基于遗传算法的高速铣削工艺参数优化研究

在高速铣削加工中,考虑机床和工件加工的实际约束条件,为合理选择高速铣削工艺参数,建立了最大生产率和最低加工成本的优化目标数学模型。以铣削速度、进给量、铣削深度、铣削宽度为工艺参数的优化变量,提出了基于遗传算法的高速铣削工艺参数优化方法,为高速铣削加工提供了理论依据。     

基于遗传算法的航空叶片铣削加工工艺参数优化

为了提高叶片加工效率和降低加工变形量,利用正交试验法确定了若干组工艺参数方案并完成CAM和CAE仿真试验,建立了加工效率和变形量的模型。为得到更好的加工效率和更优的变形量,采用遗传算法完成对铣削工艺参数的优化计算,对最优工艺参数解集进行二次试验和优化,最终获得满足更高加工效率和更优变形量的最佳工艺参数组合。结果表明:当每齿进给量0.05mm,刀具转速2860r/min,铣削宽度0.5mm,铣削深度0.1mm时,工艺参数最优。     

铣削加工仿真及工艺参数优化

针对现代铣削加工对铣削工件质量的更高要求,该研究通过AD分析、极差分析和实际加工验证,优化了铣削加工工艺参数。该研究设计了正交试验方案,确定影响铣削加工的因素的初始参数,利用Advant Edge(AD)软件依据相关参数进行铣削加工仿真,对仿真结果进行极差分析后得出优化参数。最后该研究进行实际加工,将实际加工所得的数据与仿真结果相比较,验证仿真所得数据,优化出既具有较小的切削变形,又具有较大加工效率的切削工艺参数。为铣削加工工艺优化提出改进意见。     

典型零件叶片高速五轴铣削加工的研究

叶片的高速五轴铣削是高速切削技术的一个典型应用，切削参数的优化是关系到加工效率和加工经济性的重要环节。笔者通过借鉴两种铝合金材料的试验数据来优化高速铣削参数，以提高叶片的加工质量和效率。     

薄壁零件高速铣削实验

通过高速铣削单因素实验，研究高速铣削参数对工件表面质量和铣削力变化的影响规律，优化薄壁零件高速铣削参数。在此基础上进行了薄壁零件的高速铣削实验，结果表明，采用优化后的高速铣削参数加工薄壁零件，能够有效地提高薄壁零件的加工精度和加工效率。     

盖板件高效铣削表面粗糙度预测与工艺参数优化

为了保证7075铝合金盖板件铣削表面质量和提高铣削加工效率,进行工艺参数优化,通过响应曲面法(RSM)构建铣削加工表面粗糙度预测模型,分析铣削工艺参数对表面粗糙度的影响规律。基于表面粗糙度预测模型建立高效铣削工艺参数优化目标方程,采用改进的粒子群算法(PSO)对目标方程进行优化,运用优化后的工艺参数对某盖板件进行铣削加工。试验结果表明：采用优化后的工艺参数进行盖板件铣削加工可以满足表面粗糙度要求,验证了预测模型的准确性和改进PSO方法的可行性。     

基于MATLAB软件的铣削加工参数优化

目前,在高速铣削加工生产中普遍存在的问题是缺乏优化的高速铣削工艺参数。加工参数选用不当,常造成加工成本的增加和加工效率的低下。因此,通过实验数据,利用MATLAB软件的优化函数"fmincon"找出多个单目标函数的最合理值,然后将多目标问题转化为一个具有统一目标函数的单目标问题来求解。最后,通过统一目标函数得到切削加工参数的优化值,为高速切削加工提供合理的切削加工参数。     

基于变形控制的薄壁结构件高速铣削参数选择

首先对国内外有关研究薄壁件铣削加工变形的文献进行了回顾。然后,对不同切削参数下铣削力变化规律以及因铣削力引起的加工变形进行了理论分析与试验研究,并以此为基础提出了薄壁件高速铣削切削参数选择原则。试验结果表明,采用优化的切削参数不仅使薄壁件加工精度得到了保证,加工效率也大大提高。     

