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.     

A brief review: acoustic emission method for tool wear monitoring during turning

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process monitoring. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing processes. This paper reviews briefly the research on AE sensing of tool wear condition in turning. The main contents included are:

1. The AE generation in metal cutting processes, AE signal classification, and AE signal correction.

2. AE signal processing with various methodologies, including time series analysis, FFT, wavelet transform, etc.

3. Estimation of tool wear condition, including pattern classification, GMDH methodology, fuzzy classifier, neural network, and sensor and data fusion.

A review of AE-based tool wear monitoring in turning is an important step for improving and developing new tool wear monitoring methodology.     

Influence of refrigeration/lubrication condition on SAE 52100 hardened steel turning at several cutting speeds

Nowadays, the use of cutting fluids on machining operations has been questioned, due to problems they may cause to the environment, due to damage to human health and also more due to the severe laws regarding industrial waste that have been passed. Therefore, industries are being forced to review the production processes aiming either, at elimination or, when it is not possible, a sharp reduction in the use of these fluids. The technique of minimum volume of oil (MVO) has been studied in machining processes as one alternative to the use of abundant cutting fluid. Research has shown that this technique, which is the pulverisation of a minimum volume of oil in a flow of compressed air, in several cases, reduces tool wear when compared to complete dry cutting, causing the improvement of the workpiece surface quality and an increase in tool life. In this work, the influence of MVO (oil flow of 10 ml/h) in the wear of a cubic boron nitride (CBN) tool, when turning 52100 hardened steel, was studied. Aiming at a comparison of the results, the experiments were also carried out under two other conditions: dry cutting and cutting with abundant soluble oil (wet cutting). During the experiments, the influence of cutting speed on CBN tool wear for the three refrigeration conditions was also checked. Besides this, tool wear and workpiece surface roughness was also measured as cutting time elapsed.     

Gradual wear monitoring of turning inserts using wavelet analysis of ultrasound waves

Discrete wavelet transforms of ultrasound waves is used to measure the gradual wear of carbide inserts during turning operations. Ultrasound waves, propagating at a nominal frequency of 10 MHz, were pulsed into the cutting tools towards the cutting edge at a burst frequency of 10 KHz. The reflected waves off the mark, nose and flank surfaces were digitized at a sampling rate of 100 MHz. Daubechies Quadrature Mirror Filter pair was used to decompose ultrasound signals into frequency packets using a tree structure.Normalized signals in each level of decomposition were used to search for a neural network architecture that correlates the ultrasound measurements to the wear level on the tool. A three-layer Multi-Layer Perceptron architecture yielded the best correlation (95.9%) using the wave packets from the fourth level of decomposition with frequencies 3.75–4.375 and 5.625–6.875 MHz.     

An experimental investigation on monitoring of crater wear in turning using ultrasonic technique

Tool life prediction and tool change strategies are now based on most conservative estimates of tool life from past tool wear data. Hence usually tools are underutilized. In an unmanned factory, this has the effect of increased frequency of the tool changes and therefore increased cost. An ultrasound online monitoring of crater wear of the uncoated carbide insert during the turning operation is presented. The method relies on inducing ultrasound waves in the tool, which are reflected by side flank surface. The amount of reflected energy is correlated with crater wear depth. Various ultrasonic parameters are considered for defining the crater wear and individual contribution of each parameter is analyzed. The ultrasonic parameters, amplitude, pulse width and root mean square (RMS) of the signal are used to quantify the crater depth and width. The power spectrum analysis of received signals shows the importance of frequency components in defining the tool wear. In the presented work, the normalizing of signals are carried out by insert hole, which is provided for clamping. This signal is not influenced by the wear but affected by other factors like tool material variation, improper couplant, temperature, etc. The response of the wear signal is normalized to the response of hole signal by mathematical division. A new approach adaptive neuro-fuzzy inference system (ANFIS) for monitoring of crater in carbide insert is presented. This improves the system accuracy and eliminates the limitation in statistical modeling that was presented in previous studies.     

On-line monitoring of flank wear in turning with multilayered feed-forward neural network

A multilayer feed-forward neural network (MLFF N-Network) algorithm is presented for on-line monitoring of tool wear in turning operations. The algorithm is based on the cutting conditions (cutting speed and feed rate) and measured cutting forces, which are used as inputs to a three-layer MLFF N-Network. The network is first trained using a set of workpiece material (P20 mold steel) and a tungsten carbide (H13A) cutting tool at various cutting conditions. The algorithm is later successfully verified on-line during turning of the same mold steel at conditions that differ from the data used in training. The algorithm is packaged in a software module, and integrated to an open Intelligent Machining Module used on industrial CNC systems.     

