Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks

In machining of parts, surface quality is one of the most specified customer requirements. Major indication of surface quality on machined parts is surface roughness. Finish hard turning using Cubic Boron Nitride (CBN) tools allows manufacturers to simplify their processes and still achieve the desired surface roughness. There are various machining parameters have an effect on the surface roughness, but those effects have not been adequately quantified. In order for manufacturers to maximize their gains from utilizing finish hard turning, accurate predictive models for surface roughness and tool wear must be constructed. This paper utilizes neural network modeling to predict surface roughness and tool flank wear over the machining time for variety of cutting conditions in finish hard turning. Regression models are also developed in order to capture process specific parameters. A set of sparse experimental data for finish turning of hardened AISI 52100 steel obtained from literature and the experimental data obtained from performed experiments in finish turning of hardened AISI H-13 steel have been utilized. The data sets from measured surface roughness and tool flank wear were employed to train the neural network models. Trained neural network models were used in predicting surface roughness and tool flank wear for other cutting conditions. A comparison of neural network models with regression models is also carried out. Predictive neural network models are found to be capable of better predictions for surface roughness and tool flank wear within the range that they had been trained.Predictive neural network modeling is also extended to predict tool wear and surface roughness patterns seen in finish hard turning processes. Decrease in the feed rate resulted in better surface roughness but slightly faster tool wear development, and increasing cutting speed resulted in significant increase in tool wear development but resulted in better surface roughness. Increase in the workpiece hardness resulted in better surface roughness but higher tool wear. Overall, CBN inserts with honed edge geometry performed better both in terms of surface roughness and tool wear development.     

Effects of random aspects of cutting tool wear on surface roughness and tool life

The effects of random aspects of cutting tool flank wear on surface roughness and on tool lifetime, when turning the AISI 1045 carbon steel, were studied in this investigation. It was found that standard deviations corresponding to tool flank wear and to the surface roughness increase exponentially with cutting time. Under cutting conditions that correspond to finishing operations, no significant differences were found between the calculated values of the capability indexC _p at the steady-state region of the tool flank wear, using the best-fit method or the Box-Cox transformation, or by making the assumption that the surface roughness data are normally distributed. Hence, a method to establish cutting tool lifetime could be established that simultaneously respects the desired average of surface roughness and the required capability index.     

On the use of fractal methods for the tool flank wear characterization

Fractal theory is widely used to analyze the topography of machined surfaces, but the relationship between fractal dimensions and tool flank wear has hardly been reported. In this paper, the fractal dimensions of tool flank wear are described based on the surface roughness R_a rather than the conventional worn width VB to evaluate tool wear, thus providing better fractal identification in evaluating tool performance.     

A computer algorithm for flank and crater wear estimation in CNC turning operations

In order to increase the productivity of turning processes, several attempts have been made in the recent past for tool wear estimation and classification in turning operations. The tool flank and crater wear can be predicted by a number of models including statistical, pattern recognition, quantitative and neural network models. In this paper, a computer algorithm of new quantitative models for flank and crater wear estimation is presented. First, a quantitative model based on a correlation between increases in feed and radial forces and the average width of flank wear is developed. Then another model which relates acoustic emission (AE_rms) in the turning operation with the flank and crater wear developed on the tool is presented. The flank wear estimated by the first model is then employed in the second model to predict the crater wear on the tool insert. The influence of flank and crater wear on AE_rms generated during the turning operation has also been investigated. Additionally, chip-flow direction and tool–chip rake face interfacing area are also examined. The experimental results indicate that the computer program developed, based on the algorithm mentioned above, has a high accuracy for estimation of tool flank wear.     

