Measurement of nose radius wear in turning tools from a single 2D image using machine vision

Flank and crater wear in cutting tools have been extensively studied in the past using direct and indirect methods. In finish and hard turning, however, nose radius wear plays a greater role in determining the surface quality of the finished product. This is due to the direct interaction between the tool nose area and the workpiece during machining. Nose radius wear can be measured from the 2D profiles of the tool before and after machining using a vision method. This approach, however, requires two images of cutting tools to be recorded and precisely aligned before subtraction. This work proposes a new method of measuring nose wear area from a single 2D image of the worn tool. The nose profile is extracted in the Cartesian coordinates and converted to a polar-radius plot. From the plot, the nose wear area is determined by simple subtraction.     

In-cycle monitoring of tool nose wear and surface roughness of turned parts using machine vision

Tool wear has been extensively studied in the past due to its effect on the surface quality of the finished product. Vision-based systems using a CCD camera are increasingly being used for measurement of tool wear due to their numerous advantages compared to indirect methods. Most research into tool wear monitoring using vision systems focusses on off-line measurement of wear. The effect of wear on surface roughness of the workpiece is also studied by measuring the roughness off-line using mechanical stylus methods. In this work, a vision system using a CCD camera and backlight was developed to measure the surface roughness of the turned part without removing it from the machine in-between cutting processes, i.e. in-cycle. An algorithm developed in previous work was used to automatically correct tool misalignment using the images and measure the nose wear area. The surface roughness of turned parts measured using the machine vision system was verified using the mechanical stylus method. The nose wear was measured for different feed rates and its effect on the surface roughness of the turned part was studied. The results showed that surface roughness initially decreased as the machining time of the tool increased due to increasing nose wear and then increased when notch wear occurred.     

Improved measure of workpiece surface deterioration during turning using non-contact vision method

The surface finish quality of a machined workpiece is commonly measured using the average roughness parameter, R_a. This parameter, however, is insensitive to the lateral changes undergone by the surface in the feed direction as a consequence of tool wear. In this work, the effectiveness of four methods of workpiece surface analysis, namely autocorrelation, cross-correlation, and two new methods, called lateral material shift (LMS) ratio and profile slope ratio (PSR) analyses are investigated. Dry machining experiments were carried out on 316 stainless steel. Images of tool nose and workpiece profiles were captured using digital camera, and the edges were extracted using sub-pixel edge detection. In the autocorrelation approach, each workpiece profile was correlated with a shifted version of the same profile. In the cross-correlation approach, the workpiece profiles at different stages of machining were correlated with a reference profile generated using the unworn tool edge. In the LMS ratio method, the material shift ratios were determined from each waveform on the workpiece profile at various stages of tool wear, while in the PSR method the slopes at the right and left part of the waveform were compared. Among the four methods, the LMS ratio method produced the best correlation with tool flank wear with the maximum R-squared value of 0.9461, while average roughness R_a showed no correlation at all with both major and nose flank wear.     

Simulation and measurement of surface roughness via grey scale image of tool in finish turning

Study on the surface roughness of specimen is a significant field of research because this parameter affects the performance of the machined parts. Meanwhile, the evaluation of surface roughness of specimens using a vision system via the images captured from the specimen is an interesting method which is widely used. Although the effect of flank and crater wear has been investigated extensively in the past researches on surface profiles, some reports indicated that, in finish turning, the nose radius wear has a greater effect on the surface profile of specimen. Although, vibration can affect the surface profile of a specimen in rough turning, the final surface profile in the product used is usually shaped by finish turning that may not be affected by vibration using the robust machine tool. In this work, a machine vision was used to capture the images of the tool tip in-cycle. The 2-D images of the nose area of tool tips were used to simulate the surface profile of specimens in finish turning. The simulated images of specimens in a range of machining condition were detected using the algorithm of this work. The results showed that this method can be used successfully to simulate and evaluate the surface profile of a specimen in finish lathe machining as a fingerprint of the tool tip. This method can be used for forecasting the final surface profile in order to control the performance of products.     

Modeling and optimization of hard turning of X38CrMoV5-1 steel with CBN tool: Machining parameters effects on flank wear and surface roughness

The present study, aims to investigate, under turning conditions of hardened AISI H11 (X38CrMoV5-1), the effects of cutting parameters on flank wear (VB) and surface roughness (Ra) using CBN tool. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters, namely cutting speed, feed rate and cutting time on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA). Optimal cutting conditions for each performance level are established and the relationship between the variables and the technological parameters is determined using a quadratic regression model. The results show that the flank wear is influenced principally by the cutting time and in the second level by the cutting speed. Also, it is that indicated that the feed rate is the dominant factor affecting workpiece surface roughness.     

