Surface generation modeling of micro milling process with stochastic tool wear

Micro milling is widely used to manufacture miniature parts and features at high quality with low set-up cost. To achieve a higher quality of existing micro products and improve the milling performance, a reliable analytical model of surface generation is the prerequisite as it offers the foundation for surface topography and surface roughness optimization. In the micro milling process, the stochastic tool wear is inevitable, but the deep influence of tool wear hasn't been considered in the micro milling process operation and modeling. Therefore, an improved analytical surface generation model with stochastic tool wear is presented for the micro milling process. A probabilistic approach based on the particle filter algorithm is used to predict the stochastic tool wear progression, linking online measurement data of cutting forces and tool vibrations with the state of tool wear. Meanwhile, the influence of tool run-out is also considered since the uncut chip thickness can be comparable to feed per tooth compared with that in conventional milling. Based on the process kinematics, tool run-out and stochastic tool wear, the cutting edge trajectory for micro milling can be determined by a theoretical and empirical coupled method. At last, the analytical surface generation model is employed to predict the surface topography and surface roughness, along with the concept of the minimum chip thickness and elastic recovery. The micro milling experiment results validate the effectiveness of the presented analytical surface generation model under different machining conditions. The model can be a significant supplement for predicting machined surface prior to the costly micro milling operations, and provide a basis for machining parameters optimization.     

求解作业车间调度问题的全局邻域搜索方法

采用传统的关键邻域搜索方法求解作业车间调度问题时,往往容易陷入局部极值而且难以跳出.为此,提出了一种具有动态调整能力的全局邻域交换策略,该策略有可能产生大量的不可行调度,需要一种筛选方法加以过滤.证明了一个新的邻域交换性质,利用该性质可以对所得调度方案作可行性约束判定,从而有效地过滤掉不可行调度.在此基础上,提出了一种求解作业车间调度问题的算法.最后,取不同规模的Benchmark问题算例对该算法进行测试,结果表明,无论从解的质量还是计算时间都取得了较好的效果.     

求解柔性车间作业调度的知识型协同演化方法

提出了一种求解柔性车间作业调度的知识型协同演化方法。在该方法中,各个种群采用不同的进化方法和参数设置来推进各自的演化进程;种群之间通过相互的资源竞争和信息共享,共同推动整体算法的进化进程。采用柔性作业车间调度问题的15个标准实例进行实验,结果表明所提方法在优化性能方面优于近期公开发表的七种典型方法。     

多目标柔性作业车间分批优化调度

为解决多目标柔性作业车间分批调度问题,提出了一种基于粒子群算法的多目标柔性分批调度算法。提出了一种基于游标的柔性批量分割方法,并采用一种批量分割与加工工序相融合的粒子编码方法,使得该算法不但可根据机床负荷将工件分割成具有柔性批量的多个子批,而且可使子批工艺路线选取及加工排序同时得到优化。算法引入了决策者的偏好信息,用于引导算法的搜索方向,使搜索结果集中于决策者感兴趣的Pareto边沿,避免了决策者在众多非劣解中做出困难选择。通过实例仿真,对算法性能进行了比较分析和评价,结果表明了算法的有效性和可行性。最后,从生产实际出发给出了算例,证明了算法的有效性和对生产实践的指导作用。     

Influence of tool wear on surface roughness in hard turning using differently shaped ceramic tools

Hard turning has been applied in many cases in producing bearings, gears, cams, shafts, axels, and other mechanical components since the early 1980s. Mixed ceramics (aluminum oxide plus TiC or TiCN) is one of the two cutting tool materials (apart from PCBN) widely used for finish machining of hardened steel (HRC 50–65) parts, especially under dry machining conditions and moderate cutting speed ranging from 90 to 120 m/min. This paper reports an extensive characterization of the surface roughness generated during hard turning (HT) operations performed with conventional and wiper ceramic tools at variable feed rate and its changes originated from tool wear. Moreover, it compares some predominant tool wear patterns produced on the two types of ceramic inserts and their influence on the alteration of surface profiles. After the hard turning tests, the relevant changes of surface profiles and surface roughness parameters were successively registered and measured by a stylus profilometer. In this investigation, a set of 2D surface roughness parameters, as well as profile and surface characteristics, such as the amplitude distribution functions, bearing area curves and symmetrical curves of geometrical contact obtained for the machined surface, were determined and analyzed. A novel aspect of this research is that the notch wear progress at the secondary cutting (trailing) edges was found to produce the substantial modifications of the individual irregularities, and constitute the altered surface profiles. Moreover, this research contributes to practical aspects of HT technology due to exploring the relations between the tool state at different times within the tool life and the relevant surface roughness characterization.     