Hard machining of hardened bearing steel using cubic boron nitride tool

In many cases, hard machining remains an economic alternative for bearing parts fabrication using hardened steels. The aim of this experimental investigation is to establish the behaviour of a CBN tool during hard turning of 100Cr6-tempered steel. Initially, a series of long-duration wear tests is planned to elucidate the cutting speed effects on the various tool wear forms. Then, a second set of experiments is devoted to the study of surface roughness, cutting forces and temperature changes in both the chip and the workpiece. The results show that CBN tool offers a good wear resistance despite the aggressiveness of the 100Cr6 at 60HRC. The major part of the heat generated during machining is mainly dissipated through the chip. Beyond 280 m/min, the machining system becomes unstable and produces significant sparks and vibrations after only a few minutes of work. The optimal productivity of machined chip was recorded at a speed of 120 m/min for an acceptable tool flank wear below 0.4 mm. Beyond this limiting speed, roughness (R_a) is stabilized because of a reduction in the cutting forces at high speeds leading to a stability of the machining system. The controlling parameter over roughness, in such hard turning cases, remains tool advance although ideal models do not describe this effect rationally. Surface quality obtained with CBN tool significantly compared with that of grinding despite an increase in the advance by a factor of 2.5. A relationship between flank wear (VB) and roughness (R_a) is deduced from parametric analysis based on extensive experimental data.     

An improved cutting force and surface topography prediction model in end milling

During the milling operation, the cutting forces will induce vibration on the cutting tool, the workpiece, and the fixtures, which will affect the surface integrity of the final part and consequently the product's quality. In this paper, a generic and improved model is introduced to simultaneously predict the conventional cutting forces along with 3D surface topography during side milling operation. The model incorporates the effects of tool runout, tool deflection, system dynamics, flank face wear, and the tool tilting on the surface roughness. An improved technique to calculate the instantaneous chip thickness is also presented. The model predictions on cutting forces and surface roughness and topography agreed well with experimental results.     

Experimental Investigations to Study the Effects of Microwave Treatment Strategy on Tool Performance in Turning Operation

In the present study, microwave treatment has been used to enhance the tribological properties of single-point tungsten carbide (WC) cutting tool inserts such as wear resistance and hardness. The tool hardness and cutting parameters were considered to evaluate the performance of microwave-treated WC inserts in turning operation. The optimum cutting parameters were identified using response surface method (RSM)-based desirability approach. The relationship between cutting parameters and output responses, viz. flank wear, cutting force and surface roughness, was developed using the RSM. The investigations revealed that the increase in tool hardness due to complex carbide formation results in a significant reduction in tool wear, cutting forces and improvement in the surface finish of workpiece. Further, the statistical models results were validated with the experimental results. Metallurgical properties of treated and untreated tool inserts were analyzed using scanning electron microscope, x-ray diffraction method and Vickers microhardness tests. The results highlighted the importance of microwave treatment in enhancing the machining performance in turning operation.     

Role of temperature and surface finish in predicting tool wear using neural network and design of experiments

The present work focuses on the two of the techniques, namely design of experiments and the neural network for predicting tool wear. In the present work, flank wear, surface finish and cutting zone temperature were taken as response (output) variables measured during turning and cutting speed, feed and depth of cut were taken as input parameters. Predictions for all the three response variables were obtained with the help of empirical relation between different responses and input variables using design of experiments (DOE) and also through neural network (NN) program. Predicted values of the responses by both techniques, i.e. DOE and NN were compared with the experimental values and their closeness with the experimental values was determined. Relationship between the surface roughness and the flank wear and also between the temperature and the flank wear were found out for indirect measurement of the flank wear through surface roughness and cutting zone temperature.     

