An Experimental Analysis of Surface Roughness

Transcription

1 An Experimental Analysis of Surface Roughness P.Pravinkumar, M.Manikandan, C.Ravindiran Department of Mechanical Engineering, Sasurie college of engineering, Tirupur, Tamilnadu ABSTRACT The increase of customer needs for quality in metal cutting has driven the metal cutting industry to continuously improve quality of metal cutting processes. With in these metals cutting processes, the CNC turning process in one of the most fundamental metal removal operations used in the modern manufacturing industries. It is an important parameter in the highly Automated Manufacturing engineering industries which has significant influence on the performance of mechanical parts and products. This work focuses on developing an empirical model for the prediction of surface roughness in CNC turning. The following machining parameters are considered for deriving the new model: Tool Material, Work Material, Feed, Spindle speed and Depth of cut. The existing methods used for predicting the surface roughness value are only data mining techniques, computational neural network techniques and application of Taguchi techniques. This paper presents a new algorithm to establish a statistical model for predicting the surface roughness value, which is a simple monogram like procedure. 1.INTRODUCTION 1.1 METAL CUTTING Metal cutting involving metal through machining operations. Machining traditionally takes place on lathes, drill presses, and milling machines with the use of various cutting tools. There are many machines that have been designed to perform specific types of machining operations. In a modern machine shop, most of these machines would be computer controlled (numerically controlled) and capable of running automatically according to a program set by the operator. 1.2 LATHE A machine for shaping the work piece by gripping it in a holding device and rotating it under power against a suitable cutting tool for turning, facing, threading, drilling, and other operations. 2. COMPUTER NUMERIC CONTROL CNC stands for Computer Numerical Control and has been since the early 1970 s Prior to this, it was 63

2 called NC, for Numerical control. Machining processes that have traditionally been done on conventional lathe that are possible with CNC turning centers include all kinds of turning operations like facing, boring, turning, grooving, knurling, and threading. A third benefit offered by most forms of CNC machine tools is flexibility. Since these machines are run from programs, running a different workpiece is almost as easy as loading a different program. Once a program has been verified and executed for one production run, it can be easily recalled the next time the workpiece is to be run. This leads to yet another benefit, fast change-overs. Since these machines are very easy to setup and run, and since programs can be easily loaded, they allow very short setup time. This is imperative with today s just-in-time product requirements. 2.1 Motion control the heart of CNC: The most basic function of any CNC machine is automatic, precise, and consistent motion control. Rather than applying completely mechanical devices to cause motion as is required on most conventional machine tools, CNC machine allow motion control in a revolutionary manner. All forms of CNC equipment have two or more directions of motion, called axes. These axes can be precisely and automatically positioned along their lengths of travel. The two most common axis types are linear (driven along a straight path) and rotary (driven along a circular path). 2.2 Surface Roughness Surface roughness is the measure if the finer surface irregularities in the surface texture. These are the result of the manufacturing process employed to create the surface. Surface roughness Ra is rated as the arithmetic average deviation of the surface valleys and peaks expressed in micrometers. ISO standards use the term CLA (Center Line Average). Both are interpreted identical. The Measuring Instruments are Optical Methods, Microscopes, Optical Profilers, Scatterometry, Electron/Ion Beam Methods, Mechanical Profilers. 3. SURFACE ROUGHNESS TERMINOLOGY AND AFFECTING PARAMETERS The quality of machined surface is characterized by the accuracy of its manufacture with respect to the dimensions specified by the designer. Every machining operation leaves characteristic evidence on the machined surface. This evidence in the form of finely spaced micro irregularities left by the cutting tool. Each type of cutting tool leaves its own individual pattern which therefore can be identified. This pattern is known as surface finish or surface roughness. 64

