Online tool condition monitoring in turning titanium (grade 5) using acoustic emission: modeling

This paper presents an online prediction of tool wear using acoustic emission (AE) in turning titanium (grade 5) with PVD-coated carbide tools. In the present work, the root mean square value of AE at the chip–tool contact was used to detect the progression of flank wear in carbide tools. In particular, the effect of cutting speed, feed, and depth of cut on tool wear has been investigated. The flank surface of the cutting tools used for machining tests was analyzed using energy-dispersive X-ray spectroscopy technique to determine the nature of wear. A mathematical model for the prediction of AE signal was developed using process parameters such as speed, feed, and depth of cut along with the progressive flank wear. A confirmation test was also conducted in order to verify the correctness of the model. Experimental results have shown that the AE signal in turning titanium alloy can be predicted with a reasonable accuracy within the range of process parameters considered in this study.     

The Application of an ANFIS and Grey System Method in Turning Tool-Failure Detection

The cutting process is a major material removal process; hence, it is important to search for ways of detecting tool failure. This paper describes the results of the application of an adaptive-network-based fuzzy inference system (ANFIS) for tool-failure detection in a single-point turning operation. In a turning operation, wear and failure of the tool are usually monitored by measuring cutting force, load current, vibration, acoustic emission (AE) and temperature. The AE signal and cutting force signal provide useful information concerning the tool-failure condition. Therefore, five input parameters of the combined signals (AE signal and cutting force signal) have been used in the ANFIS model to detect the tool state. In this model, we adopted three different types of membership function for analysis for ANFIS training and compared their differences regarding the accuracy rate of the tool-state detection. The result obtained for the successful classification of tool state with respect to only two classes (normal or failure) is very good. The results also indicate that a triangular MF and a generalised bell MF have a better rate of detection. We also applied grey relational analysis to determine the order of influence of the five cutting parameters on tool-state detection.     

Monitoring of hard turning using acoustic emission signal

Monitoring of tool wear during hard turning is essential. Many investigators have analyzed the acoustic emission (AE) signals generated during machining to understand the metal cutting process and for monitoring tool wear and failure. In the current study on hard turning, the skew and kurtosis parameters of the root mean square values of AE signal (AERMS) are used to monitor tool wear. The rubbing between the tool and the workpiece increases as the tool wear crosses a threshold, thereby shifting the mass of AERMS distribution to right, leading to a negative skew. The increased rubbing also led to a high kurtosis value in the AERMS distribution curve.     

Finite element modeling of 3D turning of titanium

The finite element modeling and experimental validation of 3D turning of grade two commercially pure titanium are presented. The Third Wave AdvantEdge machining simulation software is applied for the finite element modeling. Machining experiments are conducted. The measured cutting forces and chip thickness are compared to finite element modeling results with good agreement. The effects of cutting speed, a limiting factor for productivity in titanium machining, depth of cut, and tool cutting edge radius on the peak tool temperature are investigated. This study explores the use of 3D finite element modeling to study the chip curl. Reasonable agreement is observed under turning with small depth of cut. The chip segmentation with shear band formation during the Ti machining process is investigated. The spacing between shear bands in the Ti chip is comparable with experimental measurements. Results of this research help to guide the design of new cutting tool materials and coatings and the studies of chip formation to further advance the productivity of titanium machining.     

A new approach to investigate tool condition using dummy tool holder and sensor setup

The industrial demand for automated machining systems to enhance process productivity and quality in machining aerospace components requires investigation of tool condition monitoring. The formation of chip and its removal have a remarkable effect on the state of the cutting tool during turning. This work presents a new technique using acoustic emission (AE) to monitor the tool condition by separating the chip formation frequencies from the rest of the signal which comes mostly from tool wear and plastic deformation of the work material. A dummy tool holder and sensor setup have been designed and integrated with the conventional tool holder system to capture the time-domain chip formation signals independently during turning. Several dry turning tests have been conducted at the speed ranging from 120 to 180?m/min, feed rate from 0.20 to 0.50?mm/rev, and depth of cut from 1 to 1.5?mm. The tool insert used was TiN-coated carbide while the work material was high-carbon steel. The signals from the dummy setup clearly differ from the AE signals of the conventional setup. It has been observed that time-domain signal and corresponding frequency response can predict the tool conditions. The rate of tool wear was found to decrease with chip breakage even at higher feed rate. The tool wear and plastic deformation were viewed to decrease with the increased radius of chip curvature and thinner chip thickness even at the highest cutting speed, and these have been verified by measuring tool wear. The chip formation frequency has been found to be within 97.7 to 640?kHz.     

