聚晶立方氮化硼刀具磨损与寿命研究综述

聚晶立方氮化硼(PCBN)是一种超硬刀具材料,由于其具有硬度高、化学稳定性和热稳定性好等优点,已经被广泛应用于汽车、航空航天、能源等领域的机械零部件加工。文中分析了PCBN刀具的主要磨损形式及其原因,并从刀具材料构成和几何形状、工件材料以及切削条件3个方面总结了影响PCBN刀具磨损和寿命的主要因素,最后介绍了切削参数优化和添加涂层等方法在提高刀具耐磨性与寿命方面的应用。     

非对称双极脉冲磁控溅射沉积氮化铬铝涂层的微观结构和硬度

利用非对称双极脉冲磁控溅射技术,双极分别接纯铬靶和纯铝靶,通过调整两靶的功率,以反应溅射的方式沉积不同铬铝比的氮化铬铝涂层。研究不同Al含量的氮化铬铝涂层的结构和硬度。所获得的涂层依次为Cr0.95Al0.05N、Cr0.9Al0.1N、Cr0.83Al0.17N和Cr0.75Al0.25N,均为B1NaCl结构,(220)为主要的织构取向。随着涂层中Al含量的增加,涂层表面突起的尺寸逐渐降低,涂层趋于光滑致密;低Al含量涂层为柱状晶结构,随Al含量提高,涂层结构更加致密,并向等轴晶结构转变。涂层硬度随Al含量的提高先增加后降低,Cr0.83Al0.17N涂层表现出最高的硬度,维氏硬度达到33GPa以上。     

AISI 4340高强钢高速硬车削下PCBN刀具磨损机理

PCBN刀具在硬切削加工中磨损严重,探究PCBN刀具的磨损机理,能够为改善刀具切削性能、提高加工效率提供指导.采用PCBN刀具进行高速硬车削AISI 4340高强钢试验,研究不同切削速度下的PCBN刀具的磨损形式及磨损机理.通过对比三种切削速度(v=150 m/min、210 m/min、300 m/min)切削两种硬...     

PCBN刀片新牌号的开发与应用

自从几十年前材料科学家们采用类似合成人造金刚石的工艺方法首次合成出聚晶立方氮化硼（PCBN）以来，PCBN刀具在机械加工中的应用已日渐广泛。PCBN材料的硬度仅次于金刚石，但与金刚石刀具不同的是，PCBN刀具能够用于切削加工铁族合金，甚至包括硬度高于60HRC的淬硬钢。     

PCBN超硬刀具研究与进展

现代刀具切削速度的不断提高和先进的集成制造系统的发展对现代刀具的性能提出了更高的要求,刀具材料质量、性能和可靠性直接影响生产效率和加工质量,也直接影响整个制造行业的生产技术水平和经济效益,所以开发高稳定性和良好耐磨性的超硬刀具是当今的发展趋势。本文介绍了超硬材料PCBN超硬刀具的国内外发展概况和刀具性能应用,PCBN超硬刀具材料的制备方法及刀具制造过程,PCBN超硬刀具的断屑槽、修光刃结构以及新型PCBN超硬刀具,刀具车削仿真的相关研究等;并对PCBN超硬刀具及整个刀具行业的前景进行展望。      

多层CVD涂层PCBN

肯纳金属公司最近推出CVD多层“铝基”多层涂层新PCBN牌号KB9640,并声称是世界上唯一提供这种整体PCBN基体与最大韧性和CVD铝基涂层相结合制造商,这种结合被认为是抗化学碎裂和月牙洼的最佳保护层。高CBN含量的整体、非常硬的PCBN与CVD铝基多层涂层相结合具有很多优点,包括PCBN基体的高断裂韧性及其在大的切削深度下必然的韧化适应性。可用于两边的多刃刀片获得极具经济价值的利润率。据称与非涂层PCBN牌号比较,CVD铝基多层涂层因其改进的抗月牙洼性能,可提供耐热和抗化学磨损的最好保护,并且延长刀具寿命。高完整性的涂层改…     

PCBN刀具硬态车削的磨损机制研究

PCBN刀具用于高速切削、硬态切削、干切削以及加工自动化和难加工材料等先进切削工艺时显示出了卓越的性能,为了推动PCBN刀具在我国的推广使用,充分发挥PCBN刀具的潜能,有必要对PCBN刀具切削过程中的行为规律进行研究。目前国内外已经有很多这方面的研究报道,本文旨在对前人已进行的工作进行一个系统的总结,以期能得到PCBN硬态车削时的主要的磨损机制。     