Bar diameter as an influencing factor on temperature in turning

Factors such as cutting speed, feed rate, tool material, etc., are well known to have an effect on tool wear in metal turning. However, reliable methods of wear prediction over a broad spectrum of cutting circumstance remain elusive, suggesting that not all factors have been recognised as significant and thus considered. This paper demonstrates that one such factor is bar diameter. The findings are analysed in three separate ways. All tests were performed under identical cutting conditions, i.e. cutting speeds were constant as well as the feed rate and depth of cut, also the same bar was used except for varying the bar diameter. All experiments were performed in single point turning on solid carbon steel bar (BS970 080A42), by using uncoated ISO (4957) (BS 4659 BT42) HSS insert.     

Optimizing the use of dry cutting in rough turning steel operations

The main objective of using cutting fluids in machining operations is the reduction of temperature in the cutting region to increase tool life. However, the advantages offered by cutting fluids have been strongly debated because of their negative effects on the economic aspect, the environment and the health of workers using them. A trend to solve these problems is cutting without fluid, a method named dry cutting, which has been made possible due to technological innovations. This work aims to seek conditions in which dry cutting is satisfactory compared with the flood of fluid (called here wet cutting) usually used. Aiming at this goal, several experiments were carried out varying parameters such as cutting speed, feed, depth of cut and tool material in rough turning of ABNT 1045 steel in dry and wet cutting. The analysis of the results showed that wet turning is, as expected, better for tool life. The second conclusion is that dry cutting cannot be used with large depth of cut. But the main conclusion is that, if the tool material is changed to a more wear resistant one, dry cutting can be used with results very similar to those obtained with a flood of fluid.     

Tool wear and chip formation during hard turning with self-propelled rotary tools

This paper presents a performance assessment of rotary tool during machining hardened steel. The investigation includes an analysis of chip morphology and modes of tool wear. The effect of tool geometry and type of cutting tool material on the tool self-propelled motion are also investigated. Several tool materials were tested for wear resistance including carbide, coated carbide, and ceramics. The self-propelled coated carbide tools showed superior wear resistance. This was demonstrated by evenly distributed flank wear with no evidence of crater wear. The characteristics of temperature generated during machining with the rotary tool are studied. It was shown that reduced tool temperature eliminates the diffusion wear and dominates the abrasion wear. Also, increasing the tool rotational speed shifted the maximum temperature at the chip–tool interface towards the cutting edge.     

淬火钢的车削加工研究

淬火钢硬度较高,使用常规刀具加工时难以达到理想效果。现根据工件不同的硬度要求,提出了采用不同牌号的刀具材料,选择合理的切削用量,可获得较好的加工质量和经济效益。     

Hard turning of an alloy steel on a machine tool with a polymer concrete bed

Finish turning of 39NiCrMo3 alloy steel in the hardened state has been widely investigated under dry, minimum quantity of lubricant and wet cutting conditions, using inserts in ceramic and PCBN materials, on turning centers equipped with polymer concrete and cast iron beds. The progress of workpart surface roughness and tool wear with cutting time has been measured and the results analysed and discussed in detail. It has been observed that dry cutting leads to the lowest values of tool wear and surface roughness, whilst the minimal quantity of lubricant technique does not provide advantages regarding to dry turning. Furthermore, the PCBN inserts are characterised by a longer tool life than the one exhibited by the ceramic inserts. Finally, the outstanding damping and high rigidity of the polymer concrete bed has a beneficial effect on both tool wear and workpiece surface finish.     

Real time implementation of on-line tool condition monitoring in turning

This paper describes a real-time tool condition monitoring system for turning operations. The system uses a combination of static and dynamic neural networks with off-line and on-line training and cutting force components are used as diagnostic signals. The system is capable of monitoring several wear components simultaneously. The wear estimation system has been implemented experimentally to evaluate its suitability for use in shop floor conditions. The tests were performed in real time with different cutting conditions. The experimental results showed that the system was successful in predicting three wear components in real time. However, the accuracy of the wear prediction was not the same for all three wear components. The crater wear predictions were less accurate partly because of the opposing effects of crater and flank wear components on cutting force components.     

Tool wear evaluation by vibration analysis during end milling of AISI D3 cold work tool steel with 35 HRC hardness

In this study, the relationship between vibration and tool wear was investigated during end milling. For this purpose, a series of experiment were conducted in a vertical milling machine. An indexable CBN insert and AISI D3 cold work tool steel hardened to 35 HRC were used as material twin in the experiments. The vibration was measured only in the machining direction, which has more dominant signals than in the other two directions. The measurements were taken by using an acceleration sensor assembled on a machinery analyzer. Tool wear was measured by a toolmaker's microscope. It was observed that there was an increase in vibration amplitude with increasing tool wears. This situation was evident especially by monitoring vibration of displacement type. It was also observed that the first three multiplies of tooth passing frequency (1×, 2×, 3×) gave the best information about the tool wear. Results showed that there was no considerable increase in the vibration amplitude until a flank wear value of 160 μm was reached, above which the vibration amplitude increased significantly.     