Micro cutting of tungsten carbides with sem direct observation method

This paper describes the micro cutting of wear resistant tungsten carbides using PCD (Poly-Crystalline Diamond) cutting tools in performance with SEM (Scanning Electron Microscope) direct observation method. Turning experiments were also carried out on this alloy (V50) using a PCD cutting tool. One of the purposes of this study is to describe clearly the cutting mechanism of tungsten carbides and the behavior of WC particles in the deformation zone in orthogonal micro cutting. Other purposes are to achieve a systematic understanding of machining characteristics and the effects of machining parameters on cutting force, machined surface and tool wear rates by the outer turning of this alloy carried out using the PCD cutting tool during these various cutting conditions. A summary of the results are as follows : (1) From the SEM direct observation in cutting the tungsten carbide, WC particles are broken and come into contact with the tool edge directly. This causes tool wear in which portions scrape the tool in a strong manner. (2) There are two chip formation types. One is where the shear angle is comparatively small and the crack of the shear plane becomes wide. The other is a type where the shear angle is above 45 degrees and the crack of the shear plane does not widen. These differences are caused by the stress condition which gives rise to the friction at the shear plane. (3) The thrust cutting forces tend to increase more rapidly than the principal forces, as the depth of cut and the cutting speed are increased preferably in the orthogonal micro cutting. (4) The tool wear on the flank face was larger than that on the rake face in the orthogonal micro cutting. (5) Three components of cutting force in the conventional turning experiments were different in balance from ordinary cutting such as the cutting of steel or cast iron. Those expressed a large value of thrust force, principal force, and feed force. (6) From the viewpoint of high efficient cutting found within this research, a proper cutting speed was 15 m/min and a proper feed rate was 0.1 mm/rev. In this case, it was found that the tool life of a PCD tool was limited to a distance of approximately 230 m. (7) When the depth of cut was 0.1 mm, there was no influence of the feed rate on the feed force. The feed force tended to decrease, as the cutting distance was long, because the tool was worn and the tool edge retreated. (8) The main tool wear of a PCD tool in this research was due to the flank wear within the maximum value of V_max being about 260 μ.     

Upper Bound Analysis of Turning Using Sharp Corner Tools

A generalized upper bound model of turning operations using flat-faced sharp corner tools with both the side and end cutting edges engaged in cutting is described. The projection of the uncut chip area on the rake face plane is divided into a few regions separated by lines parallel to the chip flow direction at transition points. The area of each of these regions is transformed to the area of the corresponding regions of the shear surface using the ratio of the shear speed to the chip speed. Summing up the area of these regions, the total shear surface area is obtained. The tool-chip contact length at vertices is obtained from the length along the shear surface using the similarity between orthogonal and oblique cutting in the “equivalent” plane (the plane formed by the cutting velocity and chip velocity). Knowing the tool-chip contact length, the friction area is calculated. The chip flow angle and chip speed are obtained by minimizing the cutting power with respect to both these variables. Comparison of the chip flow angle predicted by the current model with the chip flow angle measured by direct high speed photography of the chip motion over the tool rake face shows good correlation between the two for various tool geometries and cutting conditions. The shape of the shear surface and the chip cross section predicted by the model are also presented.     

Experimental study on AE from precision diamond machining

Acoustic emission (AE) has been studied extensively as a technique for monitoring machining processes. In this study, relationships between the RMS AE signals and the cutting parameters in precision diamond turning are investigated experimentally. To build such experimental relationships, each measured RMS AE signal is seperated into two components, the one associated with the chip formation and the other one resulting from the rubbing friction at the tool flank-workpiece interface. The responses of these components to variations in cutting parameters are then explained. The experimental data suggest that the AE is generated predominantly by the chip formation in diamond turning, whereas the rubbing friction is one of the primary sources of AE in the conventional turning.     

Monitoring tool wear during wood machining with acoustic emission

The purpose of this study was to determine the degree of change in acoustic emission (AE) during cutting as a cutter tool was worn. AE is defined as the stress or pressure waves generated during dynamic processes in materials and is generated during fracture, delamination, deformation and distortion of wood during cutting. Previous work has shown that AE is sensitive to changes in the chip formation process and therefore could be used to monitor continuously the state of the cutting process. For this study a single-point cutting tool was worn by turning a green-white fir (Abies concolor (Gord. and Glend.) Lindl.) log on an engine lathe equipped with an automatic feed. The relationship between the AE output and the amount of wood cut was close to linear in the initial stages of the blade wear. As the blade became severely worn, the AE levels dropped dramatically and an asymptotic relationship between the two variables became evident.     

