Comparison and Optimization of Machining Parameters by using Taguchi Method (original) (raw)
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IJERT-Comparison and Optimization of Machining Parameters by using Taguchi Method
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/comparison-and-optimization-of-machining-parameters-by-using-taguchi-method https://www.ijert.org/research/comparison-and-optimization-of-machining-parameters-by-using-taguchi-method-IJERTV3IS081061.pdf In this study, three different conditions of cutting fluids viz. dry, synthetic oil and vegetable based coconut oil cutting fluids were used to determine optimum conditions for cutting force, tool chip inter face temperature, material removal rate and surface roughness. Taguchi L9 orthogonal array design of experiment was used for the experiment plan. Cutting speed, feed rate, depth of cut and coconut oil based cutting fluid were considered as machining parameters. Response tables and main effects plots ratios were used to analyze the results. The optimum values were calculated by using regression equations and were found to be cutting force (fx)-27.93 kgf, cutting force (fy)-34 kgf, tool inter face temperature-42.28 0 C , material removal rate-0.1175 gms/sec and surface roughness was 29.03 µ .
Optimization of the Cutting Fluids and Parameters Using Taguchi and ANOVA in Milling
2010
In this study, two different vegetable based cutting fluids developed from refined canola and sunflower oil and a commercial type semi-synthetic cutting fluid were carried out to determine optimum conditions for tool wear and forces during milling of AISI 304 austenitic stainless steel. Taguchi L 9 (3 4) orthogonal array was used for the experiment plan. Cutting speed, feed rate, depth of cut and types of cutting fluids were considered as machining parameters. Mathematical models for cutting parameters and cutting fluids were obtained from regression analyses to predict values of tool wear and forces. S/N ratio and ANOVA analyses were also performed to obtain for significant parameters influencing tool wear and forces.
International Journal of Mechanical Engineering Technologies and Applications, 2020
The result of a turning process is strongly influenced by the process parameters that could result in the product to be unacceptable. The cutting parameters may be determined according to the material hardness and roughness of the workpiece surface. The purpose of this paper is to investigate the effects of cutting speed and feed rate on surface roughness and vibration. In Taguchi method, the number of experiments is reduced by orthogonal arrays while the effects of uncontrollable factors are also also reduced. The Taguchi method is used to reduce track, experimental time and production cost. Simple and precise are the most benefits of this method. Unstable vibrations in machining operations, known as chats, can cause damage to tools, workpieces, and machine tools. Cutting force is found to be the most dominant factor affecting surface roughness.
Selection of Appropriate Cutting Parameters to Achive Optimum Surface Roughness with Taguchi
International Journal of Scientific and Technological Research, 2019
In this study, AISI 1040 steel, which has a hardness of 41 HRc which is frequently used in the field of automotive industry, has been turned with a CNC lathe. The test list was made by creating L9 orthogonal array in the cutting speed, cutting depth and feed parameters with Taguchi method. The work pieces are machined on CNC lathes using Ti+Al2O3+TiN coated carbide inserts. The experiments were done with dry conditions without any coolant. According to the results of the experiments, the surface roughness values (Ra) were examined. With this method signal/noise (S/N) ratio is determined and the results of the experiments in the three parameters of the surface roughness of the most significant effect is reached from the results of feed. Finally, Taguchi control experiments were applied. The obtained results show that the Taguchi estimate is about 90% accurate. In the analysis of variance, the confidence level of progress was 95%.
Optimization of machining parameters in face milling using multi-objective Taguchi technique
In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique.
A Review-Optimization of Machining Parameters in Turning Operation by Employing Taguchi Method
International Journal for Scientific Research and Development, 2015
This paper deals with literature review on optimization of independent process parameters like cutting speed, feed rate, depth of cut, tool nose radius, cutting environment, tool tip temperature, etc. which affect desired response parameters or characteristics like cutting forces, material removal rate, surface roughness, power consumption . Different optimizing tools or techniques like Taguchi’s design approach, Taguchi grey relational analysis, Analysis of variance (ANOVA) are reviewed to investigate their effectiveness in optimization and finding significant factors in turning operation.
SURFACE ROUGHNESS OPTIMIZATION IN END MILLING USING TAGUCHI METHOD AND ANOVA
In this paper, the Taguchi method has been applied to optimize the machining performance in terms of surface roughness of the product, with aluminum 6061 work piece. Three different types of cutting tools were used of which two were HSS and one was Carbide for experiment on a CNC End Mill. Taguchi's L9 orthogonal array is employed for the experimentation. The factors considered for experimentation and analysis were spindle speed, feed rate, depth of cut and tool type. Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to analyze the effect of these milling parameters. The analysis results revealed that the spindle speed was the dominant factor affecting surface roughness. Confirmation test results showed that the Taguchi method was very successful in the optimization of machining parameters for minimum surface roughness.
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/assessment-of-cutting-parameters-for-optimization-of-material-removal-rate-in-face-milling-operation-taguchi-method-and-regression-analysis https://www.ijert.org/research/assessment-of-cutting-parameters-for-optimization-of-material-removal-rate-in-face-milling-operation-taguchi-method-and-regression-analysis-IJERTV2IS60449.pdf The present research work discusses about the application of Taguchi method and Regression Analysis for optimization of Material Removal Rate in machining of Gun metal with a HSS tool. The experiment was designed using Taguchi's experimental design technique. The cutting parameters selected are spindle speed, feed and depth of cut. The effect of cutting parameters on Material Removal Rate is investigated and the optimum cutting conditions for maximizing the Material Removal Rate is determined. Linear regression equation is developed with an objective to establish a correlation between the selected cutting parameters and Material Removal Rate. The predicted values are compared with experimental values and are found to be in good agreement. Depth of cut is found to be the most influencing factor affecting Material Removal Rate followed by spindle speed and feed.
Optimization to the parameters of abrasive flow machining by Taguchi method
Materials Today: Proceedings, 2018
This project summarizes the study of the parameters (Number of process cycles, Extrusion pressure and Abrasive concentration) and experimented variation used in Abrasive flow machining (AFM) for the surface finishing process and its optimization using Taguchi method. Abrasive flow machining (AFM) process is a most suitable non-conventional finishing process of internal passages of IC engine vehicles .Workpiece were machined by making all possible arrangements of these parameters on 3 levels which resulted into total of 27 workpiece which were machined to find the optimum value of parameters. Finally the results were verified using Taguchi method to find the optimum value of parameters. It has been found through the experiment that the optimum result is obtained when 'Number of cycles is equal to 6, Extrusion pressure is 15 bars and Abrasive concentration is 100gm', which shows that the percentage difference in surface roughness after machining is 26.42%. The result obtained shows that Taguchi designs recognize that not all the factors that causes variability can be controlled. These non-controllable factors are called noise factors. Taguchi designs try to identify controllable factors that can minimize the effects of noise factors.