3 3.1 Factors affecting the surface finish Whenever two machined surfaces come in contact with one another the quality of the mating parts plays an important role in the performance and wear of the mating parts. The height, shape, arrangement and direction of these surface irregularities on the workpiece depend upon a number of factors such as: a) The machining variables which include a. Cutting speed b. Feed, and c. Depth of cut. b) The tool Geometry The design and geometry of the cutting tool also plays a vital role in determining the quality of the surface. Some geometric factors which affect achieved surface finish include: Nose radius Rake Angle Side cutting edge angel, and Cutting edge. Workpieces and tool material combination and their mechanical properties Quality and type of the machine tool used, Auxiliary tooling. And lubricant used, and 4. EXPERIMENTAL ANALYSIS Since turning is the primary operation in most of the production processes in the industry, Surface finish of the turned component has greater influence on the quality of the product. The present work aims to predict the cutting parameters that influence to surface roughness value using a combined approach of Multiple Quadratic Interpolation (MQI) and optimization technique. 4.1 Experimental works The screening experiments examined the impact of the following parameters on surface roughness (Ra) in finish truing: Feed (F) Spindle Speed (N) Depth of Cut (D) In this experiment work piece material and tool material are fixed. Work piece material: En24 65

4 Tool Material: Tungsten Carbide (nose radius 0.4) The varying parameters are feed, spindle speed and depth of cut. Feed varying from 0.1 mm/rev to 0.15 mm/rev, Spindle speed varying from 2200 rpm to 2800 rpm, and depth of cut varying from 0.1mm to 0.3 mm. The above said data are considered by referring standard data book and operator s experience. Table 4.1 Experimental Cutting Parameters Feed (MM/rev Speed (RPM) Depth of Cut (mm) Minimum Average Maximum From the above said varying parameters a test chart is prepared for various combinations. This test chart is used for conducting the experiment in CNC turning center. During the course of operation cutting tool the insert was changed for each 9 component. The following diagram shows the dimensional details of the machined component. 66

5 Table 4.2 Experimental chart S no N F D Ra Where, N = speed in RPM, F = feed in mm/rev, D = depth of cut in mm, Ra = roughness value in µm 4.2 Organizing the data The surface roughness value is measured for each component. The surface roughness data of the components were collected with surface profilometer Mitutoyo Surface Tester. Three measurements are taken along the component axis Table 4.3 Feed Matrix 67

6 N = 2200 D = 0.1 N = 2200 D = 0.1 N = 2200 D = 0.1 F F F Ra Ra Ra Range = 0.86 Range = 0.92 Range = 0.89 N = 2500 D = 0.1 N = 2500 D = 0.1 N = 2500 D = 0.3 F F F Ra Ra Ra Range = 0.86 Range = 0.84 Range = 0.86 N = 2800 D = 0.1 N = 2800 D = 0.2 N = 2800 D = 0.2 F F F Ra Ra Ra Range = 0.93 Range = 0.82 Range = 0.57 The first element of 3x3 matrix having the Ra value for various Feed values by taking RPM = 2200 and Depth of cut = 0.1 as constant value. Similar way all the elements of the matrix are constructed. The range value of the each elements of the matrix indicates the difference between maximum and minimum Ra value. Table 4.4: RPM Matrix F =0.1 D = 0.1 F =0.1 D = 0.2 F =0.1 D = 0.3 N N N Ra Ra Ra Range = 0.02 Range = 0.02 Range = 0.2 F =0.125 D = 0.1 F =0.1 D = 0.2 F =0.125 D = 0.3 N N N Ra Ra Ra Range = 0.04 Range = 0.02 Range = 0.04 F =0.15 D = 0.1 F =0.15 D = 0.2 F =0.15 D = 0.3 N N N Ra Ra Ra Range = 0.07 Range = 0.08 Range = 0.06 The first element of 3x3 matrix having the Ra value for various RPM values by taking F = 0.1 and Depth of cut = 0.1 as constant value. Similar way all the elements of the matrix are constructed. The range value of the each elements of the matrix indicates the difference between maximum and minimum Ra value Table 4.5: Depth of cut Matrix 68

