Tool wear characteristics in machining of nickel-based superalloys

Nickel-based superalloy is widely employed in aircraft engines and the hot end components of various types of gas turbines with its high strength, strong corrosion resistance and excellent thermal fatigue properties and thermal stability. However, nickel-based superalloy is one of the extremely difficult-to-cut materials. During the machining process, the interaction between the tool and the workpiece causes the severe plastic deformation in the local area of workpiece, and the intense friction at the tool–workpiece interface. The resulting cutting heat coupled with the serious work hardening leads to a series of flaws, such as excessive tool wear, frequent tool change, short tool life, low productivity, and large amount of power consumption etc., in which the excessive tool wear has become one of the main bottlenecks that constraints the machinability of nickel-based superalloys and its wide range of applications.In this article, attention is mainly focused on the tool wear characteristics in the machining of nickel-based superalloys, and the state of the art in the fields of failure mechanism, monitoring and prediction, and control of tool wear are reviewed. The survey of existing works has revealed several gaps in the aspects of tool self-organizing process based on the non-equilibrium thermodynamics, tool wear considering the tool nose radius, thermal diffusion layer in coated tools, tool life prediction based on the thermal–mechanical coupling, and industrial application of tool wear online monitoring devices. The review aims at providing an insight into the tool wear characteristics in the machining of nickel-based superalloys and shows the great potential for further investigations and innovation in the field of tool wear.     

Milling error prediction and compensation in machining of low-rigidity parts

The paper reports on a new integrated methodology for modelling and prediction of surface errors caused by deflection during machining of low-rigidity components. The proposed approach is based on identifying and modelling key processing characteristics that influence part deflection, predicting the workpiece deflection through an adaptive flexible theoretical force-FEA deflection model and providing an input for downstream decision making on error compensation. A new analytical flexible force model suitable for static machining error prediction of low-rigidity components is proposed. The model is based on an extended perfect plastic layer model integrated with a FE model for prediction of part deflection. At each computational step, the flexible force is calculated by taking into account the changes of the immersion angles of the engaged teeth. The material removal process at any infinitesimal segment of the milling cutter teeth is considered as oblique cutting, for which the cutting force is calculated using an orthogonal–oblique transformation. This study aims to increase the understanding of the causes of poor geometric accuracy by considering the impact of the machining forces on the deflection of thin-wall structures. The reported work is a part of an ongoing research for developing an adaptive machining planning environment for surface error modelling and prediction and selection of process and tool path parameters for rapid machining of complex low-rigidity high-accuracy parts.     

Tool wear mechanisms and tool life enhancement in ultra-precision machining of titanium

Titanium and its alloys are generally considered as difficult-to-machine materials due to their poor thermal conductivity and high strength, which is maintained at elevated temperatures. This paper examines the tool wear mechanisms involved in ultra-precision machining of titanium. In this study single-crystal diamond tools were used to machine commercial pure titanium (CP-Ti) and Ti-6Al-4V alloy. Industrial expectations for surface quality and tool life based on optical grade applications are presented. Results obtained from the characterization of the tool, chip and workpiece led to the identification of graphitization as the mechanism that initiates tool wear. As the cutting edge rounds-off due to graphitization the rate of adhesion of the workpiece material onto the tool increased, which caused the quality of the surface finish to deteriorate. To reduce this wear mechanism a protective barrier made of Perfluoropolyether (PFPE) polymer, was explored. Tribometer studies with PFPE coated diamond tools and titanium pins showed a reduction in the coefficient of friction (COF). Subsequent machining tests using PFPE coated diamond tools showed promising results in extending the tool life and enhancing the surface quality to a point where Ti can now be considered as a viable option for applications involving optical grade surfaces.     

Tool wear mechanisms of PcBN in machining Inconel 718: Analysis across multiple length scale

Recently, PcBN tooling have been successfully introduced in machining Ni-based superalloys, yet our knowledge of involved wear mechanisms remains limited. In this study, an in-depth investigation of PcBN tool degradation and related wear mechanisms when machining Inconel 718 was performed. Diffusional dissolution of cBN is an active wear mechanism. At high cutting speed oxidation of cBN becomes equally important. Apart from degradation, tool protection phenomena were also discovered. Oxidation of Inconel 718 resulted in formation of γ-Al₂O₃ and (Al,Cr,Ti)₃O₄ spinel that were deposited on the tool rake. Also on the rake, formation of (Ti,Nb,Cr)N takes place due to cBN-workpiece interaction. This creates a sandwich tool protection layer forming continuously as tool wear progresses. Such in operando protection enabled counterbalancing tool wear mechanisms and achieved high performance of PcBN in machining.     