Influence of the tool corner radius on the tool wear and process forces during hard turning

Hard turning has become an alternative machining process for grinding processes of hardened steels. One challenge during hard turning is the increasing wear during the operation time of the tool and the hereby influenced workpiece surface and subsurface properties. This causes unfavorable changes of the microstructure and residual stress state or rather damages of the subsurface. Important factors are the contact conditions between the tool and the workpiece. The width of flank wear land influences the size of the passive force significantly. This has a direct impact on the subsurface properties of the workpiece. One solution is to modify the contact conditions and thereby the specific mechanical and thermal loads that are applied to the tool as well as to the workpiece. This article presents an experimental approach of modified corner radius geometry of cutting tools for hard turning processes. Hereby, the size and direction of the contact length of the cutting edge are adjusted as well as the load impact during machining. The aim is to reduce the tool wear performance. The results show the potential of the load-specific tool design concerning the tool wear and the workpiece subsurface properties. Furthermore, a new approach for predicting the process forces during hard turning is presented.     

In-cycle detection of built-up edge (BUE) from 2-D images of cutting tools using machine vision

The built-up edge (BUE) phenomenon that appears under certain machining condition, such as low-to-moderate cutting speed, high depth of cut, dry cutting, cutting of ductile material, etc. is known to have a major effect on the surface quality of the finished workpiece. In the published literature, BUE has been measured using scanning electron microscope and optical microscopes to study its effect on tool life and surface quality. Such measurement methods are only applicable in off-the-machine inspection. Since the BUE extending beyond the tool nose alters the tool geometry and, thus, influences the workpiece roughness profile, detection of BUE outside the nose region is important. This research proposes a new method for detecting BUE from 2-D images of the nose region of the tool using a machine vision approach. Two methods of determining the BUE area are proposed—the subtraction method and polar-radius transformation method. Application of both methods is successfully demonstrated using simulated and real cutting tool images.     

Effect of Flank Wear on the Topography of Machined Surfaces

The effect of flank wear on the topography of machined surfaces is investigated by studying its effect on the shape of the tool nose. For this purpose, turning experiments were performed to produce surfaces corresponding to different levels of flank wear. The distribution of flank wear at the tool nose during these experiments caused the nose radius to decrease, which when replicated on the machined surface resulted in narrower and deeper feedmarks. This change in the geometry of feedmarks was represented by the increase in the arithmetic average roughness of the surface profile heights.     

Analysis of residual stress and work-hardened profiles on Inconel 718 when face turning with large-nose radius tools

Surface integrity (SI) and, particularly, the residual stress profile, has a great influence on the fatigue life of machined aeronautical critical parts. Among the different cutting parameters that affect the final SI, tool geometry is one of the most important factors. In particular, tool nose radius determines the surface roughness, as well as the thermoplastic deformation of the workpiece. Indeed, the use of large tool nose radius in the industry enables (1) increasing the feed rate while keeping the roughness values below specifications and (2) reducing the influence of the tool wear in the surface roughness. Therefore, in this study, the influence of tool nose radius in the induced residual stress profile and work-hardened layer when face turning Inconel 718 is analysed for a cutting speed range between (30–70 m/min) and a feed rate range of (0.15–0.25 mm/rev). For this purpose, residual stress profiles and work-hardened layer were measured by x-ray diffraction method after machining with a 4 mm nose radius. Then, results have been compared against different tool nose radius studies carried out by other authors for the specified working conditions. Results revealed that residual stress profiles varied when machining with different nose radius for the studied range. In particular, the increase of the nose radius brought to a higher difference between surface tensile stress and subsurface compressive peak stress, which is attributed to an increase of the thermal effect. Moreover, thicker work-hardened layer (around 100 μm) was observed when machining with large-nose radius for the studied working conditions.     

Notch wear detection in cutting tools using gradient approach and polynomial fitting

Cutting tool wear is well known to affect the surface finish of a turned part. Various machine vision methods have been developed in the past to measure and quantify tool wear. The two most widely measured parameters in tool wear monitoring are flank wear and crater wear. Works carried out by several researchers recently have shown that notch wear has a more severe effect on the surface roughness compared to flank or crater wear. In this work, a novel gradient detection approach has been developed to detect the presence of micro-scale notches in the nose area of the cutting tool. This method is capable of detecting the location of the notch accurately from a single worn cutting tool image.     

