The optimal cutting-parameter selection of production cost in HSM for SKD61 tool steels

The main purpose of this study was to construct an investigation of optimal cutting parameters for minimizing production cost on the rough machining of high speed milling operation. A machining model is constructed based on a polynomial network. The polynomial network can learn the relationships between cutting parameters (cutting speed, feed per tooth, and axial depth of cut) and tool life through a self-organizing technique. Once the material removal volume for machined parts and various time and cost components of the high speed milling operations are given, an optimization algorithm using a simulated annealing method is then applied to the polynomial network for determining optimal cutting parameters. The optimal cutting parameters are subjected to an objective function of minimum production cost with the feasible range of cutting parameters.     

Performance-based optimization of multi-pass face milling operations using Tribes

The paper proposes a new optimization technique based on Tribes for determination of the cutting parameters in multi-pass milling operations such as plain milling and face milling by simultaneously considering multi-pass rough machining and finish machining. The optimum milling parameters are determined by minimizing the maximum production rate criterion subject to several practical technological constraints. The cutting model formulated is a nonlinear, constrained programming problem. Experimental results show that the proposed Tribes-based approach is both effective and efficient.     

Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling

This paper investigates optimization design of the cutting parameters for rough cutting processes in high-speed end milling on SKD61 tool steel. The major characteristics indexes for performance selected to evaluate the processes are tool life and metal removal rate, and the corresponding cutting parameters are milling type, spindle speed, feed per tooth, radial depth of cut, and axial depth of cut. In this study, the process is intrinsically with multiple performance indexes so that grey relational analysis that uses grey relational grade as performance index is specially adopted to determine the optimal combination of cutting parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively described. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of cutting parameters. Hence, this confirms that the proposed approach in this study can be an useful tool to improve the cutting performance of rough cutting processes in high-speed end milling process.     

模糊田口法在重切削制程中切削参数最佳化设计

为了快速有效获得重切削时良好的切削性能参数,以田口法与模糊逻辑相结合,对侧面铣削SUS304不锈钢重切削制程时的切削参数进行最佳化设计。由于评估重切削制程的刀具寿命与金属移除率两项主要切削性能,受到主轴转速、每刃进给、轴向切深与径向切深的影响,由此将4个切削参数设置为可控制因子。经过田口法将各品质特性转化为S/N比,通过模糊逻辑运算,采用多重品质特性指标(MPCI)求得切削参数最佳水准组合。试验结果表明:以模糊田口法获得的切削参数最佳水准组合,能够有效改善侧面重切削制程时的切削性能,为刀具制造厂或刀具使用者寻求最佳切削条件提供参考。     

基于人工神经网络和遗传算法的平面铣削加工参数自适应优化

机械加工最优自适应控制的关键在于自适应加工模型的建立和实时优化策略的制定。本文提出用人工神经网络方法建立加工过程模型 ,用遗传算法实现在线优化。基于以上算法 ,构造了平面铣削加工参数自适应优化系统 ,可使加工系统在不违反加工约束的前提下 ,总是获得最大材料去除率。     

基于需求分类遗传算法的Al/15% SiC_p复合材料电化学加工工艺参数的优化

电化学加工（ECM）是一种重要的非传统加工工艺,主要用于加工难加工材料和错综复杂的型材。作为一个复杂的过程,很难确定最优参数去改善切削性能。金属去除率和表面粗糙度是最重要的输出参数,决定切削性能。由于切削参数对金属去除率和表面粗糙度的影响不一致,从而没有简单的切削参数的最佳组合。用多元回归模型来表示输出与输入变量之间的关系,并用基于需求分类遗传算法（NSGA-II）的多目标优化方法来优化ECM过程,得到一个需求解集。     

Development of micro milling force model and cutting parameter optimization

Taking the minimum chip thickness effect,cutter deflection,and spindle run-out into account,a micro milling force model and a method to determine the optimal micro milling parameters were developed.The micro milling force model was derived as a function of the cutting coefficients and the instantaneous projected cutting area that was determined based on the machining parameters and the rotation trajectory of the cutter edges.When an allowable micro cutter deflection is defined,the maximum allowable cutting force can be determined.The optimal machining parameters can then be computed based on the cutting force model for better machining efficiency and accuracy.To verify the proposed cutting force model and the method to determine the optimal cutting parameters,micro-milling experiments were conducted,and the results show the feasibility and effectiveness of the model and method.     