Tool flank wear prediction in CNC turning of 7075 AL alloy SiC composite

Flank wear occurs on the relief face of the tool and the life of a tool used in a machining process depends upon the amount of flank wear; so predicting of flank wear is an important requirement for higher productivity and product quality. In the present work, the effects of feed, depth of cut and cutting speed on flank wear of tungsten carbide and polycrystalline diamond (PCD) inserts in CNC turning of 7075 AL alloy with 10 wt% SiC composite are studied; also artificial neural network (ANN) and co-active neuro fuzzy inference system (CANFIS) are used to predict the flank wear of tungsten carbide and PCD inserts. The feed, depth of cut and cutting speed are selected as the input variables and artificial neural network and co-active neuro fuzzy inference system model are designed with two output variables. The comparison between the results of the presented models shows that the artificial neural network with the average relative prediction error of 1.03% for flank wear values of tungsten carbide inserts and 1.7% for flank wear values of PCD inserts is more accurate and can be utilized effectively for the prediction of flank wear in CNC turning of 7075 AL alloy SiC composite. It is also found that the tungsten carbide insert flank wear can be predicted with less error than PCD flank wear insert using ANN. With Regard to the effect of the cutting parameters on the flank wear, it is found that the increase of the feed, depth of cut and cutting speed increases the flank wear. Also the feed and depth of cut are the most effective parameters on the flank wear and the cutting speed has lesser effect.     

五轴加工技术在模具零件加工中的应用

以实际模具零件加工为例,分析了五轴加工技术在模具零件加工中的应用,与三轴加工技术相比较,五轴加工技术提高了零件质量和加工效率,减少了电极数量,缩短了模具生产周期,在模具制造业中有广阔的应用前景。     

Tool wear in friction drilling

This study investigates the tool wear in friction drilling, a nontraditional hole-making process. In friction drilling, a rotating conical tool uses the heat generated by friction to soften and penetrate a thin workpiece and create a bushing without generating chips. The wear of a conical tungsten carbide tool used for friction drilling a low carbon steel workpiece is studied. Tool wear characteristics are quantified by measuring its weight change, detecting changes in its shape with a coordinate measuring machine, and making observations of wear damage using scanning electron microscopy. Energy dispersive spectrometry is applied to analyze the change in chemical composition of the tool surface due to drilling. In addition, the thrust force and torque during drilling and the hole size are measured periodically to monitor the effects of tool wear. Results indicate that the carbide tool is durable, showing minimal tool wear after drilling 11,000 holes, but observations also indicate the progressively severe abrasive grooving on the tool tip.     

检具零件在数控加工中的探讨

根据检具零件的结构特点,将检具零件的数控加工类型分成底板类、模块类、支架类、镶件类,并介绍了对应类型零件在数控加工中的工艺过程和工艺技巧,可为同类型的检具零件加工提供一定的参考意义。     

Modelling tool wear in cemented-carbide machining alloy 718

Tool wear is a problem in turning of nickel-based superalloys, and it is thus of great importance to understand and quantitatively predict tool wear and tool life. In this paper, an empirical tool wear model has been implemented in a commercial finite element (FE) code to predict tool wear. The tool geometry is incrementally updated in the FE chip formation simulation in order to capture the continuous evolution of wear profile as pressure, temperature and relative velocities adapt to the change in geometry. Different friction and wear models have been analysed, as well as their impact on the predicted wear profile assessed. Analyses have shown that a more advanced friction model than Coulomb friction is necessary in order to get accurate wear predictions, by drastically improving the accuracy in predicting velocity, thus having a dramatic impact on the simulated wear profile. Excellent experimental agreement was achieved in wear simulation of cemented carbide tool machining alloy 718.     

Chatter suppression in five-axis machining of flexible parts

In this work on line and off line measures for chatter suppression in cutting flexible turbine blades on a five-axis machine were implemented. The off line measure was implemented by increasing the feed rate at times when the rotary axes were undergoing large increments. A spindle speed ramping controller was implemented for on line control. A combined scheme was also implemented where both the feed scheduling, off line, and speed ramping, on line, effected the cutting simultaneously. Cutting tests of aluminum turbine blades were conducted to test the effectiveness of the different vibration suppression measures. Each measure, on and off line, worked well individually, and better results were obtained under the combined scheme.     

Influence of oxygen on the tool wear in machining

High temperatures generated in machining are known to facilitate oxidation wear. A controlled atmosphere chamber was developed to investigate the effects of oxygen on tool wear and high speed machining tests were conducted on air and in argon. Cemented carbide, cermet and cubic boron nitride tooling was used on alloyed steel, hardened tool steel and superalloy Alloy 718. Machining in argon resulted in higher flank wear, higher cutting forces, and larger tool–chip contact length on the rake face. However, in hard machining, argon atmosphere reduced rake cratering. Transmission electron microscopy of tools worn on air showed formation of nanocrystalline Al₂O₃ film on the rake when machining aluminium containing Alloy 718, while no oxide films was detectable in the other cases.     