高速铣削淬硬钢工艺参数的选择

合理选择工艺参数,对高速铣削淬硬钢非常关键。基于淬硬钢高速铣削工艺参数选择的理论基础,分析了工艺参数对加工表面质量、加工效率以及刀具磨损等影响,系统地阐述了工艺参数的选择方法。     

数控铣削加工工艺参数优化方法分析

介绍数控铣削加工工艺和数控铣削加工工艺参数优化方法,通过切削深度及其参数优化、高速铣削加工及其切削参数的确定、五轴铣削加工工艺优化,有效保证数控铣削加工的可靠性与合理性。因此,分析加工工艺参数优化方法对数控铣削具有重要意义。     

An Investigation of the High Speed Machining Process Using a Variable Flow Stress Machining Theory

This article investigates the application of the Oxley modeling approach to high speed machining (HSM) process for gaining a fundamental understanding and performance prediction of this process which is gaining increased popularity due to its many economic and technological advantages such as faster metal removal rates, efficient use of machine tools and, improved surface finish and lower cutting forces. Oxley's theory has so far mainly been applied for making machining predictions for plain carbon steels in the conventional speed range. In the present work, this theory has been applied for two plain carbon steels and a low alloy steel under HSM conditions. The predicted cutting forces, chip thicknesses, and secondary deformation zone thicknesses are then compared with the experimental results obtained under identical conditions. Good agreement has been shown between measured and predicted results. In addition, the possibility of applying the theory to predict the tool life and tool deformation conditions is also explored. An ability to predict these process parameters is of paramount importance since catastrophic tool failure under HSM conditions can be extremely costly and dangerous.     

An Investigation of the High Speed Machining Process Using a Variable Flow Stress Machining Theory

Abstract

This article investigates the application of the Oxley modeling approach to high speed machining (HSM) process for gaining a fundamental understanding and performance prediction of this process which is gaining increased popularity due to its many economic and technological advantages such as faster metal removal rates, efficient use of machine tools and, improved surface finish and lower cutting forces. Oxley's theory has so far mainly been applied for making machining predictions for plain carbon steels in the conventional speed range. In the present work, this theory has been applied for two plain carbon steels and a low alloy steel under HSM conditions. The predicted cutting forces, chip thicknesses, and secondary deformation zone thicknesses are then compared with the experimental results obtained under identical conditions. Good agreement has been shown between measured and predicted results. In addition, the possibility of applying the theory to predict the tool life and tool deformation conditions is also explored. An ability to predict these process parameters is of paramount importance since catastrophic tool failure under HSM conditions can be extremely costly and dangerous.     

An optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool for best surface finish

High-speed machining (HSM) has emerged as a key technology in rapid tooling and manufacturing applications. Compared with traditional machining, the cutting speed, feed rate has been great progress, and the cutting mechanism is not the same. HSM with coated carbide cutting tools used in high-speed, high temperature situations and cutting more efficient and provided a lower surface roughness. However, the demand for high quality focuses extensive attention to the analysis and prediction of surface roughness and cutting force as the level of surface roughness and the cutting force partially determine the quality of the cutting process. This paper presents an optimization method of the machining parameters in high-speed machining of stainless steel using coated carbide tool to achieve minimum cutting forces and better surface roughness. Taguchi optimization method is the most effective method to optimize the machining parameters, in which a response variable can be identified. The standard orthogonal array of L₉ (3⁴) was employed in this research work and the results were analyzed for the optimization process using signal to noise (S/N) ratio response analysis and Pareto analysis of variance (ANOVA) to identify the most significant parameters affecting the cutting forces and surface roughness. For such application, several machining parameters are considered to be significantly affecting cutting forces and surface roughness. These parameters include the lubrication modes, feed rate, cutting speed, and depth of cut. Finally, conformation tests were carried out to investigate the improvement of the optimization. The result showed a reduction of 25.5% in the cutting forces and 41.3% improvement on the surface roughness performance.     

塑料瓶吹塑模具的高速铣削加工工艺

介绍了塑料瓶吹塑模具的高速铣削加工的工艺规划,包括走刀路线的规划、铣削方式的选定、铣削相关参数的确定、表面质量的估算,并使用Catia软件对整个加工过程进行了虚拟实现,为真实加工做好前期准备,检查加工可能发生的问题,生成数控机床需要的NC代码.     

