高速铣削SKD61模具钢表面完整性与疲劳寿命

为探究高速铣削加工中表面完整性对零件疲劳寿命的影响规律,使用圆环面铣刀对SKD61模具钢进行了高速铣削试验,并测定铣削后样件的表面完整性与疲劳寿命,根据表面完整性的量化指标,采用人工神经网络方法构建疲劳寿命预测模型。研究表明:铣削加工产生的表面残余压应力能显著延长零件的疲劳寿命。在一定范围内,零件的疲劳寿命分别随表面粗糙度和表面硬度的变化而剧烈变化。将表面完整性和人工神经网络相结合构建的零件疲劳寿命预测模型,其预测值与实测值的误差为2.3%~15.8%。     

Life prediction system using a tool’s geometric shape for high-speed milling

In recent years, machinery and tool technology has been developing rapidly. The accuracy of operations have also become more and more exact. Elsewhere, raw materials have also been honed, hoping to provide more useful properties than previously. Thus, how to find the best way to prolong the life of a tool subjected to hardened material cutting is the target of this research. Three kinds of tool angle of the endmill are used in this research; clearance angle, rake angle, and helical angle. The cutting conditions are the same; we only change the tool angle for all the cases studied. We attempt to discover better tool geometrical angles for the high-speed milling of NAK80 mold steel. The tool wear rate was measured through a toolmaker’s microscope and the roughness of the machined surface was measured by the roughness-measuring instruments after several complete surface layers were removed from the workpiece in the experiment. Also, a noise-mediator was used to detect the level of cutting noise during each surface layer workpiece removal of the high-speed milling process, and different noise levels were then compared with the tool wear rates for identifying noise characteristics in the case of an over-worn tool state. An abductive network was applied to synthesize the data sets measured from the experiments and the prediction models are established for tool-life estimation and over-worn situation alert under various combinations of different tool geometrical angles. Through the identification of tool wear and its related cutting noise, we hope to consequently construct an automatic tool wear monitoring system by noise detection during a high-speed cutting process to judge whether the tool is still good or not, and, so, the cost of milling can be reduced.     

The optimal design of micro end mill for milling SKD61 tool steel

Micromachining has become a necessary manufacturing method. Developing and applying micro-milling are determined according to the increasingly influential progress of micro tool designs and the evolution of machine tool technologies. This study employed a tungsten carbide micro end mill with a diameter of 200 μm for the design model of the micro-milling SKD61 tool steel by the finite element method. This study first used the effective rake angle on an oblique cutting process to simplify the complicated geometric relationship of the micro end mill into the orthogonal cutting model. Simulation analysis will be conducted by using the four parameters of effective rake angle, relief angle, cutting velocity, and cutting depth designed according to the Taguchi orthogonal array. This study then evaluated the four micro-milling characteristics of cutting force, tool maximum temperature, distance between the tool maximal temperature point and the tool tip point, and tool–chip contact length. The results of ANOVA show that the most influential simulation parameter on micro-milling is effective rake angle, followed by cutting velocity, cutting depth, and relief angle. The empirical results indicate that the proposed method can serve as a design base for developing and applying the micro end mill.     

An investigation of tool wear in high-speed turning of AISI 4340 steel

A commercially available insert has been used to turn an AISI 4340 steel at speeds placed between 325 and 1000 m/min. The flank wear was measured in connection to cutting time. This is to determine the tool life defined as the usable time that has elapsed before the flank wear has reached the criterion value.It is shown that an increase in cutting speed causes a higher decrease of the time of the second gradual stage of the wear process. This is due to the thin coat layer which is rapidly peeled off when high-speed turning.The investigation included the realization of a wear model in relation to time and to cutting speed. An empirical model has also been developed for tool life determination in connection with cutting speed.On the basis of the results obtained it is possible to set optimal cutting speed to achieve the maximum tool life.     

