Dynamic optimization of multipass milling operations via geometric programming

This paper outlines the development of an optimization strategy to determine the optimum cutting parameters for multipass milling operations like plain milling and face milling. The developed strategy is based on the “maximum production rate” criterion and incorporates eight technological constraints. The optimum number of passes is determined via dynamic programming, and the optimal values of the cutting conditions are found based on the objective function developed for the typified criterion by using a non-linear programming technique called “geometric programming”. This paper also underlies the importance of using optimization strategies rather than handbook recommendations as well as pointing out the superiority of the multipass over the single-pass optimization approach.     

基于高质量和低振动的铣削参数优化方法研究

针对数控铣床在切削过程中产生的振动对工件表面质量的影响,提出以低振动和高表面质量为优化目标,对切削参数进行优化。以VDF-850A铣床为研究对象对45号钢进行铣削正交试验,通过建立振动采集系统,采集振动信号提取振动特征值并测量工件表面粗糙度值,应用最小二乘法拟合数据建立了振动和粗糙度数学模型。利用层次分析法确定两目标函数权重,使用平方和加权法对两目标函数加权拟合成综合目标评价函数,运用粒子群算法优化切削参数。试验结果表明:应用粒子群算法优化后的切削参数进行加工可有效的降低振动和提高表面质量。     

On cutting parameters selection for plunge milling of heat-resistant-super-alloys based on precise cutting geometry

In plunge milling operation the tool is fed in the direction of the spindle axis which has the highest structural rigidity, leading to the excess high cutting efficiency. Plunge milling operation is one of the most effective methods and widely used for mass material removal in rough/semi-rough process while machining high strength steel and heat-resistant-super-alloys. Cutting parameters selection plays great role in plunge milling process since the cutting force as well as the milling stability lobe is sensitive to the machining parameters. However, the intensive studies of this issue are insufficient by researchers and engineers. In this paper a new cutting model is developed to predict the plunge milling force based on the more precise plunge milling geometry. In this model, the step of cut as well as radial cutting width is taken into account for chip thickness calculation. Frequency domain method is employed to estimate the stability of the machining process. Based on the prediction of the cutting force and milling stability, we present a strategy to optimize the cutting parameters of plunge milling process. Cutting tests of heat-resistant-super-alloys with double inserts are conducted to validate the developed cutting force and cutting parameters optimization models.     

Prediction of surface roughness profiles for milled surfaces using an artificial neural network and fractal geometry approach

Artificial neural networks (ANNs) models were developed for the analysis and prediction of the relationship between the cutting conditions and the corresponding fractal parameters of machined surfaces in face milling operation. These models can help manufacturers to determine the appropriate cutting conditions, in order to achieve specific surface roughness profile geometry, and hence achieve the desired tribological performance (e.g. friction and wear) between the contacting surfaces. The input parameters of the “ANNs” models are the cutting parameters: rotational speed, feed, depth of cut, pre-tool flank wear and vibration level. The output parameters of the model are the corresponding calculated fractal parameters: fractal dimension “D” and vertical scaling parameter “G”. The model consists of three-layered feed-forward back-propagation neural network. ANNs models were utilized successfully for modeling and predicting the fractal parameters “D” and “G” in face milling operations. Moreover, W–M fractal function was integrated with the developed ANNs models in order to generate an artificially fractal predicted profiles at different cutting conditions. The predicted profiles were found statistically similar to the actual measured profiles of test specimens.     

基于GA-BP的6061Al切削参数优化

针对6061Al铣削中表面粗糙度预测精度低、切削参数选择不合理的问题,提出一种基于遗传神经网络与遗传算法结合的优化模型,对6061Al切削参数进行优化。采用遗传神经网络(GA-BP)构建表面粗糙度预测模型;基于表面粗糙度预测,以材料去除率为目标函数构建切削参数优化模型;利用遗传算法进行优化求解,对6061Al切削参数进行优化。研究结果表明:所建预测模型表面粗糙度预测精度在97%以上;同时,优化模型能优化6061Al切削参数,达到较好的全局寻优效果,为铝合金工件铣削加工切削参数优化提供参考。     

Tool positioning error (TPE) characterisation in milling

Where the geometrical features so permit, the {workpiece–work-holding fixture} assembly is generally considered to be infinitely rigid. The {tool–tool-holder–spindle} assembly and the machine axes are then deformed under the action of the cutting forces. This deformation leads to a positioning error of the tool in relation to the theoretical position. With the aim of taking this positioning error into account, the inaccuracies obtained during end milling and side milling were experimentally modelled from the cutting conditions used for a given machine/mill/material triplet (TriM). Our “Virtual Worker” then used these models to predict machining errors according to the type of machining and to compensate for them.     

Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing

This paper presents an approach to select the optimal machining parameters for multi-pass milling. It is based on two recent approaches, genetic algorithm (GA) and simulated annealing (SA), which have been applied to many difficult combinatorial optimization problems with certain strengths and weaknesses. In this paper, a hybrid of GA and SA (GSA) is presented to use the strengths of GA and SA and overcome their weaknesses. In order to improve, the performance of GSA further, the parallel genetic simulated annealing (PGSA) has been developed and used to optimize the cutting parameters for multi-pass milling process. For comparison, conventional parallel GA (PGA) is also chosen as another optimization method. An application example that has been solved previously using the geometric programming (GP) and dynamic programming (DP) method is presented. From the given results, PGSA is shown to be more suitable and efficient for optimizing the cutting parameters for milling operation than GP+DP and PGA.     

A new method of cutting force measurement based on command voltages of active electro-magnetic bearings

In this paper, a new indirect method of measuring dynamic cutting forces is proposed. Milling tests have been performed on a five-axis machine, Gambin 120CR, fitted out with an electro-spindle with magnetic bearings developed by the company S2M, and named SMB30. These bearings are not affected by friction and wear. An experimental approach has been developed to determine the cutting forces as a function of the measured command voltages of the milling spindle’s magnetic bearings. The spindle is treated as a “black box”, where the transfer functions linking the unknown cutting force with command voltages are established experimentally. The cutting forces calculated from the command voltages of magnetic bearings are in good agreement with the ones measured with a Kistler four-component dynamometer. This indirect method of cutting force determination provides a useful way to estimate tool wear and monitor product quality in high-speed milling on-line.     

基于DBSCAN算法的切削载荷状态智能识别算法

针对切削过程中的切削力状态识别以及切削参数的动态调整问题,提出了一种基于密度聚类算法的切削载荷智能识别算法;该方法通过对切削力载荷特性的识别、判断,使用密度聚类算法建立簇分类算法,以距离度量作为簇分类判据,以簇的核心点作为切削载荷学习对象,通过切削载荷理想值做出判断,实现对切削载荷的智能识别。论文应用该算法,结合Agent技术,对石材高速铣削条件下的切削力载荷状况进行了智能识别和可视化表述。研究表明,该算法能够实现对切削加工状态的智能识别与判断,并达到了对切削参数在线优化的目的,提高了加工效率与加工质量,为切削加工参数的智能优化奠定了理论基础。     

Tool wear monitoring and breakage detection based on “intelligent filtering”

Several physical quantities can be used for indirect tool wear monitoring and breakage detection. Cutting forces are appropriate, since they determine the suitability of a tool for cutting. However, disturbances make the accurate and fast tool condition monitoring based upon force analysis difficult. To eliminate disturbances averaging or filtering within a predetermined bandwidth has often been applied. A new method of decomposing the force signal into components having close relationships with physical phenomena taking place during cutting is presented. The term “intelligent filtering” denotes decomposition based on on-line identification of model(s) of the cutting process. Application of “intelligent filtering” for the milling process with two cutting insert tools is discussed.     