Progressive cutting tool wear detection from machined surface images using Voronoi tessellation method

Tool condition monitoring by machine vision approach has been gaining popularity day by day since it is a low cost and flexible method. In this paper, a tool condition monitoring technique by analysing turned surface images has been presented. The aim of this work is to apply an image texture analysis technique on turned surface images for quantitative assessment of cutting tool flank wear, progressively. A novel method by the concept of Voronoi tessellation has been applied in this study to analyse the surface texture of machined surface after the creation of Voronoi diagram. Two texture features, namely, number of polygons with zero cross moment and total void area of Voronoi diagram of machined surface images have been extracted. A correlation study between measured flank wear and extracted texture features has been done for depicting the tool flank wear. It has been found that number of polygons with zero cross moment has better linear relationship with tool flank wear than that of total void area.     

基于雷达图法的材料切削加工性评价

提出一种材料切削加工性综合评价方法——雷达图法,制定了基于雷达图法的材料切削加工性综合评价的各项指标,并对各指标进行标准化、归一化处理。通过提取雷达图的特征向量,采用特定综合评价函数,实现雷达图法的数值定量评价。对两种涂层硬质合金刀具切削加工FGH95时的切削加工性进行综合的评价,对试验所得数据进行标准化、归一化处理,绘制出FGH95材料切削加工性的雷达图。     

State of the art in hard turning

Hard turning is gaining grounds for machining hardened steels as it has several benefits over grinding. There are several issues, which should be understood and dealt with, to achieve successful performance of the process. Researchers have worked upon several aspects related to hard turning. The present work is an effort to review some of these works and to understand the key issues related to process performance. The review shows that the type of tool material, cutting edge geometry and cutting parameters affect the process efficiencies in terms of tool forces, surface integrities integrity, and white layer. Adequate machine rigidity is a must essential to minimize the process inaccuracies. Also moreover, for finish hard turning, where the depth of cut is less than the nose radius of the tool, the forces deviate from the conventional trends as the radial force component is the maximum and axial force component becomes minimum. The present work finally lists down certain areas that can be taken up for further research in hard turning.     

Analytical model for tool wear monitoring in turning operations using ultrasound waves

This paper presents an analytical model to monitor the gradual wear of cutting tools, on-line, during turning operations using ultrasound waves. Ultrasound waves at a frequency of 10 MHz were pulsed continuously inside several cutting tools, towards their cutting edge. The change in tool geometry, due to gradual wear, has been related, in a mathematical form, to the change in the acoustic behavior of ultrasound waves inside the body of the cutting tools. Physical laws governing the propagation and reflection of ultrasound waves along with geometrical analysis of the wear area were used in deriving the mathematical model. The experimental setup and model evaluation is based on a previously published research work by the author, which presented an empirical model showing a corresponding change in the ultrasound behavior with tool gradual wear. The current work emphasizes the previous findings and presents the relation between the acoustic behavior of ultrasound waves and the progressive tool gradual wear in a mathematical form that can be easily used in machine control operations.     

二硅酸锂玻璃陶瓷车削实验刀具磨损模型研究

使用硬质合金数控车刀对二硅酸锂玻璃陶瓷进行车削实验,观测刀具磨损形貌。结果表明:刀尖和后刀面是磨损较严重的部分,刀具磨损形式主要是磨料磨损和黏结磨损。采用刀具磨损体积作为刀具磨损情况的评价指标,并建立车削过程刀具体积磨损的理论模型,结果表明刀具磨损体积与刀具和工件的材料属性及刀具角度有关;随车削长度增加,刀具实际磨损体积增加,将实验结果与根据模型计算所得的理论值进行对比,二者基本吻合。     

Fabrication of nanostructured tool steel layer by combination of laser cladding and friction stir processing

A general fabrication process of the nanostructured tool steel layer with various carbide particles was developed by a combination of laser cladding and friction stir processing (FSP). The dendritic carbides formed by the laser cladding were crushed to carbide nanoparticles during the FSP, and were uniformly dispersed in the iron matrix. The shape and size of the carbide particles could be controlled by the conditions of the laser cladding and the FSP. The nanostructured tool steel layer formed by the laser and the FSP under the optimized conditions had a microhardness of ~ 900 HV which was higher than that of conventional tool steels.