PCBN刀具切削性能和磨损机理研究综述

聚晶立方氮化硼(PCBN)刀具是继聚晶金刚石刀具之后的又一种超硬刀具,以其独特的“以车代磨”、“硬态加工”、“干式切削”等方式被誉为21世纪的绿色环保刀具。PCBN刀具在金属切削方面具有广泛的应用,主要用来加工各种淬硬钢、耐磨铸铁等铁基材料。本文介绍了PCBN刀具成分、几何形状、切削参数等对其切削性能的影响,在此基础上分析了不同材料加工时刀具的主要磨损机理,还简单对比了硬质合金和PCBN刀具切削性能上的差异。      

加工汽车零件用PCBN刀具

日本住友电工HARDMETAL公司推出两类用于切削加工汽车零件的PCBN刀具。一类主要用于加工铁基粉末冶金工件和铸件，其特点是刀具材料中的CBN含量（体积百分比）在80％以上，结合剂为Co、Al化合物。该类PCBN刀具分为BN700、BN800、BN600三个牌号，硬度、强度和热传导性优异；另一类主要用于加工淬硬钢、     

Sandvik、Ceram Tec公司新产品

瑞典 Sandvik硬质合金材料公司最近开发出新的低粘结剂含量 PCBN牌号 (5 0 %立方氮化硼 )— NT5 ,特别适用于淬硬钢的从连续到轻断续切削 (例如车削和开槽 )精加工。晶粒度大约为 1 .5μm,硬度 >2 60 0 HV3 ,弹性模量 5 60 GPa。典型的应用领域包括汽车和运输业用表面淬硬和完全淬硬钢部件。 NT5在球状轴承钢的连续加工中亦很有效。NT5将极好的化学稳定性与显著的高韧性、刃保持力和研磨性结合起来。标准的坯件直径 5 5 mm,厚 1 .6或 3 .2 mm,PCBN层厚度分别为 0 .7mm和 0 .9mm。基体为硬质合金。德国 Ceram Tec公司因推出涂层氮化…     

Evaluation of the performance of CBN tools when turning Ti–6Al–4V alloy with high pressure coolant supplies

Cubic Nitride Boron (CBN) tools are generally used for machining harder alloys such as hardened high Cr steels, titanium and nickel alloys. The tools are expected to withstand the heat and pressure developed when machining at higher cutting conditions because of their high hardness and melting point. This paper evaluates the performance of different CBN tool grades in finish turning Ti–6Al–4V (IMI 318) alloy at high cutting conditions, up to 250 m min⁻¹, with various coolant supplies. Tool wear, failure modes, cutting and feed forces and surface roughness of machined surfaces were monitored and used to access the performance of the cutting tools. Comparative trials were carried out with uncoated carbide tools when machining at a speed of 150 m min⁻¹. Test results show that the performance of CBN tools, in terms of tool life, at the cutting conditions investigated is poor relative to uncoated carbide tools, as expected and often, reported due probably to rapid notching and excessive chipping of the cutting edge associated with a relatively high diffusion wear rate that tends to weaken the bond strength of the tool substrate. An increase in the CBN content of the cutting tool also led to a reduction in tool life when machining at the cutting conditions investigated.     

PcBN刀具连续车削淬硬钢性能的研究

为了研究PcBN刀具在干式连续车削条件下刀具的性能,选用两种不同的PcBN刀具,在不同切削速度及不同工件硬度条件下,对淬硬钢进行车削试验。在此基础上,对刀具前、后刀面的显微形貌特征进行了观察,分析了刀具的失效机理。结果表明:切削速度对刀具的切削寿命影响很大,随着切削速度的增加刀具寿命几乎线性下降。硬度也是影响刀具切削寿命的重要因素之一,当v190 m/m in时,刀具切削硬度为(64±1)HRC工件的寿命比相同条件下切削硬度为(61±1)HRC工件的寿命下降约40%~60%。刀尖温度随着切削速度的增加不多,切屑温度要比刀尖温度高出许多。在本试验中,刀具的失效判据为崩刃或后刀面平均磨损超过0.3 mm。     

Prediction of flank wear by using back propagation neural network modeling when cutting hardened H-13 steel with chamfered and honed CBN tools

Productivity and quality in the finish turning of hardened steels can be improved by utilizing predicted performance of the cutting tools. This paper combines predictive machining approach with neural network modeling of tool flank wear in order to estimate performance of chamfered and honed Cubic Boron Nitride (CBN) tools for a variety of cutting conditions. Experimental work has been performed in orthogonal cutting of hardened H-13 type tool steel using CBN tools. At the selected cutting conditions the forces have been measured using a piezoelectric dynamometer and data acquisition system. Simultaneously flank wear at the cutting edge has been monitored by using a tool makers microscope. The experimental force and wear data were utilized to train the developed simulation environment based on back propagation neural network modeling. A trained neural network system was used in predicting flank wear for various different cutting conditions. The developed prediction system was found to be capable of accurate tool wear classification for the range it had been trained.     