A note on ‘Dynamic optimization of multipass milling operations via geometric programming’

An article published in this journal by Sonmez et al. [A.I. Sönmez, A. Baykasoğlu, I.H. Filiz, Dynamic optimization of multipass milling operations via geometric programming, International Journal of Machine Tools & Manufacture, 39(1999) 297–320] developed a mathematical model using ‘geometric programming’ for determination of the cutting parameters in multipass milling operations, such as plain milling and face milling. The developed strategy is based on the maximum production rate criterion subject to several practical technological constraints. Their published results for the production rates for the two passes show that it appears Sonmez et al. added the value of invariant time of 1.7 (for n=1) to each solution of the passes, thereby having incorrect solutions for the production rates for the rough and finish passes. This note works through the solutions to show how Sonmez et al. [1] incorrectly handled the addition of the invariant time to their solution. Moreover, the note raises the question of how correct their ‘dynamic programming’ model for production rate is, since it was used to find a range of values, which were then used for the optimization process.     

Analytical models for high performance milling. Part I: Cutting forces, structural deformations and tolerance integrity

Milling is one of the most common manufacturing processes in industry. Despite recent advances in machining technology, productivity in milling is usually reduced due to the process limitations such as high cutting forces and stability. If milling conditions are not selected properly, the process may result in violations of machine limitations and part quality, or reduced productivity. The usual practice in machining operations is to use experience-based selection of cutting parameters which may not yield optimum conditions. In this two-part paper, milling force, part and tool deflection, form error and stability models are presented. These methods can be used to check the process constraints as well as optimal selection of the cutting conditions for high performance milling. The use of the models in optimizing the process variables such as feed, depth of cut and spindle speed are demonstrated by simulations and experiments.     

Modelling and simulation of chatter in milling using a predictive force model

A predictive time domain chatter model is presented for the simulation and analysis of chatter in milling processes. The model is developed using a predictive milling force model, which represents the action of milling cutter by the simultaneous operations of a number of single-point cutting tools and predicts the milling forces from the fundamental workpiece material properties, tool geometry and cutting conditions. The instantaneous undeformed chip thickness is modelled to include the dynamic modulations caused by the tool vibrations so that the dynamic regeneration effect is taken into account. Runge–Kutta method is employed to solve the differential equations governing the dynamics of the milling system for accurate solutions. A Windows-based simulation system for chatter in milling is developed using the predictive model, which predicts chatter vibrations represented by the tool-work displacements and cutting force variations against cutter revolution in both numerical and graphic formats, from input of tool and workpiece material properties, cutter parameters, machine tool characteristics and cutting conditions. The system is verified with experimental results and good agreement is shown.     

Prediction of chatter stability in high-speed finishing end milling considering multi-mode dynamics

The strong demand for increasing productivity and workpiece quality in high-speed milling make the machine-tool system has to operate close to the limit of its dynamic stability. This requires that the chatter stability is predicted accurately to determine the optimal milling parameters. An analytical stability prediction method was proposed with multi-degree-of-freedom (MDOF) system modal analysis. This paper describes the development of this new method which allows considering the effects of multi-mode dynamics of system, higher excited frequency (i.e. tooth passing frequency) and wider spindle speed range on stability limits in high-speed milling, and these to help in selection of milling parameters for a maximum material removal rates (MRR) in real operations without chatter. Some tests were carried out to demonstrate the quality of this method used in real machining. Final, the main influencing factors of stability limits in high-speed milling were analyzed.     

An experimental study of burr formation in square shoulder face milling

Previous research on burr formation in face milling operations has usually been limited to the study of the rollover burr in the cutting direction and/or to a few machining parameters. This paper presents the results of an experimental study on the influence of the main cutting parameters on the formation of the more important burrs produced in face milling operations, namely exit burr in the cutting direction, exit burr in the feed direction and the burr formed at the top edge in a square shoulder face milling operation. Feed per tooth (Sz), cutting velocity (V), axial depth of cut (a) and exit angle (EXA) were the cutting parameters investigated. The effects of mode of milling, tool nose geometry and tool coating were also investigated to a lesser extent. The results show that exit angle and depth of cut are the cutting parameters which have a major influence on the exit burr in the cutting direction, whereas the exit burr in the feed direction is mainly affected by depth of cut. The top burr is very small and only slightly influenced by cutting conditions. It is also shown that down-milling can effectively eliminate the formation of burrs in some cases, whereas an unfavourable tool nose geometry can double the size of buns.     