激光超声复合切削硬质合金的刀具磨损及其对工件表面质量的影响

基于激光加热辅助切削和超声椭圆振动切削提出了激光超声复合切削加工工艺。采用聚晶立方氮化硼(PCBN)刀具对YG10硬质合金进行了常规切削,超声椭圆振动切削,激光加热辅助切削和激光超声复合切削对比试验。检测了刀具磨损量、刀具磨损形貌、工件表面粗糙度以及工件表面形貌,并通过扫描电镜(SEM)对刀具磨损区域进行了能谱分析,同时研究了激光超声复合切削硬质合金时PCBN刀具的磨损及其对工件表面质量的影响。最后,与常规切削、超声振动切削及激光加热辅助切削进行了对比试验。结果表明:激光超声复合切削时刀具使用寿命显著增加,加工后的工件表面粗糙度平均值分别降低了79%、60%和64%,且工件表面更加平整光滑。激光超声复合切削硬质合金时,PCBN刀具的前刀面磨损表现为平滑且均匀的月牙洼磨损,后刀面磨损表现为较窄的三角形磨损带和较浅的凹坑和划痕;刀具的失效机理主要为黏接磨损、氧化磨损和磨粒磨损的综合作用。     

A machine vision system for tool wear assessment

Automated tool condition monitoring is gaining considerable importance in the manufacturing industry. This can be attributed to the transformation of manufacturing systems from manually operated production machines to highly automated machining centres. Modern image processing techniques and machine vision systems can now enable direct tool wear measurement to be accomplished in-cycle. Such a system, characterized by its measurement flexibility, high spatial resolution and good accuracy, is presented here. The system consists of a fibre-optic light source to illuminate the tool and a CCD camera (used in conjunction with a high resolution video zoom microscope) to capture the reflected pattern. The extent of the flank wear land has been determined using both textural and gradient operators; a texture operator has been implemented in the final system.     

An experimental investigation of tool wear in electric discharge machining

In this study, the variations of geometrical tool wear characteristics – namely, edge and front wear – and machining performance outputs – namely, workpiece removal rate, tool wear rate, relative wear and workpiece surface roughness – were investigated with varying machining parameters. Experiments were conducted using steel workpieces and round copper tools with a kerosene dielectric under different dielectric flushing conditions (injection, suction and static), discharge currents and pulse durations. The experiments have shown that machining parameters and dielectric flushing conditions had a large effect on geometric tool wear characteristics and machining performance outputs. Additionally, published research on tool wear is presented in detail in this study.     

Effect of wedge angle on surface roughness in finish turning: analytical and experimental study

Most of the theoretical models for surface roughness in finish turning assume that the work piece surface profile is formed by the rounded tip of the tool nose. The effect of the straight flank section in the tool nose region on the surface roughness is usually neglected. In this work, the straight flank section is taken into account in order to predict the arithmetic average roughness R _a and root-mean-square roughness R _q more accurately. The analytical models for R _a and R _q are developed as a function of three parameters, namely feed rate, nose radius, and wedge angle. These models were verified using digital simulation method. The surface roughness determined using the new three-parameter models were compared with the existing two-parameter models that consider only the feed rate and nose radius. Decreasing wedge angle was found to lower the surface roughness significantly. An experiment was conducted to test the validity of the three-parameter model at different feed rates in real machining operation. The experimental results agreed more closely with the proposed three-parameter models compared to the two-parameter models.     

A study of tool wear using statistical analysis of metal-cutting acoustic emission

Many aspects of the interactions between cutting tools, workpiece material and the chips formed during machining that affect the wear and failure of the tool are not fully understood. The analysis of acoustic emission signals generated during machining has been proposed as a technique for studying both the fundamentals of the cutting process and tool wear and as a methodology for detecting tool wear and failure on line. A brief review of the theory of acoustic emission is presented. Acoustic emission data from reduced contact length machining experiments and tool flank wear tests are analyzed using distribution moments. The analysis shows that the skew and kurtosis of an assumed β distribution for the r.m.s. acoustic emission signal are sensitive to both the stick-slip transition for chip contact along the tool rake face and progressive tool wear on the flank of the cutting tool.     

