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 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.

Optimization of CNC Turning Operations with Multiple Performance Characteristics using Taguchi based Grey Relational Analysis

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
P. Lakshmikanthan ◽  
B. Prabu
Keyword(s):  
Analysis Of Variance ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Turning Operations ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational

This study investigates the optimization of CNC turning operation parameters for Al6061 nickel coated graphite (NCG) metal matrix composite using the Taguchi based grey relational analysis method. The turning operations are carried out with carbide cutting tool inserts. According to the Taguchi quality concept, 3-level orthogonal array was chosen for the experiments. The experiments are conducted at three different cutting speeds (125, 175, 225m/min) with feed rates (0.1, 0.15, 0.2mm/rev) and depth of cut (0.5, 1, 1.5mm) and different % of reinforcement (2.5%, 5%, 7.5%), signal to noise ratio and the analysis of variance are used to optimize cutting parameters. The effects of cutting speed, feed rate and depth of cut on surface roughness and MRR are analyzed. Mathematical models are developed by using the response surface method to formulate the cutting parameters experimental results shown that machining performance can be improved effectively by using this approach, the analysis of variance (ANOVA) is applied to identify the most significant factor for the turning operations according to the weighted sum grade of the GRG. The predict responses shows the models have more than 95% of confident level of R2 value, from the obtained confirmation experiment result, it is observed, there is a good agreement between the estimated value and the experimental value of the grey relational grade. This experimental study reveals that the grey-Taguchi and RSM can be applied successfully for multi response characteristic performances.

Multi-response optimization of CNC turning parameters of austenitic stainless steel 303 using Taguchi-based grey relational analysis

2020 ◽  
Vol 44 (4) ◽  
pp. 592-601
Author(s):  
S.R. Sundara Bharathi ◽  
D. Ravindran ◽  
A. Arul Marcel Moshi
Keyword(s):  
Stainless Steel ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Regression Equations ◽  
Turning Process ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational ◽  
Cnc Turning Process

Extensive research has been carried out to optimize the process parameters of several machining processes. Optimizing the influencing parameters of the turning operation is a precise action that determines the desired level of quality. This study focuses on the multi-criteria optimization of the CNC turning process parameters of stainless steel 303 (SS 303) material to achieve minimum surface roughness (Ra) with maximum material removal rate (MRR) by means of Taguchi-based grey relational analysis. A CNC machine was tested following Taguchi’s L9 orthogonal array design. Grey relational analysis was used as the multi-criteria optimization tool. The significance of each individual process parameter on the overall characteristics of the turned specimen was estimated using analysis of variance (ANOVA). Regression equations were generated using the input factors with the selected output parameters. In addition, a morphological study of the chips produced by the turning process was carried out using SEM images in order to relate the chip geometry with the output responses.

Modelling and Optimization of Machining parameters for Turning Automotive Shafts using RSM and Grey Relational Analysis

2020 ◽  
Vol 12 (4) ◽  
Author(s):  
S. Dinesh ◽  
K. Rajaguru ◽  
K. Saravanan ◽  
R. Yokeswaran ◽  
V. Vijayan
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational ◽  
Central Composite ◽  
Modelling And Optimization

Automotive shafts require maximum strength with regard to axial, bending and torsional loading to transmit power to various parts of a vehicle. Hence, it is very critical to analyse the manufacturing process and its governing parameters to exercise control over the surface properties of the shaft as it needs to be precisely manufactured in terms of dimensions and the surface roughness. The effect of three input parameters over two responses are considered as two major criteria's for production of shaft. The input parameters are speed, feed and depth of cut whereas the responses are material removal rate and surface roughness. Central Composite design was used and experimental results were analysed with Response Surface Methodology. ANOVA analysis was carried out to identify the most contributing parameter for MRR and SR. Grey Relational Analysis was adopted to identify the most feasible combination of machining parameters for turning process. The optimized parameter is identified as speed of 1000 rpm, 0.15 mm of feed and 0.35 mm of depth of cut using Grey Relational Analysis.

Optimization of Multiple Responses in Dry Turning Process Using Taguchi-Grey Relational Analysis

2014 ◽  
Vol 592-594 ◽  
pp. 620-624
Author(s):  
Sumit Verma ◽  
Hari Singh
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Tangential Force ◽  
Cutting Speed ◽  
Relational Theory ◽  
Depth Of Cut ◽  
Multiple Responses ◽  
Relational Analysis ◽  
Grey Relational ◽  
Optimal Cutting Parameters

The present study investigates the optimization of multiple responses in turning of EN-8 steel by the Taguchi and grey relational analysis. The performance characteristics considered are tangential force, feed force and radial force. Grey relational theory is adopted to determine the best process parameters that give lower magnitude of tangential, feed, radial forces and optimal cutting parameters. An orthogonal array L18 is used for the experimental design. The setting of process parameters— nose radius, 0.8mm; cutting speed, 60.65 m/min; feed rate, 0.04 mm/rev; and depth of cut, 0.60 mm— has highest grey relational grade and therefore produces best turning performance in terms of cutting forces.

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 Optimization of Machining Parameters using ANOVA and Grey Relational Analysis while Turning Aluminium 7075

2019 ◽  
Vol 8 (2) ◽  
pp. 5682-5686
Keyword(s):  
Grey Relational Analysis ◽  
High Speed ◽  
Removal Rate ◽  
High Speed Steel ◽  
Depth Of Cut ◽  
Total Production ◽  
Machining Parameters ◽  
Turning Operation ◽  
Relational Analysis ◽  
Grey Relational

In this research a detailed study is carried out on machining parameters for turning operation on aluminium 7075 with high speed steel. This grade of aluminium is known for its applications in aerospace industry and research about its machining parameters will lead to more developments in the field of production. Aim of this work is to optimize turning operation. Machining parameters viz. speed, feed and depth of cut are taken as input parameters. Material removal rate (MRR), tool wear (TWR), surface roughness (SR) are taken as output parameters and the set of optimized parameters means reduction in total production cost. The experiments are planned using Taguchi’s L9 orthogonal array. Grey relational analysis (GRA) is used for multi objective optimization using grey relational grades. Application of analysis of variance(ANOVA) helps in the identification of most prominent parameters among speed, feed and depth of cut

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