7 N =2200 F = 0.1 N =2200 F = 0.1 N =2200 F = 0.1 D D D Ra Ra Ra Range = 0.08 Range = 0.02 Range = 0.09 N =2200 F = 0.1 N =2200 F = 0.1 N =2200 F = 0.1 D D D Ra Ra Ra Range = 0.01 Range = 0.05 Range = 0.02 N =2200 F = 0.1 N =2200 F = 0.1 N =2200 F = 0.1 D D D Ra Ra Ra Range = 0.22 Range = 0.04 Range = 0.15 The first element of 3x3 matrix having the Ra value for various Depth of cut values by taking RPM = 2200 and Feed = 0.1 as constant value. Similar way all the elements of the matrix are constructed. The range value of the each elements of the matrix indicates the difference between maximum and minimum Ra value. 4.3 Multiple quadratic interpolation Incident matrices were prepared or the following combination (N,Ra),(D,Ra) and (F,Ra). From these matrices computed range values are Table 4.6: Incident matrices MATRIX RANGE N Ra D Ra F Ra Feed and roughness value varies remarkably then the order combinations combination. Quadratic fit is obtained for feed and roughness value. From the combination influencing nine quadratic equations were listed. F1= x 10-3 Ra x 10-2 Ra x10-2 F2= x 10-3 Ra x 10-2 Ra x10-2 F3= x 10-2 Ra x 10-2 Ra x10-2 F4= x 10-3 Ra x 10-2 Ra x10-2 F5= x 10-2 Ra x 10-2 Ra x10-2 F6= x 10-3 Ra x 10-2 Ra x10-2 F7= x 10-3 Ra x 10-2 Ra x10-2 F8= x 10-2 Ra x 10-2 Ra x10-2 F9= Ra Ra

8 For the particular Ra value nine sets of cutting combination were obtained. From the obtained combination of values, taking speed in X co-ordinate, Depth of cut in Y co- ordinate and Feed in Z co- ordinate in the Cartesian space, a 3D surface is fitted over the computed nine points. The resultant surface is the MQI surface for the particular Ra value. It can interpolate the intermediate combination of X, Y, Z values. To built the MQI surface, three quadratic cross sectional equations are derived from (P1, P2, P3), (P4, P5, P6), (P7, P8, P9). These equations are called primary quadratic equations, and the equations are constant for particular Ra value. The secondary quadratic equation is derived from target point. By substituting Speed and Depth of cut value in the secondary quadratic equation the required feed value can be calculated. Table 4.7: coordinates for MQI surface Coordinates X Y Z P F1 P F2 P F3 P F4 P F5 P F6 P F7 P F8 P F9 5. RESULT AND DISCUSSIONS From the experimental analysis Ra values are measured for 27 components with varying cutting parameters and plotted in the table 1. From the tabular values the following graphs are plotted for different combinations of parameters. 70

9 71

10 72

11 73

12 74

13 6. SOFTWARE DEVELOPMENT The MQI surface algorithm is explained in the previous chapter. The above said algorithm is converted into Visual basic 6.0 coding and MQI surface analyzer is developed. It has three main modules namely: 1. Interp 2. Contour 3. Invplot 6.1 INTERP MODULE In interp module the required combination of cutting parameters for particular for Ra value is being calculated. In this module interactive graphics box is present to interpolate the cutting parameters. The graphics present in this box is the top view of MQI Surface for the required Ra value. From this graphical box n number of parameters can be interpolated. 75

14 6.2 CONTOUR MODULE The above figure shows the screen shot of contour module. The top view of the response surface is shown in this plot. The feed distribution is plotted with various colors. Feed distribution color legend is provided for identify the feed value in the surface. 6.3 INVPLOT MODULE The screen shot shows the invplot module of the software. This module is used to predict the Ra value from the cutting parameters. This module ranges Ra value from 0.95 to 2 microns. Most promisising values are plotted in dark region. 76

15 7. CONCLUSION The MQI approach to study the impact of turning parameters on surface roughness was presented. It featured the following contributions. The depth of cut does not impact the surface roughness in the studied range, which could be used to improve productivity. Feed has a significant impact on the observed surface roughness. A systematic approach was provided to design and analyze the experiments, which is able to reduce the cost and time of experiments and to utilize the data obtained to the maximum extended. The five components are machined using randomly selected cutting parameters. The roughness for the same combination was computed using MQI software and the roughness was measured for five experimental components the resultant value observed with 5% of error. 77

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