Clustering algorithms to optimize the tool handling system management in an FMS

Tool management is recognized as a critical issue in flexible manufacturing facilities management. This article addresses the issue of tool management in a flexible system installed in an avionics components factory. The system is composed of two machining centers equipped with local tool magazines of limited capacity. A tool handling system is in charge of tool movements between the tool room and the two machines. Each machine is able to perform any operation, provided that it is equipped with the suitable tool. In this kind of installation, tool allocation must be determined, and tool movements must be synchronized in order to minimize operating costs, or, equivalently, maximize the productivity of the system. We propose an approach to production planning based on a clustering algorithm, which takes into account the tool requirements of each part program in the production batch. We also propose two different heuristics for the scheduling problem. A case study was conducted on the facility mentioned above. Two conflicting objectives can be identified for this kind of production system: the reduction of tools to be shared among machines and the reduction of workload unbalance. The tests and comparison made demonstrate how the proposed procedure leads to superior results in terms of both objectives.     

面向绿色制造的一类模糊调度模型及其算法

绿色制造是一种综合考虑环境影响和资源效率的现代制造模式，由于其生产系统的复杂性和不确定性，使得工序的加工时间和生产成本等数据用模糊数表示更加符合生产实际。为优化调度过程中的产品质量、生产成本、资源消耗、环境污染和生产周期，建立了面向绿色制造的模糊调度模型。将多目标遗传算法与模糊优选技术相结合对该模型求解，并用案例验证了模型的实用性和算法的可行性。     

工艺路线可变的双资源双目标车间调度优化

将遗传算法与启发式调度规则相结合 ,研究了工艺路线可变的双资源双目标的作业车间调度优化问题。在探讨过程中 ,不仅考虑到了每个工件有几条可行的工艺路线 ,而且考虑到了工件的调度受到机床、工人等资源的制约 ,以及在加工过程中发生的储存费用、机床的加工费用和工人的劳动费用对工件调度的影响 ,设计了以生产周期和生产成本综合优化为目标的适应度函数。启发式调度规则使该算法具有较高的局部搜索效率 ,遗传算法保证了解的全局最优性。最后给出了算例 ,并对计算结果进行了分析和讨论     

Modeling of tool wear during hard turning with self-propelled rotary tools

In this paper, an attempt is made to evaluate the self-propelled rotary carbide tool performance during machining hardened steel. Although several models were developed and used to evaluate the tool wear in conventional tools, there were no attempts in open literature for modeling the progress of tool wear when using the self-propelled rotary tools. Flank wear model for self-propelled rotary cutting tools is developed based on the work-tool geometric interaction and the empirical function. A set of cutting tests were carried out on the AISI 4340 steel with hardness of 54–56 HRC under different cutting speeds and feeds. The progress of tool wear was recorded under different interval of time. A genetic algorithm was developed to identify the constants in the proposed model. The comparison of measured and predicted flank wear showed that the developed model is capable of predicting the rate of rotary tool flank wear progression.     

数控机床刀具磨损监测实验数据处理方法研究

数控机床刀具磨损监测对于提高数控机床利用率,减小由于刀具破损而造成的经济损失具有重要意义.有针对性地回顾了国内外各种分析刀具磨损信号方法的研究工作,详细叙述了功率谱分析法、小波变换、人工神经网络以及多传感器信息融合技术的实现形式.通过比较各种数据处理方法的优缺点,提出基于混合智能多传感器信息融合技术是数控机床刀具磨损监测实验数据处理的未来发展的主要方向.     