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.     

Tool wear monitoring of micro-milling operations

The mechanical removal of materials using miniature tools, known as micro-mechanical milling processes, has unique advantages in creating miniature 3D components using a variety of engineering materials, when compared with photolithographic processes. Since the diameter of miniature tools is very small, excessive forces and vibrations significantly affect the overall quality of the part. In order to improve the part quality and longevity of tools, the monitoring of micro-milling processes is imperative. This paper examines factors affecting tool wear and a tool wear monitoring method using various sensors, such as accelerometers, force and acoustic emission sensors in micro-milling. The signals are fused through the neuro-fuzzy method, which then determines whether the tool is in good shape or is worn. An optical microscope is used to observe the actual tool condition, based upon the edge radius of the tool, during the experiment without disengaging the tool from the machine. The effectiveness of tool wear monitoring, based on a number of different sensors, is also investigated. Several cutting tests are performed to verify the monitoring scheme for the miniature micro-end mills.     

考虑加工过程的复杂薄壁件加工综合误差补偿方法

针对机器人在空间曲面焊接过程中需要保持焊接速度和焊炬位姿恒定的工艺要求,提出了一种适用于复杂空间曲面焊接机器人的运动规划方法,该方法采用NURBS曲线对三维点云描述的空间轨迹进行光顺逼近,建立机器人配合变位机组成的多自由度焊接系统运动学模型并进行逆运动学求解. 开发了一套完整的复杂空间曲面焊接机器人自动编程系统. 以翻领成型器为例进行了复杂空间曲面焊接机器人的自动编程及焊接试验. 结果表明,文中提出的复杂空间曲面焊接机器人运动规划方法和自动编程系统能够顺利完成焊接任务,且运动平稳,具有良好的焊接轨迹精度.     

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.     

3D finite element analysis of tool wear in machining

The paper is focused on the 3D numerical prediction of tool wear in metal cutting operations. In particular, an analytical model, able to take into account the diffusive wear mechanism, was implemented through a specific subroutine. Furthermore, an advanced approach to model heat transfer phenomena at the tool-chip interface was included in the numerical simulation. The adopted simulation strategy gave the possibility to properly evaluate the tool wear. The 3D FEM results were compared with some experimental data obtained turning AISI 1045 steel using uncoated WC tool; a good agreement was found out.     

Tool-life and wear mechanisms of CBN tools in machining of Inconel 718

The demand for increasing productivity when machining heat resistant alloys has resulted in the use of new tool materials such as cubic boron nitride (CBN) or ceramics. However, CBN tools are mostly used by the automotive industry in hard turning, and the wear of those tools is not sufficiently known in aerospace materials. In addition, the grade of these tools is not optimized for superalloys due to these being a small part of the market, although expanding (at 20% a year). So this investigation has been conducted to show which grade is optimal and what the wear mechanisms are during finishing operations of Inconel 718. It is shown that a low CBN content with a ceramic binder and small grains gives the best results. The wear mechanisms on the rake and flank faces were investigated. Through SEM observations and chemical analysis of the tested inserts, it is shown that the dominant wear mechanisms are adhesion and diffusion due to chemical affinity between elements from workpiece and insert.     

Tool wear estimation using resource allocation network

This paper presents tool wear estimation in face milling operations using the resource allocation network (RAN). Acoustic emission (AE) signals, surface roughness parameters and cutting conditions (cutting speed, feed) have been used to formulate input patterns. The performance of RAN has been compared with the multi-layer perceptron (MLP) trained using back-propagation (BP) algorithm, and the results are presented.     

Tool path optimization for free form surface machining

This article presents a novel approach to generate optimized tool paths for free form surfaces that are commonly used in automotive, aerospace, biomedical, home appliance manufacturing and die/mold industries. The developed tool path optimization approach can handle various objectives under multiple constraints. Due to anisotropic geometry of free form surfaces, tool paths become one of the most critical factors for determining cutting forces. Here, the concept of force-minimal tool path generation is introduced and demonstrated for free form surfaces. Nowadays, process planning engineers must select the tool paths only from a set of ordinary tool paths available in CAM systems. These standard tool paths available in CAM systems are generated based on geometric computations only, not considering mechanics of processes, and most often these paths are away being optimum for free form surfaces. Here, a new methodology is introduced the first time for generating the tool paths based on process mechanics for globally minimizing the cutting forces for any given free form surface.