数控加工仿真系统的研究与应用

介绍数控加工仿真系统的整体设计,提出格栅voxel三维实体建模方法,刀具扫描体的生成算法,实现了刀具切削工件过程的动态仿真,并对碰撞检查算法进行了初步的研究.基于以上方法,建立了蓝天数控系统的加工仿真系统,在加工前对加工程序进行验证,在加工时对刀具轨迹的执行、工件的切削过程等进行实时监控.     

Investigation and FEA-based simulation of tool wear geometry and metal oxide effect on cutting process variables

In machining, it is clearly noticed that the cutting tool wear influences the cutting process. However, it is difficult with experimental methods to study the effects of tool wear on several machining variables. Thus, in the literature, some earlier studies are performed separately on the effect of tool flank wear and crater wear on cutting process variables (such as cutting forces and temperature). Furthermore when the workpiece material adheres in cutting tool, it affects considerably the heat transfer phenomena. Accordingly, in this work the finite element analysis (FEA) is performed to investigate the influence of combination of tool flank and crater wear on the local or global variables such as cutting forces, tool temperature, chip formation on the one hand and the effects of the oxidized adhesion layer considered as oxide (Fe₂O₃/Fe₃O₄/FeO) on the heat transfer in cutting insert on the other hand. In this investigation, an uncoated cutting insert WC–6Co and medium carbon steel grade AISI 1045 are used. The factorial experimental design technique with three parameters (cutting speed Vc, flank wear land VB, crater wear depth KT) is used for the first investigation without adhesion layer. Then, only linear investigation is performed. The analysis has shown the influence of the different configurations of the tool wear geometry on the local or global cutting process variables, mainly on temperature and cutting. The simulation’s results show also, the highly influence of the oxidized adhesion layer (oxide Fe₂O₃/Fe₃O₄/FeO) on the heat transfer.     

Condition monitoring of CNC machining using adaptive control

In this work, an adaptive control constraint system has been developed for computer numerical control (CNC) turning based on the feedback control and adaptive control/self-tuning control. In an adaptive controlled system, the signals from the online measurement have to be processed and fed back to the machine tool controller to adjust the cutting parameters so that the machining can be stopped once a certain threshold is crossed. The main focus of the present work is to develop a reliable adaptive control system, and the objective of the control system is to control the cutting parameters and maintain the displacement and tool flank wear under constraint valves for a particular workpiece and tool combination as per ISO standard. Using Matlab Simulink, the digital adaption of the cutting parameters for experiment has confirmed the efficiency of the adaptively controlled condition monitoring system, which is reflected in different machining processes at varying machining conditions. This work describes the state of the art of the adaptive control constraint (ACC) machining systems for turning. AISI4140 steel of 150 BHN hardness is used as the workpiece material, and carbide inserts are used as cutting tool material throughout the experiment. With the developed approach, it is possible to predict the tool condition pretty accurately, if the feed and surface roughness are measured at identical conditions. As part of the present research work, the relationship between displacement due to vibration, cutting force, flank wear, and surface roughness has been examined.     

Global stability predictions for flexible workpiece milling using time domain simulation

This paper describes the use of peak-to-peak (PTP) force diagrams for machining stability prediction and validates its suitability for milling processes where the workpiece is considerably more flexible than the machine-tool system. These diagrams result from numerous executions of a time domain simulation which includes both the tool and workpiece dynamics and a mechanistic force model. The applicability of the PTP force diagram is validated experimentally through peripheral milling tests of thin-walled structures. Measured and simulated cutting forces are compared. It is shown that the PTP diagrams offer the global stability information which is provided by the traditional lobe diagram, while preserving the detailed, local information provided by time domain simulation.     

Increasing CNC machine tool productivity by using tool-part touch control

In this paper a new system for increasing CNC machining productivity is described. The system is based on registering the moment when the cutting tool touches the workpiece during a machining operation. The cutting tool approaches the workpiece with rapid traverse and switches to work feed when it comes in contact with it. In this way, the time for ‘cutting air’ can significantly be reduced.     