Study on job shop scheduling with sequence-dependent setup times using biological immune algorithm

Sequence-dependent setup times are one of the most important factors for the optimization of scheduling the production targets. Usually, they include the changing of tools, fixtures, cutting tools and the cleaning of production equipments. Some of them are relevant not only to the sequence requirement of the products to be processed on the equipment, but also to the processing requirement of the adjoining sequence. In this paper, a job shop scheduling problem with sequence-dependent setup times is described. A mixed integer program model is adopted to deal with this type of problem, and a scheduling algorithm based on biologic immunity mechanism is introduced. The result shows that the antibody encoding method and the mechanism of antibody proliferation and suppression can not only ensure the diversity of the antibody, but can also greatly improve the effectiveness of dealing with complex problems. Finally, a scheduling problem of finishing processing for a woollen mill is analyzed with its result described.     

Data acquisition and monitoring in machine tools with CNC of open architecture using internet

This paper presents a proposed system for data acquisition and monitoring of manufacturing process in machine tools with CNC of open architecture, using the Internet. It was applied to evaluate workpiece dimension and, indirectly, tool wear, as well as sharing shop floor information, in real time, in any place through Intranet and/or Internet, aiding the whole integration of the manufacturing system. The proposed system was developed and tested initially in a CNC lathe with open architecture. However, it can be extended to other machines and processes, lines or cells of mass production as well. In the first experiments, the system was capable of maintaining uniform, within a closer tolerance, the diameter of a batch of 30 workpieces, changing from an ISO IT13 quality to ISO IT09. It was also possible to share on-line information about the process, production and technological parameters, by Intranet/Internet, using only a HTML page navigator .     

基于遗传算法的作业车间提前/拖期调度问题

针对带有交货期窗口硬约束并对提前/拖期零件进行惩罚的一类作业车间调度问题,设计了一种改进型遗传算法,该算法采用＂逆向后推＂和＂顺向前拉＂相结合的两阶段求解策略。针对部分染色体在解码过程中违反交货期窗口硬约束而产生非法解的问题,采用基于关键路径的染色体修复方法来调整染色体基因序列,以期实现在满足交货期窗口硬约束的同时降低零件拖期成本;在保持第一调度阶段拖期成本不变的基础上,采用基于逆向重调度的目标值修订方法来延迟零件开工时间,以降低在制品流动成本和成品提前库存成本。通过80组调度测试用例的仿真结果表明,该算法在降低调度总成本和拖期成本方面具有一定的优势。     

数控机床刀具磨损监测方法研究

数控机床刀具磨损监测对于提高数控机床利用率,减小由于刀具破损而造成的经济损失具有重要意义.文章有针对性地回顾了国内外各种刀具磨损监测方法的研究工作,详细叙述了切削力监测法、切削噪声监测法、功率监测法、声发射监测法、电流监测法以及基于多传感器监测法等六种刀具磨损监测方法.本文通过比较各种监测方法的优缺点,提出基于多传感器监测法是数控机床刀具磨损监测方法的未来发展的主要方向.     

Mirror surface machining of high-alloy steels by elliptical vibration cutting with single-crystalline diamond tools: Influence of alloy elements on diamond tool damage

Elliptical vibration cutting with single-crystalline diamond tools is applied to mirror surface machining of high-alloy steels such as cold work die steels and high-speed tool steels with a hardness of more than 60 HRC. Although practical mirror surface machining of hardened die steels such as Stavax (modified AISI 420) with a hardness of 53 HRC has been realized with the elliptical vibration cutting, lives of single-crystalline diamond tools are not sufficiently long in machining of some high-alloy steels, that may be caused by a large amount of alloy elements. In order to clarify the influence of the alloy elements on the diamond tool damage, the elliptical vibration cutting experiments are conducted on six kinds of high-alloy steels and four kinds of pure metals which are the same as the alloy elements. Mechanical properties of the alloy steels, i.e. difference in hardness between carbides and matrices, and the number of small carbides, are measured, and their influence on the micro-chippings are investigated. The chemical states of the alloy elements in high-alloy steels are analyzed using an X-ray diffraction (XRD) and an electron probe micro analyzer (EPMA), and their influence on the tool wear is discussed. Based on the investigation, a mirror surface machining of DC53, which has a high hardness of 62.2 HRC and the best machinability in the tested high-alloy steels, is demonstrated, and a mirror surface with a roughness of Rt 0.05 μm is obtained successfully.     

