Investigation of the torque characteristics in vibration tapping of hardened steel

Vibration tapping is presented in this paper to solve this problem, as high-speed steel tap is incapable of tapping small-hole (M3) in hardened steel (50HRC). Theoretical analysis with fracture mechanics indicates that the impact effect of the tap on the workpiece results in increased II-type stress intensity factor and extended micro cracks, leading to lower plastic deformation, reduced cutting forces and a much lower tapping torque, and the torsional rigidity of the tap is enhanced in vibration tapping as proved by dynamic analysis. The experimental results show that with well chosen amplitudes, tapping torque decreases as vibration frequency increases, and tapping torque increases as net cutting time ratio increases, where net cutting time ratio influences the tapping torque more significantly. Vibration tapping is then proved to be a practical solution to the problem of small-hole tapping in hardened steel.     

A study of high-performance plane rake faced twist drills. Part II: Predictive force models

Predictive cutting models for the thrust, torque and power in drilling operations using modified plane rake faced twist drills are presented and discussed. The models are based on the mechanics of cutting approach incorporating the many tool and cutting process variables and have been assessed by numerically analysing the predicted trends and by comparing with the experimental data. It is shown that the model predictions are in excellent agreement with the experimental results with an average deviation of about 5%. Simpler “empirical-type” thrust, torque and power equations are also established for use as an accurate alternative to the complex predictive models to facilitate practical applications.     

Investigation of thread tapping load characteristics through mechanistics modeling and experimentation

A mechanistic model for the prediction of tapping torque and axial force is developed. The model is capable of predicting tapping torque and axial force resulting from chip formation and tool flank/workpiece friction under various machining conditions, including dry tapping and tapping with different cutting fluids. Extensive tests on tapping torque and axial force measurements are conducted to verify the predictive model. Characteristics of the measured tapping loads are studied. It is found that the total tapping load consists of a base load and a chip packing load. The base load results from chip formation and tool/workpiece friction. The predicted tapping load is found to be in good agreement with measured base load. The chip packing load is the result of chip clogging in the flutes, and is random in nature. The chip packing load may be many times that of the base load, depending on tap geometries and the machining conditions. Factors causing severe chip clogging and excessive torque leading to tap breakage are also reported.     

A study of high-performance plane rake faced twist drills.: Part I: Geometrical analysis and experimental investigation

A study of a modified drill point design with plane rake faces for drilling high-tensile steels is presented. A geometrical analysis has shown that the modified drill point design yields positive normal rake angle on the entire lips and point relieving in the vicinity of the chisel edge. This drill geometry can be expected to reduce the cutting forces and torque, and hence reduce the possible drill breakages when drilling high-tensile steels. An experimental study of drilling an ASSAB 4340 high-tensile steel with 7–13 mm titanium nitride (TiN) coated high-speed steel (HSS) drills has shown that the modified drills can reduce the thrust force by as much as 46.9%, as compared to the conventional twist drills under the corresponding cutting conditions, while the average reduction of torque is 13.2%. Drill-life tests have also been carried out and confirmed the superiority of the modified drills over the conventional twist drills. In some cases, the conventional drills were broken inside the workpiece, while the modified drills performed very well under the same cutting conditions. To mathematically predict the drilling performance and optimise the drilling process using the plane rake faced drills, predictive models for the cutting forces, torque and power will be developed in the second part of this investigation.     

Theoretical and experimental analysis of nano-surface generation in ultra-precision raster milling

The fabrication of high-quality freeform surfaces is based on ultra-precision raster milling, which allows direct machining of the freeform surfaces with sub-micrometric form accuracy and nanometric surface finish. Ultra-precision raster milling is an emerging manufacturing technology for the fabrication of high-precision and high-quality components with a surface roughness of less than 10 nm and a form error of less than 0.2 μm without the need for any additional post-processing. Moreover, the quality of a raster milled surface is based on a proper selection of cutting conditions and cutting strategies.Due to different cutting mechanics, the process factors affecting the surface quality are more complicated, as compared with ultra-precision diamond turning and conventional milling, such as swing distance and step distance. This paper presents a theoretical and experimental analysis of nano-surface generation in ultra-precision raster milling. Theoretical models for the prediction of surface roughness are built. An optimization system is established based on the theoretical models for the optimization of cutting conditions and cutting strategy in ultra-precision raster milling. A series of experiments have conducted and the results show that the theoretical models predict well the trend of the variation of surface roughness under different cutting conditions and cutting strategies.     

