Parametric optimization of cutting in turning operation using Taguchi method (original) (raw)
Related papers
2014
This project is based upon the study which means it is derived from experiment and observation rather than theory. For the fulfilment of objective our first motive is selection of cutting tool & work tool material selection of various process and performance parameters after parameterssss selection aims to study various techniques for the optimization for that purpose literature review and industrial survey is conducted. The objective of this study was to utilize Taguchi methods to optimize surface roughness in turning mild steel, EN-8 and EN-31. The turning parameters evaluated are cutting speed of 200, 250, and 300 m/min, feed rate of 0.08, 0.12 and 0.15 mm/rev, depth of cut of 0.5 mm and tool grades of TN60, TP0500 and TT8020, each at three levels. The experiment was designed and carried out on the basis of standard L9 Taguchi orthogonal array. The results show that the Taguchi method is suitable to solve the stated problem with minimum number of trials as compared with full factorial design.
In the modern high-tech world the accuracy and finishing of a job are very important. In the present study the control parameters of a cast iron specimen undergoing turning operation are optimized so as to obtain minimum surface roughness. The parameters most responsible for surface roughness are identified and their working ranges are set. These parameters are spindle speed, feed rate and depth of cut. Experiments are conducted using parameter combinations obtained by Taguchi's L-9 orthogonal array and corresponding surface roughness are noted. S/N ratio calculations are done to find the significance order of the control parameters. Next analysis of variance (ANOVA) verifies the working ranges of the control parameters and their order of significance.
Surface quality is one of the specified customer requirements for machined parts. There are many parameters that have an effect on surface roughness, but those are difficult to quantify adequately. In finish turning operation many parameters such as cutting speed, feed rate, and depth of cut are known to have a large impact on surface quality. In order to enable manufacturers to maximize their gains from utilizing hard turning, an accurate model of the process must be constructed. Several statistical modeling techniques have been used to generate models including regression and Taguchi methods. In this study, an attempt has been made to generate a surface roughness prediction model and optimize the process parameters Genetic algorithms (GA). Future directions and implications for manufacturers in regard to generation of an robust and efficient machining process model is discussed.
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.
Quality is the prime requirement for most of the customers and hence it is always a challenging and upcoming task in industries. This work focus on Surface Roughness produced in hard turning process on Lathe. The process of hard turning is done on AISI 1040 Steel material under dry conditions using coated Carbide Inserts and High Speed Steel (HSS) Tools. Spindle Speed and Feed are chosen as control factors. The control factors are adopted to analyze significance and contribution on the Surface Roughness of the machined parts. Taguchi methodology based on Orthogonal Arrays (OA) is used to Design the Experiments. Signal-to-noise Ratio (S/N ratio) of the generated Roughness values is used to evaluate the optimal machining parameter combinations. Later Analysis of Variance (ANOVA) is used to analyze the influences and contribution of the machining parameters on the Roughness values based on F-Statistic Test. Regression Model analysis was developed for predicting the Average Surface Roughness (Ra) as a function of Speed and Feed. Confirmation experiments are yielding an error of max 8.55% and 0.46% in Regression, while machining with Carbide and HSS tools respectively.
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.
Quality is inversely proportion to variability. In the other words as variability reduces, Quality improves. This approach has been used in this work. In the present work variability in the dimension of the manufactured part has been reduced. Reduction in the surface roughness as well as tolerance is the basic aim of this work. The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface finish) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes the turning process is one of the most fundamental cutting processes used in the manufacturing industry. Surface finish and dimensional tolerance, are used to determine and evaluate the quality of a product, are two of the major quality attributes of a turned product. The project work has been carried out at Neeraj Industries, Badli Industrial Area, Delhi in which the optimization of input parameter has been done for improvement of quality of the product in turning operation on CNC machine. Feed Rate, Spindle speed & Depth of cut are taken as the input variables and the dimensional tolerances and the surface roughness are taken as quality output. In the reduction of variation of performance characteristics and quality measures, Taguchi approach is very useful in the design of experiments. In the present work L9 Array has been used in design of experiment for optimization of input parameters. This project attempts to introduce and thus verifies experimentally as to how the Taguchi parameter design could be used in identifying the significant processing parameters and optimizing the surface roughness of the turning operation. There are two purposes of this research .The first is to demonstrate a systematic approach of using Taguchi parameter design of process control of individual CNC turning machine.The second is to demonstrate the use of Taguchi parameter design in order to identify the optimum surface roughness and dimensional tolerance performance with a particular combination of cutting parameters in a CNC turning operation.The present work shows that the spindle speed is key factor for minimizing the dimensional variation and feed rate is most effective input parameter for minimizing the surface roughness.
Parameter Optimisation Using CNC Lathe Machining
International Journal of Advance Research, Ideas and Innovations in Technology, 2017
In today’s manufacturing systems most of the time manufacturers, for retaining their position in the market competition, depends on manufacturing engineers and various production personnel in the industry. To get benefits of quick and effective setups while developments of a manufacturing processes for new products. For the manufacturing challenges, the Taguchi parameter optimization method is a powerful and efficient tool for quality and performance output. This thesis discusses on the parameter optimization of CNC lathe machining for surface roughness using the Taguchi method, where surface roughness generated during machining. In the parameter optimization, the parameters are cutting speed, feed, and depth of cut. After selecting parameters turning on CNC lathe is to be done and selected orthogonal array and parameters used for the optimum set of combined controlled parameters for surface roughness. Into this combination of parameters selected for minimum surface roughness value ...
Abstract— Turning is one of the most important machining processes used in various industrial applications. Usually the quality of finished part in turning operation is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry. The objective of this study is to model and optimize machining parameters and tool geometry in order to improve the surface roughness in turning operation of AISI1045 steel. Machining parameters and tool geometry are considered as input parameters. In turn, the surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach. Keywords: machining parameters; tool geometry; signal to noise, Taguchi method, analysis of variance
Materials & Design, 2007
Nickel-base superalloy Inconel 718 is a high-strength, thermal-resistant. Because of its excellent mechanical properties, it plays an important part in recent years in aerospace, petroleum and nuclear energy industries. Due to the extreme toughness and work hardening characteristic of the alloy, the problem of machining Inconel 718 is one of ever-increasing magnitude. This investigation optimized the machining characteristics of Inconel 718 bars using tungsten carbide and cermet cutting tools. The approach is based on Taguchi method, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) are employed to study the performance characteristics in turning operations. The roundness and flank wear of the ultrasonically and conventionally machined workpieces were measured and compared.