Optimization of CNC Turning Process Parameters for Prediction of Surface Roughness Through Taguchi ’ S Parametric Design Approach (original) (raw)
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Analysis of Surface Roughness with Different Cutting Parameters in Turning: A Review
— This paper is all about the steps and procedures used to optimize turning parameters using Taguchi's design of experiment. An attempt is made to review the literature on optimizing machining parameters in turning processes. In this study, analysis will be done by process parameter like cutting speed, feed rate and depth of cut based on surface roughness in finish turning of work piece material with carbide tool having different rack angle. The surface roughness will measure at the end of useful tool life. The combine effects of the process parameters on performance characteristics will investigating using ANOVA and will normality testing optimization technique will help to optimize the process parameters.
Experimental Investigation and Parametric Studies of Surface Roughness Analysis in CNC Turning
The modern machining industries are focused on achieving high quality, in terms of part/component accuracy, surface finish, high production rate and increase in product life. Surface roughness of machined components has received serious attention of researchers for many years. It has been an important design feature and quality measure in machining process. There are a large number of parameters which affect the surface roughness. The typical controllable parameters for the CNC machines include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to determine the most significant parameter for required output. Many techniques are used for optimization of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant parameter. The present work is therefore in a direction to integrate effect of various parameters which affect the surface roughness. This paper investigates the parameters affecting the surface roughness and / or material removal rate with CNC turning process studied by researchers. It also discusses some other parameters such as cutting force and power consumption in different conditions. Keywords: Surface Roughness, CNC Turning, Parametric studies, Optimization
OPTIMIZATION OF CUTTING PARAMETERS FOR SURFACE ROUGHNESS IN TURNING
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The optimized cutting parameters are very important to control the required surface quality. In the present study, Taguchi method is used to find the optimal cutting parameters for surface roughness (Ra) in turning. The L-18 orthogonal array, the signal-to-noise ratio & analysis of variance are employed to study the performance characteristics in turning operations of AISI-410 steel bars using TiN coated inserts. The four cutting parameters namely, insert radius, depth of cut, feed & cutting speed are optimized with considerations of surface roughness. The analysis reveals that feed rate has the most significant effect on Ra.
Literature Review on Optimization of Surface Roughness during Turning Operation
The mechanical manufacturing industries are regularly challenged for achieving higher productivity and high quality products in order to remain competitive. The desired shape, size and finished ferrous and non ferrous materials are conventionally produced through turning the preformed blanks with the help of cutting tools that moved past the work piece in a machine tool. Among various cutting processes, turning process is one of the most fundamental and most applied metal removal operations in a real manufacturing environment. The surface roughness of the machined parts is one of the most significant product quality characteristic which refers to the deviation from the nominal surface. Surface roughness plays a vital role in many applications such as precision fits, fastener holes, aesthetic requirements and parts subject to fatigue loads. Surface roughness imposes one of the most significant constraints for the selection of cutting parameters and machine tools in development of a process. Surface finish in turning has been found to be influenced in varying amounts by a number of factors such as feed rate, work material characteristics, work hardness, unstable built-up edge, cutting speed, depth of cut, cutting time, tool nose radius and tool cutting edge angles, stability of machine tool and work piece setup, chatter, and use of cutting fluids.
Study the Effect of Cutting Conditions for turning process on the Machined Surface
2012
Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials. The matrix of test conditions included cutting speeds of the 16, 30, 45 and 60 m/min, feed rates of 0.17, 0.35 and 0.7 mm/rev while the depth of cut has been kept constant. The effect of cutting parameters on surface roughness is evaluated and t...
Productivity and the quality of the machined parts are the main challenges of metal cutting industry during turning process. Therefore cutting parameters must be chosen and optimize in such a way that the required surface quality can be controlled. Hence statistical design of experiments (DOE) and statistical/mathematical model are used extensively for optimize. The present investigation was carried out for effect of cutting parameters (cutting speed, depth of cut and feed) In turning off mild steel and aluminum to achieve better surface finish and to reduce power requirement by reducing the cutting forces involved in machining. The experimental layout was designed based on the 2^k factorial techniques and analysis of variance (ANOVA) was performed to identify the effect of cutting parameters on surface finish and cutting forces are developed by using multiple regression analysis. The coefficients were calculated by using regression analysis and the model is constructed. The model is tested for its adequacy by using 95% confidence level. By using the mathematical model the main and interaction effects of various process parameters on turning was studied.
ANALYSIS AND OPTIMIZATION OF SURFACE ROUGHNESS IN DRY TURNING OPERATION OF MILD STEEL
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In all the machining operations, surface finish is an essential characteristic of concern for many of the turned workpieces. So it is very important for getting the required surface quality controlled to have the choice of optimized cutting factors. In the present experimental work the optimization of cutting factors (depth of cut, feed rate, spindle speed) has been done in dry turning of mild steel of (0.21% C). In the present work, turning operations were carried out on mild steel by high speed steel cutting tool in dry condition and the combination of the optimal levels of the factors was obtained to get the lowest surface roughness. The Analysis of Variance (ANOVA) and Signal-to-Noise ratio were used to study the performance characteristics in turning operation. The results of the analysis show that depth of cut was the only factor found to be significant. Results obtained by Taguchi method match closely with ANOVA and depth of cut is most influencing parameter. The predicted values and measured values are fairly close, which depicts that the developed model can be effectively used to predict the surface roughness in the turning operation.
The manufacturing industries are very much concerned about the quality of their products. They are focused on producing high quality products in time at minimum cost. Surface finish is one of the crucial performance parameters that have to be controlled within suitable limits for a particular process. Surface roughness of machined components has received serious attention of Researchers for many years. It has been an important design feature and quality measure in machining process. There are a large number of parameters which affect the surface roughness. These include cutting tool variables, work piece material variables, cutting conditions etc. Therefore, prediction or monitoring of the surface roughness of machined components has been challenging and unexplored area of research The present work is therefore in a direction to integrate effect of various parameters which effect the surface roughness. Experiments were carried out with the help of factorial method of design of experiment (DOE) approach to study the impact of turning parameters on the roughness of turned surfaces. A mathematical model was formulated to predict the effect of machining parameters on surface roughness of a machined work piece. Model was validated with the experimental data and the reported data of other researchers. Further parametric investigations were carried out to predict the effect of various parameters on the surface research Keywords: Surface Roughness, Design of Experiments, CNC Turning, Surface Roughness, factorial method,
Evaluation of Surface Roughness of Mild Steel Component Turned using Multi Tool Turning Method
The prime attempt in any production process is to produce an acceptable component at the minimum possible cost without affecting the surface finish or overall quality of the component. In order to achieve this objective in metal cutting or metal machining, many attempts have been made in several different ways; such as optimizing the tool life in order to minimize the production cost, maximizing the production rate to reduce the production cost, etc. but no single effort has been found fully successful because of the numbers of complexities involved in the process. For example, if cutting speed is reduced in order to enhance the tool life, the metal removal rate is also reduced and therefore, the production cost increased. A similar effect is observed if the efforts have been made to increase the production rate by increasing the cutting speed, feed and depth of cut, if we increase the above cutting parameters it will affect the surface quality adversely. A balance is therefore required to be stuck between the above parameters or there should be a new technique which will enhance the productivity without affecting the surface finish of the component. One such technique is introduced in this research work in which two single point cutting tools works simultaneously on the single work piece for improving the production rate at optimum surface finish.