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。     

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.     

Fuzzy control of feed rate in end milling operations

In order to improve productivity in end milling operations, a new adaptive control system based on fuzzy logics to maintain a constant cutting force is developed. It is shown, by experimental cutting tests, that the cutting tool travels in the air cut with fast feed rate, yet in the varying depths of cut, the tool travels with an adjustable feed rate to prevent the occurrence of tool breakage and maintain a high metal removal rate.     

Broaching of Inconel 718 with cemented carbide

Broaching is the standard process for machining complex-shaped slots in turbine discs. More flexible processes such as milling, wire EDM machining and water-jet cutting are under investigation and show promising results. In order to further use existing resources and process knowledge, the broaching process has to be improved towards higher material removal rates. Taking into account that the state-of-the-art broaching process is working with high-speed-steel tools, the higher thermal resistant cemented carbide cutting materials offer the potential to significantly increase cutting speeds, which lead to increased process productivity. The following article presents a broad study on broaching with cemented carbide tools. Different cutting edge geometries are discussed on the basis of process forces, chip formation and tool wear mechanisms. Furthermore, a detailed comparison to the standard process is drawn.     

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.     

On the closed form mechanistic modeling of milling: Specific cutting energy,torque, and power

Specific energy in metal cutting, defined as the energy expended in removing a unit volume of workpiece material, is formulated and determined using a previously developed closed form mechanistic force model for milling operations. Cutting power is computed from the cutting torque, cutting force, kinematics of the cutter, and the volumetric material removal rate. Closed form expressions for specific cutting energy were formulated and found to be functions of the process parameters: pressure and friction for both rake and flank surfaces and chip flow angle at the rake face of the tool. Friction is found to play a very important role in cutting torque and power. Experiments were carried out to determine the effects of feedrate, cutting speed, workpiece material, and flank wear land width on specific cutting energy. It was found that the specific cutting energy increases with a decrease in the chip thickness and with an increase in flank wear land.     

Extension of Tlusty׳s law for the identification of chatter stability lobes in multi-dimensional cutting processes

Chatter vibrations in cutting processes are studied in the present paper. A unified approach for the calculation of the stability lobes for turning, boring, drilling and milling processes in the frequency domain is presented. The method can be used for a fast and reliable identification of the stability lobes and can take into account nonlinear shearing forces, as well as process damping forces. The applicability of Tlusty׳s law, which is a simple scalar relationship between the real part of the oriented transfer function of the structure and the limiting chip width, is extended to milling and any other multi-dimensional chatter problem without neglecting the coupled dynamics. The given analysis is suitable for getting a deep understanding of the chatter stability dependent on the parameters of the cutting process and the structure. Basic examples based on experimental data of real machine tools include the dependence of the stability behavior on the rotational direction in turning, the effect of axial–torsional structural coupling in drilling, and the dynamics of slot milling.     

Model-based predictive force control in milling: determination of reference trajectory

Today, powerful process simulation tools allow an offline process planning and optimization of metal cutting processes. The quality of the optimization strongly depends on the model and its parameters. Real cutting processes are influenced by uncertainties such as tool wear status or material properties, which are both unknown. To overcome this limitation, sensors and process control systems are used. Model-based Predictive Control (MPC) was developed in the 1970s for the chemical process industry. This control method was found to be very suitable to control complex manufacturing processes such as milling processes. Using MPC in metal cutting processes allows considering technological boundary conditions explicitly. Adapting the feed velocity and thus the process force increases the productivity and process stability in milling. A core element of the MPC is the use of a reference trajectory representing the time-dependent set point value in the optimization procedure. The tool path information, however, is given position-based. Thus, calculating the reference trajectory is not trivial and strongly influences the control quality. This paper presents two methods for determining the reference trajectory. The first method is based on an adaptive signal filter. For the second method the MPC is extended to a two-layer MPC: the first layer calculates an optimal reference trajectory; the second layer controls the machine tool.