Analysis of force patterns and tool life in milling operations

The paper describes the practical effects of the operating parameters in the milling operation. Experiments have been conducted to measure cutting force and tool life under dry conditions. Based on the experimental results, three mathematical models have been developed: Force, TLife and Force/TLife. Further analyses have been conducted on the cutting force patterns: seasonal pattern and nonlinear trend. A process optimisation that is based on the minimum production cost has been applied to relate Force model, TLife model and machinability criteria, such as power consumption, cutting parameters and surface roughness.Nomenclature C _w cost of workpiece ($) - C _s set-up cost ($) - C _m machining cost ($) - C _o overhead cost ($) - C _r tool replacement cost ($) - C _t tool cost ($) - D diameter of the cutter (inch) - d depth of cut per pass (inch) - d ₀ required depth (inch) - e _t random error attth sample - F cutting force (N) - f feedrate (ipm) - L length of workpiece (inch) - N spindle speed (r.p.m.) - n number of teeth - P power of the motor (h.p.) - R surface roughness (µm) - R _e real part of a complex function - T tool life (min) - t sample number - t _m machining time (s) - t ₀ overhead time (s) - t _r tool replacement time (s) - t _s set-up time (s) - U _i unit cost of itemi ($/unit)v - v cutting speed (i.p.m.)     

The study of chip characteristics and tool wear in milling of SKD61 mold steel

In recent years, many machining applications have used dry cutting for high-speed cutting, for which, tool life prediction and research are important issues. In this study, a tungsten carbide tool cutting steel SKD61 was used, and the actual value of the chip shooting and the wear of the flank were determined using an industrial camera. The chip type and chip color are also discussed. After color calibration and chromaticity conversion, the model was trained through the neural network and the results were predicted. The tool wear curve and the theoretical curve were found to be closely related, and the chip color changed regularly. In the CIE XY chromaticity coordinate value, when the initial cutting was observed, the chip chromaticity coordinate point range was small, but as the wear amount increased, the chip chromaticity coordinate point range expanded gradually. The tool wear prediction established in this study was determined from the experimental results. The maximum errors of the test and verification were 0.031 mm and 0.022 mm. After calculation, the mean absolute percentage error (MAPE) was within 3 % and the accuracy level is MAPE is less than 10 %, so it has a high accurate prediction ability. Established tool wear predictions are also provided.

     

Cutter path orientations when high-speed finish milling inclined hardened steel

The use of high-speed milling (HSM) for the production of moulds and dies is becoming more widespread. Critical aspects of the technology include cutting tools, machinability data, cutter path generation and technology. Much published information exists on cutting tools and related data (cutting speeds, feed rates, depths of cut, etc.). However, relatively little information has been published on the evaluation of cutter paths for this application. Most of the research focuses on cutter path generation with the main aim on reducing production time. Work concerning cutter path evaluation and optimisation on tool wear, tool life and relevant workpiece machinability characteristics are scant. This paper investigates and evaluates the different cutter path orientations when high-speed finish milling inclined hardened steel, at a workpiece inclination angle of 75°. The results demonstrate that employing a vertical downward orientation achieved the longest life. However, in terms of workpiece surface roughness, vertical upward orientation is generally preferred.     

Adaptive modelling of the milling process and application of a neural network for tool wear monitoring

An adaptive signal processing scheme that uses a low-order autoregressive time series model is introduced to model the cutting force data for tool wear monitoring during face milling. The modelling scheme is implemented using an RLS (recursive least square) method to update the model parameters adaptively at each sampling instant. Experiments indicate that AR model parameters are good features for monitoring tool wear, thus tool wear can be detected by monitoring the evolution of the AR parameters during the milling process. The capability of tool wear monitoring is demonstrated with the application of a neural network. As a result, the neural network classifier combined with the suggested adaptive signal processing scheme is shown to be quite suitable for in-process tool wear monitoring     

FPGA-based reconfigurable system for tool condition monitoring in high-speed machining process

We present a reconfigurable system to detect and indicate online and in real time, the cutting tool conditions in high-speed face milling. It consists of a data acquisition system (DAS) and a hardware signal processing (HSP) unit. The DAS acquires and digitalizes the cutting vibration signals generated from machining tests performed under different tool conditions and cutting parameters. The HSP unit processes the digitalized vibration signals using reconfigurable IIR band-pass digital filter and statistical techniques, designed and implemented into a single field-programmable gate array (FPGA) and coefficients read-only memories. The system operation is divided into learning and monitoring modes. The tool condition is indicated by an alarm signal, one LED indicator, and a message shown on four-digit seven-segment displays. In all experiments, the system correctly detected the tool condition. The proposed system is fast, compact, reliable, and economical, and no modification of the machine-tool structure is required.     