Tool wear measurement in turning using force ratio

The aim of this work was to develop a reliable method to predict flank wear during the turning process. The present work developed a mathematical model for on-line monitoring of tool wear in a turning process. Force signals are highly sensitive carriers of information about the machining process and, hence, they are the best alternatives for monitoring tool wear. In the present work, determination of tool wear has been achieved by using force signals. The relationship between flank wear and the ratio of force components was established on the basis of data obtained from a series of experiments. Measurement of the ratio between the feed force and the cutting force components (F_f/F_c) has been found to provide a practical method for an in-process approach to the quantification of tool wear. A series of experiments was conducted to study the effects of tool wear as well as other cutting parameters on the cutting force signals, and to establish a relationship between the force signals, tool wear and other cutting parameters. The flank wear and the ratio of forces at different working conditions were collected experimentally to develop a mathematical model for predicting flank wear. The model was verified by comparing the experimental values with the predicted values. The relationship was then used for determination of tool flank wear.     

Determining the influence of cutting fluids on tool wear and surface roughness during turning of AISI 304 austenitic stainless steel

Knowledge of the performance of cutting fluids in machining different work materials is of critical importance in order to improve the efficiency of any machining process. The efficiency can be evaluated based on certain process parameters such as flank wear, surface roughness on the work piece, cutting forces developed, temperature developed at the tool chip interface, etc. The objective of this work is to determine the influence of cutting fluids on tool wear and surface roughness during turning of AISI 304 with carbide tool. Further an attempt has been made to identify the influence of coconut oil in reducing the tool wear and surface roughness during turning process. The performance of coconut oil is also being compared with another two cutting fluids namely an emulsion and a neat cutting oil (immiscible with water). The results indicated that in general, coconut oil performed better than the other two cutting fluids in reducing the tool wear and improving the surface finish. Coconut oil has been used as one of the cutting fluids in this work because of its thermal and oxidative stability which is being comparable to other vegetable-based cutting fluids used in the metal cutting industry.     

Tool wear and machining performance of cBN–TiN coated carbide inserts and PCBN compact inserts in turning AISI 4340 hardened steel

PCBN is the dominant tool material for hard turning applications due to its high hardness, high wear resistance, and high thermal stability. However, the inflexibility of fabricating PCBN inserts with complex tool geometries and the prohibitive cost of PCBN inserts are some of the concerns in furthering the implementation of CBN based materials for hard turning. In this paper, we present the results of a thorough investigation of cBN plus TiN (cBN–TiN) composite-coated, commercial grade, carbide inserts (CNMA 432, WC–Co (6% Co)) for hard turning applications in an effort to address these concerns. The effect of cutting speed and feed rate on tool wear (tool life), surface roughness, and cutting forces of the cBN–TiN coated carbide inserts was experimented and analyzed using analysis of variance (ANOVA) technique, and the cutting conditions for their maximum tool life were evaluated. The tool wear, surface roughness, and cutting forces of the cBN–TiN coated and commercially available PCBN tipped inserts were compared under similar cutting conditions. Both flank wear and crater wear were observed. The flank wear is mainly due to abrasive actions of the martensite present in the hardened AISI 4340 alloy. The crater wear of the cBN–TiN coated inserts is less than that of the PCBN inserts because of the lubricity of TiN capping layer on the cBN–TiN coating. The coated CNMA 432 inserts produce a good surface finish (<1.6 μm) and yield a tool life of about 18 min per cutting edge. In addition, cost analysis based on total machining cost per part was performed for the comparison of the economic viability between the cBN–TiN coated and PCBN inserts.     

Modelling the correlation between cutting and process parameters in high-speed machining of Inconel 718 alloy using an artificial neural network

An artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between cutting and process parameters during high-speed turning of nickel-based, Inconel 718, alloy. The input parameters of the ANN model are the cutting parameters: speed, feed rate, depth of cut, cutting time, and coolant pressure. The output parameters of the model are seven process parameters measured during the machining trials, namely tangential force (cutting force, F_z), axial force (feed force, F_x), spindle motor power consumption, machined surface roughness, average flank wear (VB), maximum flank wear (VB_max) and nose wear (VC). The model consists of a three-layered feedforward backpropagation neural network. The network is trained with pairs of inputs/outputs datasets generated when machining Inconel 718 alloy with triple (TiCN/Al₂O₃/TiN) PVD-coated carbide (K 10) inserts with ISO designation CNMG 120412. A very good performance of the neural network, in terms of agreement with experimental data, was achieved. The model can be used for the analysis and prediction of the complex relationship between cutting conditions and the process parameters in metal-cutting operations and for the optimisation of the cutting process for efficient and economic production.     