The micromilling process for high aspect ratio microstructures

 High aspect ratio microstructures are currently created by several processes which include lithography (X-ray, deep ultraviolet, etc.) and mechanical machining (diamond machining, microdrilling, etc.). The lithographic processes require more extensive processing equipment such as an energy source, mask/mask holder/mask aligner, photoresist and substrate, and chemical development capacity. In addition, these processes are serial in nature and each adds to the tolerances of the finished structure. The current mechanical processes provide for the direct removal of the substrate material in a single step but are more limited in the geometric patterns which can be created. In conventional machining, the process which provides the most versatility in geometric patterns is milling. The micromilling process has two basic components. The first is the fabrication of small milling cutters with very sharp cutting edges. The second is the actual removal of the workpiece material with a very precise and repeatable machine tool. Several basic cutter designs have been fabricated using focused ion beam micromachining and are undergoing testing. The cutter diameters are nominally 100 micrometers and 22 micrometers. Results have been obtained which show that this process can be very effective for the rapid fabrication of molds and mask structures. Received: 30 October 1995 / Accepted: 4 March 1996     

Robotic path compensation training method for optimizing face milling operations based on non-contact CMM techniques

Currently, the use of industrial robots in the machining of large components in metallic materials of significant hardness is proliferating. The low rigidity of industrial robots is still the main conditioning for their use in machining applications, where the forces developed in the process cause significant deviations on the cutting tool path. Although there are already methodologies that facilitate the pose study of the robot mechanical behaviour, predicting deviation values of the cutting tool path and facilitating the selection of process variables, robotic cell users still request new methods able to allow them to optimize the use of these production systems. On the other hand, non-contact measurement technologies have burst into many fields of knowledge, their use is becoming consolidated, and they allow the digitization of complex surfaces. This research presents the development of a new method of robotic machining trajectory compensation that allows optimizing the manufacture of flat surfaces using an industrial anthropomorphic robot. The new training method determines the actual deviations of the cutting tool after the machining process, and checks if these are within the admissible range of flatness error. This method is a novel iterative technique that incorporates the algorithm that uses the measured deviations and a reduction factor fr to calculate the offset that modifies the coordinate value of the programmed path points outside the admissible range and generates a new machining path to be tested. The method has been tested on a pre-industrial scale for aluminium machining, and the algorithm has carried out two iterations to generate a compensated robotic milling path within a flatness tolerance range of 300 µm, improving the error deviation by 37% comparing to the initial path.     

Recurrent ANN for monitoring degraded behaviours in a range of workpiece thicknesses

This paper presents the use of artificial neural networks (ANN) to diagnose degraded behaviours in wire electrical discharge machining (WEDM). The detection in advance of the degradation of the cutting process is crucial since this can lead to the breakage of the cutting tool (the wire), reducing the process productivity and the required accuracy. Concerning this, previous investigations have identified different types of degraded behaviours in two commonly used workpiece thicknesses (50 and 100 mm). This goal was achieved by monitoring different functions of characteristic discharge variables. However, the thresholds achieved by these functions depended on the thickness of the workpiece. Consequently, the main objective of this work is to detect the degradation of the process when machining workpiece of different thicknesses using one unique empirical model. Since artificial neural network techniques are appropriate for stochastic and non-linear nature processes, its use is investigated here to cope with workpieces of different thicknesses. The results of this work show a satisfactory performance of the presented approach. The satisfactory performance is shown by two ratios: the validation ratio, which ranges between 85% and 100%, and the test ratio, which results between 75% and 100%.     

Hybrid cutting simulation via discrete vector model

Geometric cutting simulation and verification play an important role in detecting NC machining errors in mold and die manufacturing, thereby reducing the correcting time and cost on the shop floor. According to workpiece model, current researches may be categorized into view-based, solid-based, and discrete vector-based methods. Each methodology has its own strengths and weaknesses in terms of computing speed, representation accuracy, and its ability to perform numerical inspection. This paper proposes a cutting simulation methodology via a hybrid workpiece model which consists of the general discrete vector model and its simplified model. Workpiece modeling scheme, cutting simulation via tool swept surface modeling and vector intersection, and some case studies of mold and die machining are presented in this paper.     