High accurate interpolation of NURBS tool path for CNC machine tools

Feedrate fluctuation caused by approximation errors of interpolation methods has great effects on machining quality in NURBS interpolation, but few methods can efficiently eliminate or reduce it to a satisfying level without sacrificing the computing efficiency at present. In order to solve this problem, a high accurate interpolation method for NURBS tool path is proposed. The proposed method can efficiently reduce the feedrate fluctuation by forming a quartic equation with respect to the curve parameter increment, which can be efficiently solved by analytic methods in real-time. Theoretically, the proposed method can totally eliminate the feedrate fluctuation for any 2nd degree NURBS curves and can interpolate 3rd degree NURBS curves with minimal feedrate fluctuation. Moreover, a smooth feedrate planning algorithm is also proposed to generate smooth tool motion with considering multiple constraints and scheduling errors by an efficient planning strategy. Experiments are conducted to verify the feasibility and applicability of the proposed method. This research presents a novel NURBS interpolation method with not only high accuracy but also satisfying computing efficiency.     

数控车刀尖R补偿的分析和应用

分析数控车削加工中的刀尖R补偿,详细说明刀尖R补偿的原理与使用方法。     

TS/MP混合算法求解作业车间JIT调度问题

针对作业车间准时制生产调度这类典型的非正规性能指标调度问题,采用禁忌搜索和数学规划的混合策略进行求解,即在每一迭代搜索过程中,首先由禁忌搜索得到各机器上的工序加工序列,再调用数学规划方法来优化各工序的开工时间。另外,设计了一种包含交换和插入两种移动操作的邻域构造方法。邻域构造方法通过交换相邻加工工序对来在当前解的邻域内寻优,而将目标工序插入块之间的间隙以解除块对相关工序的束缚,这种邻域结构有助于提高禁忌搜索求解准时制生产调度问题的搜索效率。48个标准算例的仿真结果证明禁忌搜索/数学规划方法在准时制生产调度解的质量方面具有一定优势。     

Wear behavior of some cutting tool materials in hard turning of HSS

This study presents an assessment of the performance of four cutting tool in the machining of medium hardened HSS: polycrystalline c-BN (c-BN+TiN), TiN coated polycrystalline c-BN (c-BN+TiN), ceramic mixed alumina (Al₂O₃+TiC), and coated tungsten carbide (TiN coated over a multilayer coating (TiC/TiCN/Al₂O₃)). The Al₂O₃+TiC and the coated carbide tools can outperform both types of c-BN at high cutting speeds. Raman and SEM mapping revealed an alumina tribo-layer that protects the surface of the Al₂O₃+TiC cutting tool. The high chemical and thermal stability of Al₂O₃ tribo-films protects the tool substrate because it prevents the heat generated at the tool/chip interface from entering the tool core.     

Comparative evaluation of machinability characteristics of Nimonic C-263 using CVD and PVD coated tools

Machining of Nimonic C-263 has always been a challenging task owing to its hot strength, low thermal conductivity, tendency to work harden and affinity towards tool materials. Although coated tools have been used to overcome some of these challenges, selection of coated tool with appropriate deposition technique is of immense significance. The current study attempts to comparatively evaluate various performance measures in machining of Nimonic C-263 such as surface roughness, cutting force, cutting temperature, chip characteristics, and tool wear with particular emphasis on different modes of tool failure for commercially available inserts with multi-component coating deposited using chemical vapour deposition (CVD) and physical vapour deposition (PVD) techniques. Influence of cutting speed (V_c) and machining duration (t) has also been investigated using both coated tools. The study demonstrated remarkable decrease in surface roughness (74.3%), cutting force (6.3%), temperature (13.4%) and chip reduction coefficient (22%) with PVD coated tool consisting of alternate layers of TiN and TiAlN over its CVD coated counterpart with TiCN/Al₂O₃ coating in bilayer configuration. Severe plastic deformation and chipping of cutting edge and nose, abrasive nose and flank wear along with formation of built-up-layer (BUL) were identified as possible mechanisms of tool failure. PVD coated tool successfully restricted different modes of tool wear for the entire range of cutting speed. Superior performance can be attributed to the hardness and wear resistance properties, thermal stability due to presence of TiAlN phase and excellent toughness owing to PVD technique and multilayer architecture.