The effect of cutting parameters and cutting tools on machining performance of carbon graphite material

Abstract

The present study focuses on the effects of cutting speed, feed rate and cutting tool material on the machining performance of carbon graphite material. Polycrystalline Diamond (PCD) cutting tools are used in machining experiments and its performance is compared with the tungsten carbide (WC) and Cubic Boron Nitride (CBN) tools. Machining performance criteria such as flank and nose wear and resulting surface topography and roughness of machined parts were studied. This study illustrates that feed rate and cutting tool material play a dominant role in the progressive wear of the cutting tool. The highest feed rate and cutting speed profoundly reduce the tool wear progression. The surface roughness and topography of specimens are remarkably influenced from the tool wear. Major differences are found in the wear mechanisms of PCD and WC and CBN cutting tools.     

Experimental investigation and performance analysis of cemented carbide inserts of different geometries using Taguchi based grey relational analysis

In this work, effect of machining parameters cutting speed, feed rate and depth of cut, geometrical parameters cutting insert shape, relief angle and nose radius were investigated and optimized using Taguchi based grey relational analysis. 18 ISO designated uncoated cemented carbide inserts of different geometries were used to turn practically used automotive axles to study the influence of variation in carbide inserts geometry. Performance measures viz., flank wear, surface roughness and material removal rate (MRR) were optimized using grey relational grade, based on the experiments designed using Taguchi’s Design of Experiments (DoE). A weighted grey relational grade is calculated to minimize flank wear and surface roughness and to maximize MRR. Analysis of variance shows that cutting insert shape is the prominent parameter followed by feed rate and depth of cut that contributes towards output responses. An experiment conducted with identified optimum condition shows a lower flank wear and surface roughness with higher MRR. The confirmation results obtained are confirmed by calculating confidence interval, which lies within the width of the interval.     

Measurement of flank wear on cyclotron-activated tools

A method using cyclotron-induced radioactivity in cemented carbide turning tools was used to measure flank wear. The radioactivity is induced only in the wear area and is induced to a depth of 240 μm. Some of the parameters governing the induction and measurement of radioactivity are discussed.As the machining proceeds, the radioactive material from the tools is worn away and the remaining activity is measured by γ ray counting. Some correlation studies showed that the decrease in radioactivity is proportional to the square of the flank wear value measured optically. Therefore the method is more sensitive than the optical method and also is non-subjective.The method does not affect the tool performance nor is it affected by machining conditions, so that the total radioactivity loss at the end of tool life is independent of machining parameters. It has also been shown to be completely safe under workshop conditions.     

The monitoring of flank wear on the CBN tool in the hard turning process

In precision hard turning, tool flank wear is one of the major factors contributing to the geometric error and thermal damage in a machined workpiece. Tool wear not only directly reduces the part geometry accuracy but also increases the cutting forces drastically. The change in cutting forces causes instability in the tool motion, and in turn, more inaccuracy. There are demands for reliably monitoring the progress of tool wear during a machining process to provide information for both correction of geometric errors and to guarantee the surface integrity of the workpiece. A new method for tool wear monitoring in precision hard turning is presented in this paper. The flank wear of a CBN tool is monitored by feature parameters extracted from the measured passive force, by the use of a force dynamometer. The feature parameters include the passive force level, the frequency energy and the accumulated cutting time. An ANN model was used to integrate these feature parameters in order to obtain more reliable and robust flank wear monitoring. Finally, the results from validation tests indicate that the developed monitoring system is robust and consistent for tool wear monitoring in precision hard turning.     

Modelling the effect of flank wear on machining thrust stability

This paper discusses an analytical assessment of the effect of cutting tool flank wear on machining stability along the thrust direction in a turning operation based on an analysis of frequency band root-mean-square (RMS) level of the accelerometer signals. The energy content of machining at the tool-tip/workpiece interface along the flank is represented by the RMS signal level, in comparison to the random vibration of the cantilever portion of the tool holder. The RMS signals measured from a tool-post accelerometer in stable machining with tool wear effect are calculated using the frequency band RMS method at the first natural frequency of the cantilever portion of the tool holder. Increasing flank wear results in increasing stability and decreasing RMS in the thrust direction in machining. For model validation, a series of machining experiments were performed under the condition of various flank wear/land widths, while the RMS signals from a tool-post accelerometer were collected and studied. It was found that theoretical predictions were shown to be in agreement with experimental results.