The micromilling process for high aspect ratio microstructures

High aspect ratio microstructures are currently created by several processes which include lithography (X-ray, deep ultraviolet, etc.) and mechanical machining (diamond machining, microdrilling, etc.) The lithographic processes require more extensive processing equipment such as an energy source, mask/mask holder/mask aligner, photoresist and substrate, and chemical development capacity. In addition, these processes are serial in nature and each adds to the tolerances of the finished structure. The current mechanical processes provide for the direct removal of the substrate material in a single step but are more limited in the geometric patterns which can be created. In conventional machining, the process which provides the most versatility in geometric patterns is milling. The micromilling process has two basic components. The first is the fabrication of small milling cutters with very sharp cutting edges. The second is the actual removal of the workpiece material with a very precise and repeatable machine tool. Several basic cutter designs have been fabricated using focused ion beam micromachining and are undergoing testing. The cutter diameters are nominally 100 micrometers and 22 micrometers. Results have been obtained which show that this process can be very effective for the rapid fabrication of molds and mask structures.     

A multi-regional computation scheme in an AR-assisted in situ CNC simulation environment

Computer numerical control (CNC) simulation systems based on 3D graphics have been well researched and developed for NC tool path verification and optimization. Although widely used in the manufacturing industries, these CNC simulation systems are usually software-centric rather than machine tool-centric. The user has to adjust himself from the 3D graphic environment to the real machining environment. Augmented reality (AR) is a technology that supplements a real world with virtual information, where virtual information is augmented on to real objects. This paper builds on previous works of integrating the AR technology with a CNC machining environment using tracking and registration methodologies, with an emphasis on in situ simulation. Specifically configured for a 3-axis CNC machine, a multi-regional computation scheme is proposed to render a cutting simulation between a real cutter and a virtual workpiece, which can be conducted in situ to provide the machinist with a familiar and comprehensive environment. A hybrid tracking method and an NC code-adaptive cutter registration method are proposed and validated with experimental results. The experiments conducted show that this in situ simulation system can enhance the operator’s understanding and inspection of the machining process as the simulations are performed on real machines. The potential application of the proposed system is in training and machining simulation before performing actual machining operations.     

A time-varying geometry modeling method for parts with deformation during machining process

Deformation due to residual stress is a significant issue during the machining of thin-walled parts with low rigidity. If there are multiple processes with deformation during machining, some process suitability issues will appear. On this occasion, the actual geometric state of the deformed workpiece is needed for process adjustment. However, it is still a challenge to obtain the complete geometry information of deformed workpiece accurately and efficiently. In order to address this issue, a time-varying geometry modeling method, combining cutting simulation and in-process measurement, is proposed in this paper. The deformed workpiece model can be reconstructed via transforming the deformed workpiece with only a small amount of the measurement points by superimposing material removal and workpiece deformation simulation according to a time sequence, which takes advantage of the proposed Curved Surface Mapping based Geometric Representation Model (CSMGRM). Machining experiment of a typical structural part has shown that the deformed geometry model of the whole workpiece can be reconstructed within the error of 0.05mm, which is less than one tenth of the finish machining allowance in general cases, and it is sufficient to meet the accuracy requirements for interference or overcut/undercut analysis and process adjustment.     

