method for fabricating these microstructures, owing to its advantage of high efficient and better localization. However, the machining performance is often influenced by the machining or nonmachining parameters in AS-EMM. In order to get a better machining result in AS-EMM, the optimization of AS-EMM, including nozzle inclination and process parameters, was studied in this paper. Firstly, nozzle inclination was optimized by the different selected air incidence angles (θ) in simulation, and θ = π/4 was advised. Then, the grey relational analysis based on the orthogonal test method was used to analyze the grey relational grade for parameters and obtain the optimal parameter combination, i.e., at electrolyte velocity 5.5 m/s, gas velocity 160 m/s, and voltage 8 V. Finally, the optimization result was verified experimentally.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

Multi-Response Optimization of Dissimilar Al-Ti Alloy FSW Using Taguchi - Grey Relational Analysis

2020 ◽  
Vol 833 ◽  
pp. 35-39 ◽  
Author(s):  
Shival Patel ◽  
Kishan Fuse ◽  
Khushboo Gangvekar ◽  
Vishvesh Badheka
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Traverse Speed ◽  
Anova Analysis ◽  
Friction Stir ◽  
Relational Analysis ◽  
Significant Process ◽  
Grey Relational Grade ◽  
Response Optimization ◽  
Grey Relational

This article presents multi-response optimization of friction stir welding of dissimilar Al 6061-Titanium alloy using Taguchi based grey relational analysis. Taguchi’s L9 orthogonal array was used for designing the experiments. Process parameters considered for the experiments were rotational speed, traverse speed and tilt angle. Ultimate tensile strength, yield strength, and % elongation were the responses measured which all are larger-the-better characteristics. Based on grey relational grade, optimum levels of process parameters were identified and further ANOVA analysis was carried out to find most significant process parameter.

Effect of Process Parameters on Performance Measures in CNC Turning Using One Factor at a Time Approach for SS304

2016 ◽  
Vol 854 ◽  
pp. 26-32
Author(s):  
M. Fakkir Mohamed ◽  
B. Praveen Kumar ◽  
P.L. Madhavan ◽  
M. Pradeep
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Optimal Parameter ◽  
Numerical Control ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Process Factor ◽  
Relational Analysis ◽  
Grey Relational

This work extent with the improvement of machining parameters in turning of SS304 austenitic stainless-steel in Computer Numerical Control (CNC) shaping machine by victimization of coated inorganic compound tools. Throughout the experiment, process parameters like Speed, Feed and Depth of Cut are used to inquire their general intent on the Surface Roughness (Ra) and Material Removal Rate (MRR) as the quality targets. 9 experimental runs supported by one factor at a Time Approach as Design of Experiment and Grey Relational Analysis (GRA) method is applied to see associate degree for optimum CNC turning parameter setting. An optimal parameter combination of the turning method is obtained by victimization of Grey Relational Analysis. By dissecting the Grey Relational Grade matrix, the degree of influence for every controllable process factor onto individual quality targets is found for the higher performance characteristics.

scholarly journals Grey Relational Analysis to Determine the Optimum Process Parameters for Open-End Spinning Yarns

2012 ◽  
Vol 7 (2) ◽  
pp. 155892501200700 ◽  
Author(s):  
Hossein Hasani ◽  
Somayeh Akhavan Tabatabaei ◽  
Ghafour Amiri
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Raw Materials ◽  
Performance Characteristics ◽  
Optimum Process ◽  
Rotor Speed ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

This article focuses on an approach based on the Taguchi method with grey relational analysis for optimizing the process parameters for open-end spun yarns with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to optimize the process parameters. Optimal process parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. CVm%, hair number per meter, and tenacity of yarn were selected as quality characteristics. Using these characteristics, the process parameters, including rotor speed, rotor diameter, opener speed, yarn linear density and navel type are optimized. The raw materials used in this investigation were cotton fibers (35%) and cotton waste (65%) collected from ginning machines. The Experimental results show parameter rotor speed has the most significant effect on the multiple performance characteristics.

Experimental Investigation of Electrochemical Micromachaning Process Parameters on Pure-Titanium Using Taguchi-Grey Relational Analysis

2016 ◽  
Vol 852 ◽  
pp. 198-204
Author(s):  
T. Geethapriyan ◽  
K. Kalaichelvan
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Metal Removal ◽  
Removal Rate ◽  
Pure Titanium ◽  
Electrochemical Machining ◽  
Electrochemical Micromachining ◽  
Influence Of Process Parameters ◽  
Relational Analysis ◽  
Grey Relational

