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.

Optimization of Cutting Parameters of Multiple Performance Characteristics in End Milling of AlSi/AIN MMC – Taguchi Method and Grey Relational Analysis

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
S. H. Tomadi ◽  
J. A. Ghani ◽  
C. H. Che Haron ◽  
M. S. Kasim ◽  
A. R. Daud
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Volume Fraction ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Grey Relational

The main objective of this paper is to investigate and optimize the cutting parameters on multiple performance characteristics in end milling of Aluminium Silicon alloy reinforced with Aluminium Nitride (AlSi/AlN MMC) using Taguchi method and Grey relational analysis (GRA). The fabrication of AlSi/AlN MMC was made via stir casting with various volume fraction of particles reinforcement (10%, 15% and 20%). End milling machining was done under dry cutting condition by using two types of cutting tool (uncoated & PVD TiAlN coated carbide). Eighteen experiments (L18) orthogonal array with five factors (type of tool, cutting speed, feed rate, depth of cut, and volume fraction of particles reinforcement) were implemented. The analysis of optimization using GRA concludes that the better results for the combination of lower surface roughness, longer tool life, lower cutting force and higher material removal could be achieved when using uncoated carbide with cutting speed 240m/min, feed 0.4mm/tooth, depth of cut 0.3mm and 15% volume fraction of AlN particles reinforcement. The study confirmed that with a minimum number of experiments, Taguchi method is capable to design the experiments and optimized the cutting parameters for these performance characteristics using GRA for this newly develop material under investigation.

scholarly journals Development of Bio-Cutting Fluid (Cirtullus lanatus) and its Performance Assessment on the Machining of AISI 1525 Steel Using Taguchi Technique and Grey Relational Analysis

2021 ◽  
Vol 12 (4) ◽  
pp. 5324-5346
Keyword(s):  
Vegetable Oils ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Mineral Oils ◽  
Relational Analysis ◽  
Grey Relational

Due to traditional mineral oils' adverse environmental and health effects, vegetable oil-based cutting fluids have become widely attractive in machining. The majority of the vegetable oils used in literature are edible and may compete with human consumption if promoted, thereby making it more expensive as cutting fluids. However, few studies have been carried out on the applicability of lesser-known vegetable oils as cutting fluids. This study, therefore, aims at investigating the efficiency of lesser-known vegetable oil (watermelon oil) as a machining cutting fluid. The developed watermelon oil was mechanically compared to the traditional mineral oil in turning AISI 1525 steel based on cutting temperature, surface roughness, and chip formation mode. The experiment depended on Taguchi plan with L9 orthogonal arrangement utilizing feed rate, depth of cut, and cutting speed as critical input parameters. Moreover, the grey relational analysis optimization approach was employed to analyze the parameter impacts and achieve the best possible cutting parameters. The optimization showed that the best combinations of cutting parameters for cutting speed, feed rate, and depth of cut were (355 rev/min, 0.1 mm/rev and 1 mm), and (355 rev/min, 0.1 mm/rev, and 1.25 mm) for watermelon and mineral oils, respectively.

Response Surface Modeling and Grey Relational Analysis to Optimize Turning Parameters with Multiple Performance Characteristics

2012 ◽  
Vol 2 (2) ◽  
pp. 12-45 ◽  
Author(s):  
L. B. Abhang ◽  
M. Hameedullah
Keyword(s):  
Response Surface ◽  
Grey Relational Analysis ◽  
Cutting Parameters ◽  
Interface Temperature ◽  
Nose Radius ◽  
Turning Operations ◽  
Relational Analysis ◽  
Feed Force ◽  
Grey Relational Grade ◽  
Grey Relational

Optimization of process parameters is the key step in response surface methods to achieve high quality without cost inflation. The multi-response optimization of the machining parameters viz, chip-tool interface temperature, main cutting force and feed force on lathe turning of En-31 steel as alloy steel using RSM with grey relational analysis is reported. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. The models were developed using response surface methodology. Optimal cutting parameters can be determined by RSM method using the grey relational grade as the performance index. Chip-tool interface temperature, main cutting force, and feed force are important characteristics in turning operations. Using these characteristics, the cutting operations, including cutting velocity, feed rate, depth of cut, and effective tool nose radius, are optimized. A model is developed to correlate the multiple performance characteristic called grey relational grade and turning parameters and a new combination of RSM and grey relational analysis is proposed. The grey relational grades were significantly affected by cutting parameters and tool nose radius. Optimal parameter setting is determined for the multi-performance characteristic.

scholarly journals Multiobjective Optimization of Surface Integrity in Milling TB6 Alloy Based on Taguchi-Grey Relational Analysis

2014 ◽  
Vol 6 ◽  
pp. 280313 ◽  
Author(s):  
Kaining Shi ◽  
Dinghua Zhang ◽  
Junxue Ren ◽  
Changfeng Yao ◽  
Yuan Yuan
Keyword(s):  
Surface Integrity ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Test Results ◽  
Relational Analysis ◽  
Optimum Cutting ◽  
Grey Relational Grade ◽  
Grey Relational

This paper studied an effective method based on Taguchi's method with the grey relational analysis, focusing on the optimization of milling parameters on surface integrity in milling TB6 alloy. The grey relational grade that is derived from the grey relational analysis is mainly used to determine the optimum cutting process operations with multiple performance characteristics. Specifically, surface roughness (Ra), hardness, and residual stress were important characteristics in surface integrity of milling TB6 alloy. Based on the combination of these multiple performance characteristics, the feed per tooth, cutting speed, and depth of cut were optimized in this study. Additionally, the analysis of variance (ANOVA) was also applied to determine the most significant factor for the surface integrity of milling TB6 alloy according to the contribution of the ANOVA, and the most significant factor is the cutting speed in this paper. Based on the analysis, the experimental test results have been improved prominently through the grey relational analysis. Hence this method can be an effective approach to enhance the surface integrity of milling TB6 alloy.

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.

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.

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.

Improvement in the performance with less stiff air layer formation around the rubber tube-pasted grinding wheel

2019 ◽  
Vol 233 (15) ◽  
pp. 5175-5189 ◽  
Author(s):  
Spandan Guha ◽  
Partha Protim Das ◽  
Shankar Chakraborty
Keyword(s):  
Cutting Speed ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Grinding Wheel ◽  
Rubber Tube ◽  
Layer Formation ◽  
Relational Analysis ◽  
Grinding Performance ◽  
Roughness Amplitude ◽  
Grey Relational

In the grinding operation, a stiff layer of air gets formed around the periphery of the grinding wheel that causes deterioration of its performance. In the present work, in order to restrict the generation of stiff air layer around the periphery of the grinding wheel, a rubber tube is pasted on its surface to improve the grinding performance. An experimental investigation is carried out with low alloy steel as the work material. Taguchi's L9 orthogonal array is considered for the design of experiments while taking cutting speed, depth of cut, and type of the cutting fluid as the input grinding parameters. A comparative analysis using rubber tube-pasted grinding wheel and normal grinding wheel reveals that the developed wheel significantly improves the grinding performance with respect to surface roughness, amplitude of vibration and grinding ratio, as compared to the normal wheel. Moreover, grey relational analysis aided with fuzzy logic is applied in the experimental results to derive the optimal combination of process parameters for further enhancement of the grinding performance. Finally, analysis of variance results identify cutting speed as the most significant parameter while grinding with normal wheel, whereas depth of cut appears to be the most important parameter while machining with rubber tube-pasted grinding wheel.

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