Numerical analysis of the tool wear effect in the machining induced residual stresses

Machining is a dynamic process involving coupled phenomena: high strain and strain rate and high temperature. Prediction of machining induced residual stresses is an interesting objective at the manufacturing processes modelling field. Tool wear results in a change of tool geometry affecting thermo-mechanical phenomena and thus has a significant effect on residual stresses. The experimental study of the tool wear influence in residual stresses is difficult due to the need of controlling wear evolution during cutting. Also the involved phenomena make the analysis extremely difficult. On the other hand, Finite Element Analysis (FEA) is a powerful tool used to simulate cutting processes, allowing the analysis of different parameters influent on machining induced residual stresses.The aim of this work is to develop and to validate a numerical model to analyse the tool wear effect in machining induced residual stresses. Main advantages of the model presented in this work are, reduced mesh distortion, the possibility to simulate long length machined surface and time-efficiency. The model was validated with experimental tests carried out with controlled worn geometry generated by electro-discharge machining (EDM). The model was applied to predict machining induced residual stresses in AISI 316 L and reasonable agreement with experimental results were found.     

Simulation of micro-patterns engraved by grinding process with screw shaped wheel

Grinding is an important means of realizing precision and ultra-precision machining of workpiece surface. The surface patterning of workpiece directly affects its mechanical properties such as friction, wear, contact stiffness, fitting property. Therefore, prediction of the geometry of the workpiece surface is very important to evaluate the workpiece quality to perform mechanical function accurately. In this paper using MATLAB simulation, prediction for the geometry pattern of the workpiece according to the developed shape of the grinding wheel dressed by thread cutting was studied. The model for the geometry of the grinding wheel surface was first developed and subsequently, a new simulation model for surface pattern by grinding process was established. The simulation results could be used to optimize the grinding process and to improve the workpiece surface quality or predict the surface pattern by given grinding parameters.     

刀具状态在线监测与智能识别方法研究

切削加工中刀具状态是影响加工质量的关键因素,刀具的磨损直接影响工件的加工精度和表面粗糙度.选择加速度传感器监测切削加工中的振动信号,针对刀具状态变化时振动能量分布随之变化的特点,提取不同频段振动能量作为特征量,利用RBF神经网络进行聚类辨识.实验结果表明,该方法具有良好的识别效果和工程应用价值.     

Modelling of the cutting tool stresses in machining of Inconel 718 using artificial neural networks

This study covers two main subjects: (i) The experimental and theoretical analysis: the cutting forces and indirectly cutting tool stresses, affecting the cutting tool life during machining in metal cutting, are one of very important parameters to be necessarily known to select the economical cutting conditions and to mount the workpiece on machine tools securely. In this paper, the cutting tool stresses (normal, shear and von Mises) in machining of nickel-based super alloy Inconel 718 have been investigated in respect of the variations in the cutting parameters (cutting speed, feed rate and depth of cut). The cutting forces were measured by a series of experimental measurements and the stress distributions on the cutting tool were analysed by means of the finite element method (FEM) using ANSYS software. ANSYS stress results showed that in point of the cutting tool wear, especially from von Mises stress distributions, the ceramic cutting insert may be possible worn at the distance equal to the depth of cut on the base cutting edge of the cutting tool. Thence, this wear mode will be almost such as the notch wear, and the flank wear on the base cutting edge and grooves in relief face. In terms of the cost of the process of machining, the cutting speed and the feed rate values must be chosen between 225 and 400 m/min, and 0.1 and 0.125 mm/rev, respectively. (ii) The mathematical modelling analysis: the use of artificial neural network (ANN) has been proposed to determine the cutting tool stresses in machining of Inconel 718 as analytic formulas based on working parameters. The best fitting set was obtained with ten neurons in the hidden-layer using back propagation algorithm. After training, it was found the R² values are closely 1.     

Modeling of cutting geometry and forces for 5-axis sculptured surface machining

5-Axis sculptured surface machining is simulated using discrete geometric models of the tool and workpiece to determine the tool contact area, and a discrete mechanistic model to estimate the cutting forces. An extended Z-buffer model represents the workpiece, while a discrete axial slice model represents the cutting tool. Determination of the contact area for a given tool move requires a swept envelope (SWE) of the tool path. The SWE is used to find the intersections of the tool envelope with Z-buffer elements (ZDVs) representing the workpiece. A 3-axis approximation of the 5-axis tool movement is used to simplify the calculations while maintaining a desired level of accuracy. The intersection of the SWE with each ZDV yields segments which are used to find the contact area between the cutter and the workpiece for a given tool path. The contact area is subsequently used with the discrete force model to calculate the vector cutting force acting on the tool.     