A hybrid approach to integrate machine learning and process mechanics for the prediction of specific cutting energy

Specific cutting energy is an important concept because it affects not only surface integrity but also process sustainability. However, the predictive power of traditional analytical models for specific energy is significantly limited by the complex mechanical–thermal coupling in cutting. This paper has proposed a new hybrid approach to integrate data-driven machine learning and process mechanics for the prediction of specific cutting energy. Compared to traditional analytical models, the accuracy of the hybrid approach has been validated in milling of H13 tool steel and Inconel 718. The predictive model is also transferable to other cutting processes.     

Effects of Synchronizing Errors on Cutting Performance in the Ultra-High-Speed Tapping

Synchronizing errors between the spindle motor and the z-axis motor directly influences the cutting characteristics in tapping, because the tapping process is accomplished by synchronizing the movement of the z-axis with the revolutionary spindle motion. The excessive synchronizing error can cause tap breakage due to the abrupt increase of cutting torque or damage the thread accuracy by overcutting the already cut threads. This paper describes the effects of the synchronizing errors on the cutting performance in the ultra high-speed tapping and presents a minimum level of synchronizing errors necessary to maintain the quality of the cut thread.     

The investigation on the prediction of tool wear and the determination of optimum cutting conditions in machining 17-4PH stainless steel

The purpose of this paper is to develop a predictive model for the prediction of tool flank wear and an optimization model for the determination of optimum cutting conditions in machining 17-4PH stainless steel. The back-propagation neural network (BPN) was used to construct the predictive model. The genetic algorithm (GA) was used in the optimization model. The Taguchi method (TM) was used to find the optimum parameters for both models, respectively. Two steps of experiments have been carried out by machining 6 mm length and 90 mm length of the workpiece, respectively. The experimental scheme was arranged by using an orthogonal array of TM. It has been shown that the predictive model is capable of predicting the tool flank wear in an agreement behavior. The optimization model has also been proved that it is a convenient and efficient method to find the optimum cutting conditions associated with the maximum metal removal rate (MMRR) under different constraints. The constraint is the tool flank wear that can be determined from the predictive model. Furthermore, the systematic procedure to develop the models in this paper can be applied to the usage of the predictive or optimized problems in metal cutting.     

基于AdvantEdge的直槽丝锥工艺参数优化

为改善316 L不锈钢材料的攻丝性能,研究以性能指标轴向力、扭矩、温度最低为优化目标,采用单因素试验和全因素试验设计相结合的方法,对影响攻丝性能的直槽丝锥工艺参数(主轴转速、丝锥涂层、切削液种类)进行优化;基于AdvantEdge软件进行攻丝数值模拟,采用熵权分析法确定最佳工艺参数组合,并通过对比试验验证了优化工艺后的...     

Fundamental studies of driven and self-propelled rotary tool cutting processes—II. Experimental investigation

An extensive experimental investigation has been carried out to verify the developed mechanics of cutting analyses for the fundamental driven and self-propelled rotary tool cutting processes. This involved testing the dynamic or perfect equivalence between the rotary tool and equivalent classical processes over a wide range of inclination angles, cut thickness and rake angles using statistical processing techniques. The collinearity conditions at the shear plane and rake face have also been tested as part of the model verification. It has been shown that all the force components, deformation and basic cutting parameter trends and quantities required for perfect equivalence have been satisfied as were the necessary collinearity conditions. The verified models provide a deeper understanding of the cutting mechanics and characteristics of these ingenious material removal operations and form the basis for the development of predictive cutting models for the fundamental and complex practical rotary tool operations.     