Experimental investigation of machining characteristics and chatter stability for Hastelloy-X with ultrasonic and hot turning

Ultrasonic-assisted machining is a machining operation based on the intermittent cutting of material which is obtained through vibrations generated by an ultrasonic system. This method utilizes low-amplitude vibrations with high frequency to prevent continuous contact between a cutting tool and a workpiece. Hot machining is another method for machining materials which are difficult to cut. The basic principle of this method is that the surface of the workpiece is heated to a specific temperature below the recrystallization temperature of the material. This heating operation can be applied before or during the machining process. Both of these operations improve machining operations in terms of workpiece-cutting tool characteristics. In this study, a novel hybrid machining method called hot ultrasonic-assisted turning (HUAT) is proposed for the machinability of Hastelloy-X material. This new technique combines ultrasonic-assisted turning (UAT) and hot turning methods to take advantage of both machining methods in terms of machining characteristics, such as surface roughness, stable cutting depths, and cutting tool temperature. In order to observe the effect of the HUAT method, Hastelloy-X alloy was selected as the workpiece. Experiments on conventional turning (CT), UAT, and HUAT operations were carried out for Hastelloy-X alloy, changing the cutting speed and cutting tool overhang lengths. Chip morphology was also observed. In addition, modal and sound tests were performed to investigate the modal and stability characteristics of the machining. The analysis of variance (ANOVA) method was performed to find the effect of the cutting speed, tool overhang length, and machining techniques (CT, UAT, HUAT) on surface roughness, stable cutting depths, and cutting tool temperature. The results show both ultrasonic vibration and heat improve the machining of Hastelloy-X. A decrease in surface roughness and an increase in stable cutting depths were observed, and higher cutting tool temperatures were obtained in UAT and HUAT compared to CT. According to the ANOVA results, tool overhang length, cutting speed, and machining techniques were effective parameters for surface roughness and stable cutting depths at a 1% significance level (p ≤ 0.01). In addition, cutting speed and machining techniques have an influence on cutting tool temperature at a 1% significance level (p ≤ 0.01). During chip analysis, serrated chips were observed in UAT and HUAT.     

Effect of material anisotropy on shear angle prediction in metal cutting—a mesoplasticity approach

Material anisotropy plays an important role in the formation of shear angle in metal cutting. Crystallographic textures contribute to an important source of material anisotropy. A simplified mesoplasticity model is proposed in this paper to predict the effect of crystallographic orientations on the shear angle formation in machining a polycrystalline work material. The most likely shear angle is the one at which the Taylor factor is minimum. A good agreement is found between the predicted shear angle in machining a polycrystalline OFHC copper and the experimental data reported in the published literature. The assumptions made in the model approximate well the cutting conditions commonly encountered in single point diamond turning process.     

车削过程切削力的计算机数值仿真

切削力是表征切削过程最重要特征的物理量,其动态变化将直接影响加工过程中刀具与工件的相对位移、刀具磨损和表面加工质量等,所以对切削力建模是进行加工过程物理仿真研究的基础。因此在基于实时工况的切削实验研究基础上,考虑切削参数的因素,利用BP（back pmpagation）神经网络建立车削过程中的切削力的仿真模型。通过大量的样本训练,使神经网络能够对切削力进行较准确地数值仿真。     

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.     

面向加工特征的刀具和切削参数计算机辅助选择系统

切削刀具制造商面临围绕大量工件材料和加工特征为客户提供合理刀具和切削参数的现状,切削工艺规划的核心步骤也是刀具和切削参数的确定。确定刀具和切削参数一般多从零件材料角度出发,可能导致工件与刀具不匹配。文中提出面向加工特征的刀具和切削参数计算机辅助选择系统的开发。系统包括车削特征、铣削特征、钻削和镗削加工特征,系统利用特征图形作为用户交互式接口,采用关系数据库结合数据驱动和规则推理逻辑来选择刀具和切削参数,利用数学模型计算过程参数包括单工步加工工时、切削功率、最大粗糙度等,并辅助制定工序。以车刀和车削参数选择为例,介绍该系统的实现方法。该系统可以辅助设计师及工艺人员选择合理的刀具和切削参数。     

FORCES AND TEMPERATURES IN HARD TURNING

In precision machining, due to the recent developments in cutting tools, machine tool structural rigidity and improved CNC controllers, hard turning is an emerging process as an alternative to some of the grinding processes by providing reductions in costs and cycle-times. In industrial environments, hard turning is established for geometry features of parts with low to medium requirements on part quality. Better understanding of cutting forces, stresses and temperature fields, temperature gradients created during the machining are very critical for achieving highest quality products and high productivity in feasible cycle times. To enlarge the capability profile of the hard turning process, this paper introduces prediction models of mechanical and thermal loads during turning of 51CrV4 with hardness of 68 HRC by a CBN tool. The shear flow stress, shear and friction angles are determined from the orthogonal cutting tests. Cutting force coefficients are determined from orthogonal to oblique transformations. Cutting forces, temperature field for the chip and tool are predicted and compared with experimental measurements. The experimental temperature measurements are conducted by the advanced hardware device FIRE-1 (Fiberoptic Ratio Pyrometer).     