Coating optimisation for high speed machining with advanced nanomechanical test methods

Advanced nanomechanical testing has been used to evaluate key factors influencing tool life (1) a plasticity index (PI, the plastic work done/total work done during indentation), at room and elevated temperature (2) hot hardness and (3) fatigue fracture resistance, and determine their relative importance in different cutting applications. The optimum combination of hardness and toughness/plasticity to minimise wear and extend the life of coated WC-Co cutting tools was found to vary with the severity and nature of the cutting conditions. For interrupted cutting the plasticity index is critical, with high values (i.e. not extremely high H/E) resulting in extended tool life. Elevated temperature nanoindentation showed decreasing hardness and increasing PI with temperature. In high-speed turning hot hardness is the dominant factor whilst for interrupted cutting high hot hardness should be combined with improved plasticity for longer tool life. A novel test technique nano-impact, was used to simulate the interrupted contact (and cyclic loading) conditions occurring in milling applications and evaluate the fatigue fracture resistance of coated tools. It was able to successfully rank coatings in terms of tool life in end milling and reproduce the evolution of tool wear in the cutting test. In elevated temperature nano-impact testing the probability and extent of fracture during the test decreased at elevated temperature, consistent with the higher PI. Results from the advanced nanomechanical tests can be used in combination to predict which coatings have longer life in severe cutting conditions.     

Effects of cutting geometry in turning with TiN-coated tools

The effects of cutting tool geometry on the performance of TiN-coated high-speed steel tools were studied. Turning tests were carried out with inserts made of conventional and powder metallurgical HSS. The workpiece material was a case hardening steel with a hardness of 170 HB. Two different cutting geometries were used. In addition to altering the cutting angles, the effect of honing the cutting edge before coating was studied. The results showed clearly that even small changes in the tool angles affect the performance of the TiN-coated tool. Honing the cutting edge significantly increased wear resistance by improving the edge strength and reducing microchipping. On the basis of the results the modification of cutting tool geometry for hard coatings is discussed.     

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。     

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.     

等离子弧加热车削工艺的研究

采用等离子弧加热车削加工高强度和高硬度轴类零件的方法,是一种经济高效的机械加工方法,本文通过等离子弧加热切削刀具材料选择试验、刀具几何角度选择试验、粗车和半精车试验,建立了刀具材料、刀具几何角度与有关工艺参数之间的关系,得出了加工时的有关最佳工艺参数.     

大应变切削制备的超细晶纯铜切屑热稳定性的研究

采用不同前角的刀具对纯铜进行大应变切削加工,对获得的超细晶纯铜切屑进行不同温度的退火处理.利用扫描电子显微镜(SEM)和维氏硬度测量仪进行检测,分析不同前角和退火温度对超细晶纯铜切屑微观组织和力学性能的影响.结果表明:用0°前角刀具进行大应变切削加工后,切屑晶粒平均尺寸为0.3μm、硬度为160HV,在200～280℃...     

Statistical analysis of the effects of machining parameters and workpiece hardness on the surface finish of machined medium carbon steel

The objective of this study is to ascertain the effect of machining parameters and workpiece hardness on surface roughness of machined components and to develop a better understanding of the effect of process parameters on the machined surface. Such an understanding can provide insight into the problems of controlling the finish of machined surfaces when the process parameters are adjusted to obtain a certain surface finish. The collected data were analyzed using parametric analyses of variance (ANOVA) with surface finish as the dependent variable and hardness of the workpiece material, cutting tool position from the surface of the clamping device (chuck), depth of cut, cutting velocity, and cutting feed as independent variables. The results showed that surface roughness is significantly affected by the workpiece hardness, cutting feed, cutting speed, depth of cut, cutting tool position from the chuck, and their interactions with each other. The results suggest that feed rate and cutting speed can be adjusted to produce a certain surface finish when the position of the cutting tool from the surface of a clamping device or the hardness of the workpiece is changed.