The effect of lubrication conditions on belt finishing

The belt finishing process is a recent manufacturing technique in the field of superfinishing of hard material. Belt finishing leads to an homogenous surface with a very smooth surface roughness and good bearing curve parameters. In this way, belt finishing can complement effectively hard turning, whose disability is the shifting of the surface quality due to tool flank wear. In order to study the effect and the interaction of lubrications conditions on belt finishing after hard turning, an experimental study is proposed. The interaction between lubrications conditions and belt feed and the effect on roughness parameters has been investigated. It was shown that minimum quantity lubrication with low belt feed is the best way to have the optimal roughness characteristics. Under these conditions, the process is not a basic belt finishing operation but a combination of belt finishing and lapping due to the presence of a slurry made of free abrasive grains, microchips and oil, in the contact. Additionally, it has been revealed that dry belt finishing is not suitable because of the rapid destruction of abrasive grains.     

Development of flank wear prediction model of Zirconia Toughened Alumina (ZTA) cutting tool using response surface methodology

Flank wear is an important criterion for machinability assessment of a material. The present study is an attempt to evaluate the influence of factors such as cutting speed, feed rate and depth of cut on flank wear during hard turning of EN 24 steel with newly developed transformed toughened nano-composite Zirconia Toughened Alumina (ZTA) ceramic inserts. ZTA provides a cost effective materials solution to the most demanding applications which require wear resistance, corrosion resistance, high temperature stability and superior mechanical strength. Several machining experiments were performed and mathematical models for flank wear have been postulated by using Response Surface Methodology (RSM). The analysis was based on a first order model in which the flank wear (V_b) is expressed as a function of three independent variables i.e. cutting speed (V), feed rate (F) and depth of cut (T). Analysis of Variance (ANOVA) was applied to check the adequacy of the mathematical model and their respective parameters. Key parameters and their interactive effect on flank wears have also been presented in graphical contours which may help for choosing the process parameters and predict the cutting condition for maximum tool life.     

电弧离子镀和高功率脉冲磁控溅射AlTiN涂层及其切削性能研究

目的 比较两种沉积方法制备的AlTiN涂层的切削性能.方法 利用高功率脉冲磁控溅射技术(HiPIMS)和电弧离子镀技术(AIP),在硬质合金车刀片上沉积AlTiN涂层,比较和研究两种AlTiN涂层的组织形貌特性及综合性能.利用扫描电子显微镜和X射线能量色散谱仪,观察和检测涂层的生长形貌和元素含量.采用激光共聚焦扫描显微...     

Tool wear when turning hardened AISI 4340 with coated PCBN tools using finishing cutting conditions

Tool wear is one of the most important aspects in metal cutting, especially when machining hardened steels. The present work shows the results of tool wear, cutting force and surface finish obtained from the turning operation on hardened AISI 4340 using PCBN coated and uncoated edges. Three different coatings were tested using finishing conditions: TiAlN, TiAlN-nanocoating and AlCrN. The lowest tool wear happened with TiAlN-nanocoating followed by TiAlN, AlCrN and uncoated PCBN. Forces followed the same pattern, increasing in the same order, after flank wear appears. At the beginning of cutting, there was no significant difference amongst the coated tools, only the uncoated one showing higher cutting force. Ra values were between 0.7 and 1.2 μm with no large differences amongst the tools. Finite element method (FEM) simulations indicated that temperature at the chip–tool interface was around 800 °C in absence of flank wear, independently of coating. In that range only the TiAlN coating oxidize since AlCrN needs higher than 1000 °C. Therefore, due to a combination of high hardness in the cutting temperature range and the presence of an oxidizing layer, TiAlN-nanocoating performed better in terms of tool wear and surface roughness.     