Simulation of media behaviour in vibration assisted abrasive flow machining

Abrasive flow machining (AFM) is an abrasive-based precision finishing process used for achieving surface finish in micro and nano-level. The AFM polishes surfaces by extruding a visco-elastic media in contact with the workpiece. The media, also called a ‘flexible tool’, plays a key role in the performance of the process. Ultrasonic assisted abrasive flow machining (UAAFM) is a new variant of the AFM process in which the workpiece is subjected to mechanical vibration orthogonal to the media flow direction. In this process a high frequency, in the range of about 5–20 kHz, is given to the workpiece with the help of a piezo actuator and a specially designed fixture. The present work highlights on the possible behaviour of the tool (media) during UAAFM and its effect on the machining process through a computation based approach. Commercially available simulation tool was used to study the effect of the media in response to different set of machining conditions. The responses were evaluated in terms of changes in the fluid pressure, velocity profile of the fluid, temperature distribution in the working fluid and the possible wall shear on the work surface. A three-dimensional model was constructed for simulating the UAAFM process. The simulation shows that the abrasive particles tend to hit the target surface at an angle ‘θ’ which significantly affects the basic mechanisms involved and enhances the effectiveness of the process. The computed wall shear explains that the process will have higher finishing rate and hence the performance. The enhanced interaction of abrasive media in UAAFM while compared to simple AFM could be explained by the resultant pressure–velocity phenomena. Results show that while changes in the amplitude of applied vibration (10 μm and 50 μm) significantly affect the wall shear, the media velocity and pressure profiles are only marginally sensitive to this parameter. The simulation results also confirm that the rise in temperature during the process will not affect the media stability. Results have been discussed vis-a-vis the basic mechanism of the process through suitable illustrations.     

Design of an optimal damper to minimize the vibration of machine tool structures subject to random excitation

The vibration of machine tools during machining adversely affects machining accuracy and tool life, and therefore must be minimized. The cutting forces for stable turning are generally known to be random, and hence excite all the resonance modes. Of all these modes, those that generate relative motions between a cutting tool and a workpiece are of concern.This paper presents a new approach for designing an optimal damper to minimize the relative vibration between the cutting tool and workpiece during stable machining. An approximate normal mode method is employed to calculate the response of a machine tool system with nonproportional damping subject to random excitation. The major advantage of this method is that it reduces the amount of computation greatly for higher-order systems when responses have to be calculated repeatedly in the process of optimization. An optimal design procedure is presented based on a representative lumped parameter model that can be constructed by using existing experimental or analytical techniques. The two-step optimization procedure based on the modified pattern search and univariate search effectively leads the numerical solution to the global minimun irrespectively of initial values even under the existence of many local minima.     

Effect of workpiece springback on micromilling forces

The machining forces present in micromilling with tools in the 50–100 m diameter range are dominated by contact pressure and friction between the tool cutting edges and the workpiece. A model of the micromilling process was developed based on the elastic contact between the tool and the workpiece along the side and bottom cutting edges of the tool. Micromilling experiments were conducted on 6061-T6 aluminum to obtain machining forces in the feed and cross-feed directions during slot milling and partial engagement end milling. Comparisons with the experimental data indicate reasonable agreement for full slot milling as well as end milling with radial depths of cut in the range of 2 m to 40 m. It was concluded that this model is adequate for predicting micromilling forces with the precision needed to reduce tool breakage and workpiece clamping forces and for predicting tool deflection that affects wall slope and feature size.This work was supported primarily by the Engineering Research Centers Program of the National Science Foundation under Award Number EEC-9986866. The Engineering Research Center for Wireless Integrated Microsystems is also hereby acknowledged. All machining was performed at the Micromechanical Applications and Processes Laboratory at Michigan Technological University.