Non-conventional machine are nowadays plays a vital role in manufacturing complex shaped products and to produce the product with high accuracy the electrochemical machining is widely used to machine complicated shapes for electrically conducting difficult-to-machine materials such as super alloys, Ti-alloys, alloy steel, tool steel, stainless steel, etc. such titanium-based alloys are in common use for aero engine components such as blades and blisks (blade integrated disks). Therefore, in this present work to investigate the influence of some predominant electrochemical process parameters such as applied voltage, electrolyte concentration, Micro-tool feed rate and duty cycle on the metal removal rate , overcut and surface roughness to fulfill the effective utilization of electrochemical machining of Pure-titanium. The purpose of this study is to investigate the influence of process parameters on machining characteristics and optimize the combination of those parameters using Taguchi-grey relational analysis. From this result, it is observed that process parameters have significant role in Electrochemical Micromachining process and the optimization values has been found using proposed multi-response methodology.

scholarly journals MACHINABILITY STUDY ON AL- 10% TIC COMPOSITES AND OPTIMUM SETTING OF DRILLING PARAMETERS IN ELECTROCHEMICAL MICRO MACHINING USING GREY RELATIONAL ANALYSIS

2014 ◽  
Vol 44 (4) ◽  
pp. 331-338
Author(s):  
S. DHARMALINGAM ◽  
P. MARIMUTHU ◽  
K. RAJA
Keyword(s):  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Removal Rate ◽  
Matrix Composites ◽  
Micro Machining ◽  
Machining Performance ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

This paper investigates the influence of the process parameters like machining voltage, electrolyte concentration, frequency on the over cut and Material Removal Rate (MRR) on drilling of Al- 10% TiC Metal Matrix composites using Electrochemical Micro Machining (EMM) through taguchi methodology and grey relational analysis. Based on the analysis, optimum levels of parameters were determined and the same to validate through the confirmation test. Experimental results are in close agreement with the developed model. The confirmation results reveal that, there is considerable improvement in Material Removal Rate, Overcut. Grey relational grade are improved by 89.5 %, 57.9% and 95.16 % respectively. It is observed that the machining performance can be effectively improved with respect to initial parametric setting.

Multi-response optimization of EDM parameters using grey relational analysis (GRA) for Ti-5Al-2.5Sn titanium alloy

2020 ◽  
Vol 18 (1) ◽  
pp. 50-57
Author(s):  
Munmun Bhaumik ◽  
Kalipada Maity
Keyword(s):  
Titanium Alloy ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Optimal Parameter ◽  
Machining Efficiency ◽  
Peak Current ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time

Purpose In this research, electro discharge machining (EDM) of Ti-5Al-2.5Sn titanium alloy is performed taking gap voltage, pulse on time, peak current and duty cycle as process parameters. The purpose of this paper is to find out the optimal process parameters setting for getting higher machining efficiency. Design/methodology/approach For experimental design, a face-centered central composite design (FCCCD)-based response surface methodology (RSM) is used. Multi-objective optimization like grey relational analysis (GRA) is adopted to achieve the higher machining efficiency by means of lower radial overcut (ROC), surface roughness (Ra), tool wear rate (TWR) and higher material removal rate (MRR). For the statistical study, analysis of variance (ANOVA) has been carried out. Findings The result shows that gap voltage, peak current and pulse on time are the most efficient parameters for the responses. An optimal parameter setting has been obtained for achieving higher machining efficiency. For validation of the study, confirmation experiment has been performed at optimal parameters setting. Originality/value Optimum parameter level for higher machining performance of Ti-5Al-2.5Sn Titanium alloy has been achieved machined by copper electrode during EDM operation.

scholarly journals Analysis and optimization of laser drilling process during machining of AISI 303 material using grey relational analysis approach

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
V. Chengal Reddy ◽  
Thota Keerthi ◽  
T. Nishkala ◽  
G. Maruthi Prasad Yadav
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Pulse Frequency ◽  
Laser Drilling ◽  
Simultaneous Optimization ◽  
Fibre Laser ◽  
Drilling Process ◽  
Relational Analysis ◽  
Grey Relational

AbstractSurface roughness and heat-affected zone (HAZ) are the important features which influence the performance of the laser-drilled products. Understanding the influence of laser process parameters on these responses and identifying the cutting conditions for simultaneous optimization of these responses are a primary requirement in order to improve the laser drilling performance. Nevertheless, no such contribution has been made in the literature during laser drilling of AISI 303 material. The aim of the present work is to optimize the surface roughness (Ra) and HAZ in fibre laser drilling of AISI 303 material using Taguchi-based grey relational analysis (GRA). From the GRA methodology, the recommended optimum combination of process parameters is flushing pressure at 30 Pa, laser power at 2000 W and pulse frequency at 1500 Hz for simultaneous optimization of Ra and HAZ, respectively. From analysis of variance, the pulse frequency is identified as the most influenced process parameters on laser drilling process performance.

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