Tool force and deflection compensation for small milling tools

A technique to compensate for deflection of small milling tools (diameter<1 mm) has been demonstrated. This open-loop technique involves predicting the cutting and thrust forces, applying these forces to the tool, calculating the shape error due to tool deflection and creating a new tool path to eliminate this error. The tool force model has evolved from a decade of research to predict the forces in diamond turning. This model was modified to include the effects of tool rotation in milling as well as the changes in contact area and force direction using a ball end mill to create a free form surface. Experimental measurements were made to corroborate the components of the tool forces in the cutting and thrust directions. The force model was then combined with tool stiffness to calculate the deflection of the tool as a function of the depth of cut, the up-feed per revolution and the geometry of the part. Two experiments were used to demonstrate the effectiveness of this error compensation technique—a slot and a large circular groove. Each experiment reduced the error due to tool deflection by an order of magnitude from 20–50 μm to 2–5 μm.     

高速铣削加工的数学模型建立和实验研究

在高速铣削机理研究中,铣削参数的应用实验研究是至关重要的.通过单因素和多因素实验,研究高速铣削参数对已加工工件表面粗糙度和表层残余应力的影响规律.实验表明,高速铣削能够获得较好的工件表面质量.     

Development of a novel cubic boron nitride cutting tool with a textured flank face for high-speed machining of Inconel 718

Nickel-based superalloys such as Inconel 718 offer several advantages, including high-temperature strength and high corrosion resistance; this has led to a rapid increase in the demand for such materials, particularly in the aircraft industry. In contrast, these alloys are known to be among the most difficult-to-cut materials because of their mechanical and chemical properties, and tools used for this purpose have extremely short lifetimes. Recently, cubic boron nitride (CBN), which is the second hardest of all known materials, has received significant attention as a material for cutting tools and has already established itself in many fields of application. However, the performance of CBN tools is still insufficient for practical use, especially in the high-speed machining of Inconel 718. To overcome this problem, we first conducted orthogonal cutting experiments on Inconel 718 and performed cross-sectional observations of the CBN cutting tool in order to identify its wear mechanisms in continuous cutting operations under high-speed machining conditions (300 m/min). As a result, it was found that fatal tool failure occurs through crater and flank wear because of diffusion led by high cutting temperatures and subsequent chip adhesion to the tool flank face, accompanied by cutting edge chipping. Based on these results, a CBN cutting tool with a textured flank face was newly developed to improve the cutting tool life. Experimental: results showed that micro grooves generated on the flank face significantly suppressed the cutting edge chipping and remarkably extended the lifetime of the CBN tool during high-speed machining of Inconel 718.     

The effects of cutting parameters on tool life and wear mechanisms of CBN tool in high-speed face milling of hardened steel

High-speed face milling of AISI H13 hardened steel is conducted in order to investigate the effects of cutting parameters on tool life and wear mechanisms of the cubic boron nitride (CBN) tools. Cutting speeds ranging from 400 to 1,600 m/min are selected. For each cutting speed, the metal removal rate and axial depth of cut are fixed, and different combinations of radial depth of cut and feed per tooth are adopted. The tool life, tool wear progression, and tool wear mechanisms are analyzed for different combinations of cutting parameters. It is found that for most of the selected cutting speeds, the tool life increases with radial depth cut and then decreases. For each cutting speed, the CBN tool life can be enhanced by means of adopting suitable combination of cutting parameters. When the cutting speed increases, the normal wear stage becomes shorter and the tool wear rate grows larger. Because of the variations of cutting force and tool temperature, the tool wear mechanisms change with different combinations of cutting parameters even at the same cutting speed. At relatively low cutting speed, in order to acquire high tool life of the CBN tool, the tool material should possess sufficient capability of resisting adhesion from the workpiece. When relatively high cutting speed is adopted, retention of mechanical properties to high cutting temperature and resistance to mechanical impact are crucial for the enhancement of the CBN tool life.     