基于改进遗传算法的数控机床加工铣削参数优化方法

对于数控机床加工铣削参数优化多采用常规的可信度近似模型,但该方法易受到材料失效应变系数的影响,导致优化后的加工效率较低,提出基于改进遗传算法的数控机床加工铣削参数优化方法。根据工件的本构模型,对切削刃进行采样抽取,确定最小铣削力波动位置;引入材料失效准则计算材料失效应变系数,基于此,以加工时间最短、加工成本最低和加工能耗消耗最小为目标建立铣削参数优化模型,并采用改进遗传算法求解模型,通过迭代适应度值,输出最佳铣削参数;最后,采用对比实验的形式对所提方法的优化性能进行测试。测试结果表明：应用所提方法对数控机床加工铣削参数进行优化后,能够有效缩短切削时间,提高加工效率。     

钛合金铣削加工表面残余应力有限元仿真

为了分析铣削工艺参数对钛合金已加工表面残余应力的影响,根据金属切削有限元分析的相关理论,以钛合金Ti6Al4V为工件材料,建立了铣削加工的有限元模型。采用正交试验设计法对钛合金Ti6Al4V铣削仿真的工艺参数进行优化,并用极差法分析不同的铣削速度、铣削深度、铣削路径对钛合金Ti6Al4V工已加工表面残余应力的影响。研究表明:在钛合金Ti6Al4V铣削过程中,对工件已加工表面残余应力影响因素由小到大依次为:铣削深度<铣削路径<铣削速度,切削深度对已加工表面残余应力影响较小,铣削速度对已加工表面残余应力影响最大;在研究范围内,随着铣削速度的增大,已加工表面残余应力逐渐增加。     

An investigation of workpiece temperature variation in end milling considering flank rubbing effect

Better prediction about the magnitude and distribution of workpiece temperatures has a great significance for improving performance of metal cutting process, especially in the aviation industry. A thermal model is presented to describe the cyclic temperature variation in the workpiece for end milling. Owing to rapid tool wear in the machining of aeronautical components, flank rubbing effect is considered. In the proposed heat source method for milling, both the cutting edge and time history of process are discretized into elements to tackle geometrical and kinematical complexities. Based on this concept, a technique to calculate the workpiece temperature in stable state, which supposes the tool makes reverse movement, is developed. And a practicable solution is provided by constructing a periodic temperature rise function series. This investigation indicates theoretically and experimentally the impact of different machining conditions, flank wear widths and cutter locations on the variation of workpiece temperature. The model results have been compared with the experimental data obtained by machining 300M steel under different flank wear widths and cutting conditions. The comparison indicates a good agreement both in trends and values. With the alternative method, an accurate simulation of workpiece temperature variation can be achieved and computational time of the algorithm is obviously shorter than that of finite element method. This work can be further employed to optimize cutting conditions for controlling the machined surface integrity.     

SKD11铣削刀具寿命试验研究及工艺参数优化

为提高SKD11模具钢铣削刀具的寿命,对SKD11模具钢进行了刀具寿命铣削试验,基于极差方法分析了各工艺参数对刀具寿命的影响规律。基于刀具寿命铣削试验,利用多元线性回归方法,推导并求解出了SKD11模具钢铣削刀具磨损的数学模型。利用最优化设计方法和MATLAB优化工具箱,以加工效率和刀具磨损为目标函数,针对实际的铣削问题优选了工艺参数。优化的工艺参数能兼顾刀具寿命和加工效率,为加工企业降低综合生产成本提供了重要的理论依据和案例参考。     

Geometric adaptive straightness control system for the peripheral end milling process with large error sources

An off-line Geometric Adaptive Control (GAC) scheme is proposed to compensate for machining straightness errors due to the machine tool's inaccuracy and those arising as a result of the metal cutting process during the finish peripheral end milling process. In the milling process, the workpiece travels along the guideway while the spindle system remains fixed. The scheme is based on the exponential smoothing of post-process measurements of relative machining errors due to the tool and bed deflections. Without a priori knowledge of the variations of the cutting parameters, the time-varying parameters are estimated by an Exponentially Weighted Recursive Least Squares (EWRLS) method. This method is able to incorporate a straightedge which is not necessarily accurate to identify the guideway errors. To reduce the drift of the cutting parameters, a single parameter adaptation method is introduced. Experimental results show that the location error is controlled within the range of the fixing error of the milling bed on the guideway. Further, the waviness error is reduced to less than 10 μm in the machining of a 508-mm long prismatic workpiece regardless of the machining conditions.     