FORCES AND TEMPERATURES IN HARD TURNING

In precision machining, due to the recent developments in cutting tools, machine tool structural rigidity and improved CNC controllers, hard turning is an emerging process as an alternative to some of the grinding processes by providing reductions in costs and cycle-times. In industrial environments, hard turning is established for geometry features of parts with low to medium requirements on part quality. Better understanding of cutting forces, stresses and temperature fields, temperature gradients created during the machining are very critical for achieving highest quality products and high productivity in feasible cycle times. To enlarge the capability profile of the hard turning process, this paper introduces prediction models of mechanical and thermal loads during turning of 51CrV4 with hardness of 68 HRC by a CBN tool. The shear flow stress, shear and friction angles are determined from the orthogonal cutting tests. Cutting force coefficients are determined from orthogonal to oblique transformations. Cutting forces, temperature field for the chip and tool are predicted and compared with experimental measurements. The experimental temperature measurements are conducted by the advanced hardware device FIRE-1 (Fiberoptic Ratio Pyrometer).     

A probabilistic neural network applied in monitoring tool wear in the end milling operation via acoustic emission and cutting power signals

Tool condition monitoring, which is very important in machining, has improved over the past 20 years. Several process variables that are active in the cutting region, such as cutting forces, vibrations, acoustic emission (AE), noise, temperature, and surface finish, are influenced by the state of the cutting tool and the conditions of the material removal process. However, controlling these process variables to ensure adequate responses, particularly on an individual basis, is a highly complex task. The combination of AE and cutting power signals serves to indicate the improved response. In this study, a new parameter based on AE signal energy (frequency range between 100 and 300 kHz) was introduced to improve response. Tool wear in end milling was measured in each step, based on cutting power and AE signals. The wear conditions were then classified as good or bad, the signal parameters were extracted, and the probabilistic neural network was applied. The mean and skewness of cutting power and the root mean square of the power spectral density of AE showed sensitivity and were applied with about 91% accuracy. The combination of cutting power and AE with the signal energy parameter can definitely be applied in a tool wear-monitoring system.     

Multi-objective optimization of oblique turning operations using finite element model and genetic algorithm

Multi-objective optimization of oblique turning operations while machining AISI H13 tool steel has been carried out using developed finite element (FE) model and multi-objective genetic algorithm (MOGA-II). The turning operation is optimized in terms of cutting force and temperature with constraints on required material removal rate and cutting power. The developed FE model is capable to simulate cutting forces, temperature and stress distributions, and chip morphology. The tool is modeled as a rigid body, whereas the workpiece is considered as elastic–thermoplastic with strain rate sensitivity and thermal softening effect. The effects of cutting speed, feed rate, rake angle, and inclination angle are modeled and compared with experimental findings. FE model is run with different parameters with central composite design used to develop a response surface model (RSM). The developed RSM is used as a solver for the MOGA-II. The optimal processing parameters are validated using FE model and experiments.     

ANALYSIS OF THREE-DIMENSIONAL MACHINING USING AN EXTENDED OBLIQUE MACHINING THEORY

This paper presents an extended oblique machining theory applicable to the analysis of 3-D machining. Existing theories are evaluated to identify suitable formulations which are used with necessary modifications for predicting various quantities pertaining to cutting conditions of three dimensional machining. Actual chip flow angles extracted from measured forces, to account for the nose radius effect, are used, instead of available models, to predict important quantities such as shear plane angle, effective rake angle and shear flow angle. Experiments are conducted in the realms of conventional and high speed machining using AISI 4140 steel and aluminum 7075-T6 respectively with uncoated carbide inserts, and various process conditions pertaining to the cutting mechanics are calculated. The extended oblique machining theory is experimentally validated in predicting temperatures at the tool-chip interface and shear plane for conventional machining. Simulation results from the finite element modeling are used for verifying the shear stress and shear plane temperature predicted by the extended oblique machining theory.