步进式振动攻螺纹优越性的理论证明

建立了步进式振动攻螺纹的理论模型，证明了步进式振动攻螺纹相对于普通攻螺纹能够降低平均切削扭矩和提高丝锥的动刚度。     

A cutting force model for finishing processes using helical end mills with significant runout

Analytical cutting force models play an important role in a wide array of simulation approaches of milling processes. The accuracy of the simulated processes directly depends on the predictive power of the applied cutting force model, which may vary under specific circumstances. End milling processes with small radial cutting depths, e.g. finishing processes, are particularly problematic. In this case, the tool runout, which is usually neglected in established cutting force models, can become quite significant. Within this article, well-known cutting force models are implemented for runout-prone finishing processes and modified by integrating additional parameters. A method is presented for how these additional runout parameters can be efficiently determined alongside commonly used cutting coefficients. For this purpose, a large number of milling experiments have been performed where the cutting forces were directly measured using a stationary dynamometer. The measured cutting forces were compared with the simulated cutting forces to verify and assess the modified model. By using the presented model and calibration method, cutting forces can be accurately predicted even for small radial cutting depths and significant tool runout.     

Modelling and prediction of cut shape for plasma arc cutting based on artificial neural network

Abstract

An artificial neural network approach for the modelling of plasma arc cutting processes is introduced. Neural network models have been proposed for predicting the cut shape and estimating the special cutting variables. The implementation of artificial neural networks in the modelling of cutting processes is discussed in detail. The performance of the neural networks in modelling is presented and evaluated using actual cutting data. Moreover, prediction applications of the above neural network models are described for various cutting conditions. It is shown that estimated results based on the proposed models agree well with experimental data; the neural network models yield good prediction results over the entire range of cutting process parameters spanned by the training data. The testing and prediction results show the effectiveness and satisfactory prediction accuracy of the artificial neural network modelling. The developed models are applicable to carbon steel.     

Tapping of Al–Si alloys with diamond-like carbon coated tools and minimum quantity lubrication

The deep hole drilling and tapping of automotive powertrain components made of hypoeutectic Al–Si alloys are of considerable importance. This work investigates the dry and minimum quantity lubricated (MQL) tapping of Al–6.5%Si (319 Al) alloys as alternatives to conventional flooded tapping. Two types of tests were done in comparison with flooded tapping. In the first set dry tapping experiments were performed using diamond-like carbon (DLC) coated and uncoated HSS taps. HSS-dry tapping caused immediate tool failure within less than 20 holes due to aluminum adhesion, resulting in high forward and backward torques. DLC-dry tapping improved tool life considerably and exhibited small torques. The second set of tapping experiments used MQL and only uncoated HSS taps. The use of MQL at the rate of 80 ml/h produced similar average torques to flooded tapping, and a high thread quality was observed. DLC coatings’ low COFs against 319 Al limited the temperature increase during DLC-dry tapping to 75 °C. The low COF of DLC against aluminum was responsible for preventing built-up edge (BUE) formation and thus, instrumental in improving thread quality. The use of MQL reduced the tapping temperature to 55 °C. The mechanical properties of the material adjacent to tapped holes, evaluated using hardness measurements, revealed a notable softening in the case of HSS-dry tapping, but not for MQL tapping. The presence of sulphur and phosphorus-based additives in MQL fluids proved beneficial in preventing aluminum adhesion.     

A thermo-mechanical model of dry orthogonal cutting and its experimental validation through embedded micro-scale thin film thermocouple arrays in PCBN tooling

Cutting temperature and its distribution in the cutting zone are a critical factor that significantly affects tool life and degrades part accuracy during metal removal operations. However, issues surrounding their modeling and experimental validation in the immediate cutting zone still remain an unresolved issue. A major impediment is the unavailability of adequate temperature measurement methods with sufficient temporal and spatial resolution to measure actual temperatures and validate predictive models. In this paper, a model for the dry orthogonal cutting process with thermo-mechanical coupling effects, i.e., interactions between the stress state, strain rates and the temperature softening of material in the plastic deformation zone, is proposed to predict cutting temperature distribution in the cutting zone. The feasibility and prediction accuracy of the model is verified by experimental measurements through Thin Film Thermocouple (TFTC) arrays embedded at the immediate vicinity of the cutting zone into Polycrystalline Cubic Boron Nitride (PCBN) tooling. The experimental verification is performed under hard turning conditions. It has been shown that the predictions of the proposed model are in very close agreement with the experimentally measured results including the cutting forces, chip thickness and cutting temperature distributions on the rake and flank faces in the cutting zone. Furthermore, the modeling results have also provided an essential understanding on the stress distributions at the tool/chip and work/tool interfaces as well as of the nature of the chip flow velocity along the rake face of the cutting tool.     