RCPM—A new method for robust chatter prediction in milling

The reliability of conventional chatter prediction algorithms is limited by the inaccuracy of machining system dynamic models. In this paper, a new probabilistic algorithm for a robust analysis of stability in milling, which performs the stability analysis on an uncertain dynamic milling model, is presented. In this approach, model parameters are considered as random variables, and robust analysis of stability is carried out in order to estimate system's probability of instability for a given combination of cutting parameters. By doing so, probabilistic instead of deterministic stability lobes are obtained, and a new criterion for system stability based on level curves and gradient of the probabilistic lobes can be applied to identify optimal robust stable cutting conditions. Experimental validation consisted of different phases: firstly, machining system dynamics were estimated by means of pulse tests. Secondly, cutting force coefficients were determined by performing cutting tests. Eventually, chatter tests were performed and the experimental stability lobes were compared with the predicted robust stable regions.     

New procedures for calibration of instantaneous cutting force coefficients and cutter runout parameters in peripheral milling

In this paper, new procedures are proposed to calibrate the instantaneous cutting force coefficients and the cutter runout parameters for peripheral milling. By combining with optimization algorithm, i.e., the Nelder–Mead simplex method, detailed calibration schemes are derived for a mechanistic cutting force model in which the cutting force coefficients are described as the exponential functions of the instantaneous uncut chip thickness. Three different cutter runout models are considered in the calculation of instantaneous uncut chip thickness. Only one or two tests are required to perform the calibration. Experimental verifications are also conducted to validate the proposed procedures, and the results show that they are efficient and reliable. To see the effect of different runout models on milling process, comparisons among the predicted results under a wide range of cutting parameters are made to study the consistency and limitations of different models. It is found that the radial cutter runout model is a recommendable one for cutting force modelling.     

高速铣削表面粗糙度的研究

通过在HSM－700型高速铣床上的正交铣削试验，联系平时实际的生产加工情况，分析高速铣削的切削加工参数对零件表面粗糙度的影响。通过分析不同铣削参数下的零件表面粗糙度和切屑变形，为高速加工切削参数的选择和表面质量的控制提供依据。     

Increasing productivity in sculpture surface machining via off-line piecewise variable feedrate scheduling based on the force system model

Sculpture surface machining is a critical process commonly used in various industries such as the automobile, aerospace, die/mold industries. Since there is a lack of scientific tools in practical process planning stages, feedrates for CNC machining are selected based on the trial errors and previous experiences. In the selections of the process parameters, production-planning engineers are conservative in order to avoid undesirable results such as chipping, cutter breakage or over-cut due to excessive cutter deflection. Currently, commonly used CAD/CAM programs use only the geometric and volumetric analysis, but not the physics of the processes, and rely on experience based cutting tool database and users’ inputs for selection of the process parameters such as feed and speed. Usually, the feeds and cutting speeds are set individual constant values all along the roughing, semi-finishing, and finishing processes. Being too conservative and setting feedrate constant all along the tool path in machining of sculpture surfaces can be quite costly for the manufacturers. However, a force model based on the physics of the cutting process will be greatly beneficial for varying the feedrate piecewise along the tool path.The model presented here is the first stage in order to integrate the physics of the ball-end milling process into the selection of the feeds during the sculpture surface machining. Therefore, in this paper, an enhanced mathematical model is presented for the prediction of cutting force system in ball end milling of sculpture surfaces. This physical force model is used for selecting varying and ‘appropriate’ feed values along the tool path in order to decrease the cycle time in sculpture surface machining. The model is tested under various machining conditions, and some of the results are also presented in the paper.     

Advanced cutting conditions for the milling of aeronautical alloys

This paper deals with possible improvement aspects on the chip cutting milling of two alloys that are used frequently in the aerospace industry, in particular the titanium alpha–beta-based alloy Ti6Al4V and the nickel alloy usually known as type 718. Both alloys are used widely in the manufacture of different turbo-engine parts, considering their excellent mechanic features, and their resistance to high temperatures. These alloys, however, are extremely difficult to be milled, due to different factors, which are analysed later in this paper. For of this reason, their milling, drilling, and turning are carried out at very low speeds and feeds. This paper studies the tool influence as to its geometry and coating, and as to the parameters of the process (i.e. cutting speed, tooth feed, and depth of radial cut), looking for an increase in the productivity of the milling process. The cutting conditions thus searched for are successful in increasing the efficiency in the milling of actual parts in this field.