Complex cast parts with rapid tooling: rapid manufacturing point of view

Rapid manufacturing techniques are typically either material addition or material subtraction processes. Direct metal laser sintering (DMLS) is a material addition process that enables the rapid creation of complex parts via laser sintering (or electron beam melting) whereby layers of powder are deposited and then partially or totally melted using a laser. This technique is directly challenging other more rapid, but subtractive manufacturing processes like high-speed milling (HSM) and electro-erosion. In terms of machining, the capacity of rapid tooling to quickly manufacture complex shapes, like conformal cooling channels, is an advantage (Boillat in J Phys IV 12(Pr 11):27–38, 2002, Au in Int J Adv Manuf Technol 34:496–515, 2007). On the other hand, the dimensional accuracy of this process is definitely lower than that obtained using HSM. To our knowledge, no systematic study of the dimensional capacities of this process has yet been carried out. In this article, through the geometrical study of the quality of the obtained parts, the capability of this process is studied and verified with respect to the required constraints of the die casting method.     

新钢1580热轧层流冷却温度控制的研究

主要介绍了新钢层流冷却设备及其自控制系统,根据现场使用的工况采用了先进的数学模型与控制技术,优化参数与现场工艺装备,提高了卷取温度命中率和产品性能.     

高速铣削淬硬钢时切削载荷平稳化研究

和传统的铣削加工相比,高速铣削淬硬钢更需要稳定的切削载荷,以尽可能减少刀具碎裂和过度磨损。本研究借助三向压电石英测力仪,使用TiAlN涂层球形端铣刀,在13500 r/min的转速下,对淬火45#钢(47HRC~48HRC)进行了高速铣削试验,建立了高速铣削下的多项式切削力试验模型,模拟了以恒定切削力为目标、优化进给率的加工实例。结果显示,稳定的切削载荷能有效地提高加工效率,避免刀具剧烈磨损。     

Extraction Fuzzy Linguistic Rules from Neural Networks for Maximizing Tool Life in High-speed Milling Process

In metal cutting industry it is a common practice to search for optimal combination of cutting parameters in order to maximize the tool life for a fixed minimum value of material removal rate(MRR). After the advent of high-speed milling(HSM) pro cess, lots of experimental and theoretical researches have been done for this purpose which mainly emphasized on the optimization of the cutting parameters. It is highly beneficial to convert raw data into a comprehensive knowledge-based expert system using fuzzy logic as the reasoning mechanism. In this paper an attempt has been presented for the extraction of the rules from fuzzy neural network(FNN) so as to have the most effective knowledge-base for given set of data. Experiments were conducted to determine the best values of cutting speeds that can maximize tool life for different combinations of input parameters. A fuzzy neural network was constructed based on the fuzzification of input parameters and the cutting speed. After training process, raw rule sets were extracted and a rule pruning approach was proposed to obtain concise linguistic rules. The estimation process with fuzzy inference showed that the optimized combination of fuzzy rules provided the estimation error of only 6.34 m/min as compared to 314 m/min of that of randomized combination of rules.     

Double spiral tool-path generation and linking method for complex pocket machining

Complex pockets with one or more islands have been widely used in industrial and manufacturing production. In this paper, a new double spiral tool-path generation and linking method are proposed for complex pockets with islands which can be used for high-speed machining (HSM) is used. Taking into account the path interval, step length and other processing parameters, precise milling can be achieved without cutter lifting and retraction motions to guarantee machining accuracy and reduce processing time. The method has been implemented in several simulations and validated successfully through the actual machining of a complicated pocket. The results indicate that this method is superior to other existing machining methods, and it can achieve HSM of complicated shaped pockets based on parametric surface.     

基于RBF神经网络的难加工材料高速铣削力预报研究

切削力的预报是切削加工的重要研究方向.文中运用RBF神经网络建立了铣削力预测模型,将预报结果与试验真值以及由回归分析处理的结果进行对比验证,结果表明此方法可行,为切削参数优化和数据库研制提供了依据.