Analytical modeling and experimental investigation of tool and workpiece temperatures for interrupted cutting 1045 steel by inverse heat conduction method

Cutting temperature is a key factor which directly affects tool wear, workpiece integrity, and machining precision in high speed machining process. The interrupted cutting process consists of several periodical characteristics, such as cutting force and time varying heat source. Induced cutting temperature models with time varying heat flux are developed in this paper to predict temperature distribution at tool inserts and workpiece during interrupted cutting process. A set of interrupted cutting experimental installation is designed to verify the proposed models. The comparison of predicted and measured results for 1045 steel in interrupted cutting processes shows reasonable agreement. The measured temperature of both the tool inserts and workpiece increase firstly and then decrease as the cutting speed increases. The peak temperature of the workpiece appears at 1500 m/min, while the peak tool inserts temperature appears at 1250 m/min approximately. Heat flux is calculated by the inverse heat conduction method. The applicability of Salomon's hypothesis to the temperature of tool inserts and workpiece is discussed during the interrupted cutting process. The dropped temperature at high cutting speed is mainly caused by that heat flux into tool inserts decreases and heat transfer time is not enough after the critical cutting speed.     

Investigation of the effects of tool micro-geometry and coating on tool temperature during orthogonal turning of quenched and tempered steel

Reliable information about tool temperature distribution is of central importance in metal cutting. Application of dedicated charge-coupled device (CCD) sensor based near infrared (0.85–1.1 μm) imaging technique to the orthogonal turning of quenched and tempered steel is presented. Special attention was paid to the role of calibration on the interpretation of isotherms. Experimental results from systematic studies devoted to the role of heat source width, cutting parameters, edge micro-geometry and coating indicate the flexibility and reliability of this approach. Results compare favourably with those from other techniques capable of indicating tool isotherms as well as with numerical models based on FEM.     

数控机床切削性能检测实验方法研究

数控机床作为现代制造业的核心装备之一,直接反映国家的整体技术和经济水平。分别讨论了数控机床满负荷切削、曲线切削、标准件切削和刚性攻丝实验,用于考核评价机床的负荷能力、动态性能、切削精度和螺纹加工能力,对于企业优化机床的切削性能、提高机械产品的加工质量具有实际参考价值。     

钛合金材料内螺纹加工新方法

钛合金材料由于存在硬度高、强度大等特点,在进行内螺纹加工过程中刀具经常损坏.通过分析振动攻丝和挤压攻丝的特点,提出振动挤压攻丝方法.从钛合金金属流变规律角度分析了振动挤压攻丝的工艺特点,给出了一种振动挤压攻丝机的原理.采用振动挤压攻丝新方法对钛合金材料进行内螺纹加工,螺纹表面硬度高,丝锥损坏现象显著减小.     

Estimation of heat conduction losses in laser cutting

Numerical models of laser cutting are essential for an improved understanding of the process. In order for the models to closely represent real physics the heat lost by conduction during cutting has to be incorporated into them. This paper outlines the details of a mathematical model that is used to estimate heat conduction losses in laser cutting by employing integral methods to solve the three-dimensional, heat-conduction equation. Simple, yet accurate, correlations are presented for the conduction heat loss rate, as well as for characteristic thicknesses of the heat affected zone (HAZ). These variables are functions only of Peclet number (Pe), which may be thought of as a dimensionless cutting speed. The correlations are then used to predict (i) the cutting speed in laser cutting, and (ii) the temperature field in the HAZ. The predictions show an excellent match with experimental results. Cutting speed is predicted using an energy balance at the cutting front. An implicit, nonlinear equation for Pe as a function of Stefan number (Ste) and dimensionless heat of combustion results. Ste gives the ratio of sensible heat to latent heat in the workpiece. Detailed analysis of beam absorptivity, coupled with the dimensionless cutting speed result suggests that the dimensional cutting speed, u_o, may be correlated as a unique function of the ratio of incoming laser power to workpiece thickness, Q_las/d. This is corroborated by measured cutting rates over a wide range of sample thicknesses and two beam power settings.