Experimental evaluation of minimum quantity lubrication in near micro-milling

This paper presents the performance of the minimum quantity lubrication (MQL) technique in near micro-milling with respect to dry cutting on the basis of tool wear, surface roughness and burr formation. The effects of tool materials, oil flow rate and air flow rate on tool performance in MQL cutting are also studied. It is found that the application of MQL will significantly improve the tool life, surface roughness and burr formation compared to those in dry cutting based on slotting tests with micro-end mills on a meso-scale machine tool. It is also observed that the values of surface roughness are close related to the tool-wear conditions in micro-cutting. Based on the experimental results, it is presumed that the maximum allowable tool flank wear of the 600-μm micro-tool is 80 μm while the surface finish quickly deteriorates after the tool flank wear reaches 80 μm and the tool breaks soon after the tool wear reaches 100 μm. The optimal lubrication conditions in this study are oil flow rate of 1.88 ml/h and air flow rate of 40 l/min. It is also found that the air flow rate has a more significant influence on tool life than the oil flow rate under MQL conditions in this study.     

基于响应曲面法的钛合金干式车削工艺参数优化

为了提高钛合金干式车削加工质量,采用响应曲面法对主要车削工艺参数进行了优化,以工件表面粗糙度Ra和刀具磨损量VC作为评价指标,设计了切削速度、背吃刀量和进给量三因素的Box-Behnken实验模型。利用方差和拟合残差概率分布分析三因素的显著性及交互作用,并结合实验检验所建表面粗糙度和刀具磨损二阶响应预测模型的有效性。响应曲面法优化后的最佳工艺参数为:切削速度20 m/min、背吃刀量0.1788 mm、进给量0.1 mm/r,此时得到的表面粗糙度和刀具磨损量为1.031μm和155.6μm,与预测值的误差分别为:9.93%和1.58%。结果表明:基于响应曲面法的钛合金干式车削表面粗糙度和刀具磨损量预测模型准确有效。     

Optimum cutting tool geometry when interrupted cutting carburized steel by CBN tool

Interrupted turning, a quite severe application for the CBN tool, was attempted. In the turning of a two-groove bar, gradual wear controlled the tool life. However tool failure determined the life in the turning of a spline shaft. The type of failure in the latter case changed depending on the way in which the tool collided with the tool tip—catastrophic damage could be avoided with substantial improvement of the tool life and surface roughness of the workpiece. For further improvements of the life, a new tool was developed having a land on the flank face. Turning with this new tool resulted in a prolonged life, as much as 26 times that of the conventional tool previously developed for continuous turning.     

Cutting performance and wear mechanism of nanoscale and microscale textured Al2O3/TiC ceramic tools in dry cutting of hardened steel

Nanoscale and microscale textures with different geometrical characteristics were fabricated on the surface of the Al₂O₃/TiC ceramic tool, and molybdenum disulfide (MoS₂) solid lubricants were burnished into the textures. The effect of the textures on the cutting performance was investigated using the textured self-lubricated tools and conventional tools in dry cutting tests. The tool wear, cutting force, cutting temperature, friction coefficient, surface roughness and chip topography were measured. Results show that the cutting force, cutting temperature, friction coefficient and tool wear of nanoscale and microscale textured self-lubricated tools are significantly reduced compared with the conventional tool, and the developed tool with wavy microscale textures on the rake face is the most effective in improving the cutting performance. The textured self-lubricated tools increase the surface roughness of machined workpiece, while they can reduce the vibration for a stable cutting and produce more uniform surface quality. The chip topography is changed by the textured self-lubricated tools. As a result, the nanoscale and microscale textured self-lubricated tools effectively improve the cutting performance of conventional Al₂O₃/TiC ceramic tool, and they are applicable to a stable dry cutting of the hardened steel.