General tool correction for five-axis milling

In this paper a method is presented by which cutter location data can be determined for any type of milling tools defined according to DIN 66215 whereby any point of the tool can be defined as the contact point. In addition, the cutter location point for 5-axis milling can be determined using a single formula for any type of milling tool.     

A standardized model for the evaluation of machining coolant/lubricant costs

Compliance with environmental regulations is becoming more and more costly for manufacturers as government scrutiny and global trade agreements become more stringent. Metal-cutting fluid use and disposal is a major concern as these environmental issues become more prominent. Gaining a clear understanding of the costs associated with machining coolant/lubricant use can be difficult. Many factors impact this cost, such as the original purchase price, maintenance costs, disposal management and fees, and performance factors related to the particular fluid. This paper develops a detailed cost and performance-based methodology for machining coolant/lubricant selection. A model by which to evaluate the relative impacts of coolant/lubricant decisions on the unit workpiece cost of production is described. At present, a widely accepted methodology is not available for this purpose. The model presented here will assist manufacturing companies of all types in making this critical decision.     

Monitoring of tool fracture in milling

For untended manufacturing operations, in-process monitoring of tool fracture plays a critically important role. A tool fracture feature in the spectrum of the displacement signal of the spindle in milling has been discovered. Therefore, a new signal processing algorithm called the band-limited average energy method using the tool fracture feature to monitor tool fracture is proposed. The energy content of the tool fracture feature is extracted and normalised to detect tool fracture. It is shown, by theoretical studies and experimental results, that tool fracture can be detected under varying cutting conditions in milling.     

Effect of tool stiffness upon tool wear in high spindle speed milling using small ball end mill

Longer tool life can be tentatively achieved at a higher feed rate using a small ball end mill in high spindle speed milling (over several tens of thousands of revolutions per minute), although the mechanism by which tool life is improved has not yet been clarified. In the present paper, the mechanism of tool wear is investigated with respect to the deviation in cutting force and the deflection of a ball end mill with two cutting edges. The vector loci of the cutting forces are shown to correlate strongly with wear on both cutting edges of ball end mills having various tool stiffnesses related to the tool length. The results clarified that tool life can be prolonged by reducing tool stiffness, because the cutting forces are balanced, resulting in even tool wear on both cutting edges as tool stiffness is lowered to almost the breakage limit of the end mill. A ball end mill with an optimal tool length showed significant improvement in tool life in the milling of forging die models.     

An economic and reliable tool life estimation procedure for turning

The conventional methods of tool life estimation take a long time and consume a lot of work piece material. In this paper, a quicker method for the estimation of tool life is proposed, which requires less consumption of work piece material and tools. In this method the tool life is estimated by fitting a best-fit line on the data falling in the steady wear zone and finding the time till tool failure by extrapolation. Neural networks are used to predict lower, upper and most likely estimates of the tool life. Comparison between neural networks and multiple regression shows the superiority of the former. The paper also proposes a methodology for continuous monitoring of tool use in the shop floor and updating/obtaining the tool life estimates based on the shop floor feed back.     

教学型加工中心刀库结构及控制软件设计

这里以V400立式加工中心刀库设计为例,探讨了教学型加工中心刀库结构的特点,并针对基于IPC的模块化开放式数控系统,提出了刀库控制系统软件的实现方法。     

An intelligent sensor fusion system for tool monitoring on a machining centre

The objective of this paper is to construct an intelligent sensor fusion monitoring system for tool breakage on a machining centre. Since none of the sensing and diagnosis techniques have proved to be completely reliable in practice, an intelligent tool-monitoring system consisting of a neural-network-based algorithm and a sensor fusion system is proposed. The dual sensing signals of cutting force and acoustic emission are used simultaneously in the proposed system owing to good correlation existing between them, and, a self-learning neural-network algorithm is used to integrate multiple sensing information to make a proper decision about tool condition. The results show good performance in tool-breakage detection by the proposed monitoring system, especially where there is high interference.