Optimization of machining conditions for turning cylindrical stocks into continuous finished profiles

The optimization problem involving straight turning operations for bar components with constant finished diameters has received extensive attention. In the real-world turning processes on a computer numerical control (CNC) machine, the cylindrical stocks are frequently machined into their desired continuous profiles. Such turning processes require not only straight turning but also face turning, taper turning and circular turning to complete the removal of stock. However, machining models proposed in the literature do not simultaneously consider these turning operations to optimize machining conditions (parameters). This study formulates a machining model to optimize the machining conditions for turning cylindrical stocks into continuous finished profiles, thereby extending the applications of machining optimization. The usefulness of the developed machining model is finally established through a test example.     

Experimental investigation of cutting parameters in machining of 100Cr6 with tangential turn-milling method

The turn-milling methods for machining operation have been developed to increase efficiency of conventional machines recently. These methods are used especially by coupling some apparatuses on the computer numerical control (CNC) machine to decrease the production time and machine costs, ensure the maximum production and increase the quality of machining. In this study, 100Cr6 bearing steel extensively used in industry has been machined by tangential turn-milling method. This paper presents an approach for optimization of the effects of the cutting parameters including cutter speed, workpiece speed, axial feed rate, and depth of cut on the surface roughness in the machining of 100Cr6 steel with tangential turn-milling method by using genetic algorithm (GA). Tangential turning-milling method has been determined to have optimum effects of cutting parameters on the machining of 100Cr6 steel. The experimental results show that the surface roughness quality is close to that of grinding process.     

一种大型铝合金薄壁件高效加工工艺研究

通过对某型号卫星贮箱支架的数控加工实践,研究了大型铝合金框架式薄壁结构件的高效数控加工工艺技术。通过合理选择机械加工规程和工艺参数,解决了这类零件加工过程中极易超差等难题,可靠地满足了型号研制的要求。同时利用Mastercam X软件研究了高效数控加工问题。     

A simulated annealing approach for optimization of multi-pass turning operations

In this paper, an optimization algorithm based on the simulated annealing (SA) algorithm and the Hooke-Jeeves pattern search (PS) is developed for optimization of multi-pass turning operations. The cutting process is divided into multi-pass rough machining and finish machining. Machining parameters are determined to optimize the cutting conditions in the sense of the minimum unit production cost under a set of practical machining constraints. Experimental results indicate that the proposed nonlinear constrained optimization algorithm, named SA/PS, is effective for solving complex machining optimization problems. The SA/PS algorithm can be integrated into a CAPP system for generating optimal machining parameters.     

Constrained multi-objective optimization of EDM process parameters using kriging model and particle swarm algorithm

This paper investigates the highly nonlinear relationship between process parameters and machining responses, including material removal rate (MRR), surface roughness (SR), and electrode wear rate (EWR) of electric discharge machining (EDM) using Kriging model. Subsequently, an emerging multi-objective optimization algorithm called particle swarm is used to determine the best machining conditions that not only maximize the machining speed but also minimize the EWR with a constraint of the SR. The experiment was carried out with P20 steel on a CNC EDM machine using copper electrode. The research result shows that the MRR increases sharply when increasing the discharge current just like other researches pointed out. However, the relationship between EWR and current is complicated. EWR appears the minimum value when the current is around 30?A. The speed of change of MRR per unit of EWR is the highest when the SR is around 14.5?µm. The combination of Kriging regression model and particle swarm optimization is considered as an intelligent process modeling and optimization of EDM machining. The proper selection of process parameters helps the EDM operator to reduce the machining time and cost.     

Load spectra of CNC machine tools

Load spectra of CNC machine tools are described in this paper; 112 CNC machine tools have been traced for 3 years. Data including machining parameters and conditions, drawings and NC programs of parts, process cards and specifications of each individual CNC machine tool are gathered. A database containing this information is designed. The loads of CNC machine tools are calculated and the distribution parameters of loads are estimated. A fuzzy multicriteria comprehensive evaluation method is applied to evaluate the fitness of the distribution model. This methodology lays a foundation for the reliability designs of CNC machine tools. Copyright © 2000 John Wiley & Sons, Ltd.     

A GA-based approach to machining operation sequencing for prismatic parts

This paper presents a study of using a genetic algorithm (GA) method to select the machining operation sequence for prismatic parts. Four types of process planning rules including precedence rules, clustering rules, adjacent order rules and optimization rules are considered and are encompassed quantitatively in the fitness calculations for alternative operation sequences. The impact of variations of the rules on the result of operation sequencing and that of GA parameters on the solution efficiency are discussed through analysis of examples and experiments. The proposed genetic algorithm proves effective for machining operation sequencing of prismatic parts, by incorporating various production environment considerations into process planning.     

自由曲面的CNC直接插补加工技术

在ＣＮＣ系统上直接根据曲面几何定义与加工工艺参数对多轴贡面加工的连续运动轨迹进行实时插补控制，在ＣＮＣ上直接在ＡＰＴ高级语言编程，极大地科化了零件程序，并可在线修改与补偿机床运动结构、刀具形状尺寸及加工作量等工艺参数，使曲在线曲面精加工经济而高效。在单ＣＰＵ硬件环境下实现了从一般二次曲线到复杂的参数组合曲面，从两轴加工到复杂的五轴联动功能，可采用多种加工刀具与加工方式，可实时检测与处理刀具干涉，并     

基于有限元分析的薄壁圆环零件加工工艺研究

目的 针对薄壁圆环零件刚性差、强度弱、加工过程中易发生受力变形的难题,基于薄壁圆环零件加工成形工艺,优化零件的加工工艺和装夹方式。方法 考虑到工艺对零件加工质量的影响,对零件的加工方法和装夹方式进行研究,提出一种新的加工工装,运用ANSYS软件对零件装夹受力情况和振动变形进行有限元模拟仿真分析。结果 该工装不仅能够防止零件发生应力集中,还提升了零件加工精度和表面质量,工装设计为一夹一顶方式,只需调整顶尖压紧力便可确保圆环件在加工中不会发生变形,同时拆装方便,提高了生产效率。结论 对于薄壁圆环件的数控加工,可通过科学设计零件加工工艺流程和装夹工装,解决零件受力变形问题,保证薄壁圆环零件的尺寸、形位公差和表面粗糙度符合要求,提高了生产加工效率,满足产品批量生产使用要求,为类似薄壁件的加工提供了参考。     

Virtual prototyping and manufacturing planning by using tri-dexel models and haptic force feedback

This paper presents a new method of using the tri-dexel volumetric models and a haptics force feedback for virtual prototyping and manufacturing planning. In the proposed method, the initial polyhedral surface model is converted to a tri-dexel volumetric model by using a depth-peeling dexelization algorithm. In the virtual prototyping process, the tri-dexel volumetric model is updated by the swept volume of a moving cutter via a haptic force feedback interface device. A collision detection algorithm is proposed for the virtual sculpting and the pencil-cut planning with real-time haptic force feedback to the users. Tool paths are generated for machining the virtual sculpted parts via the simulation and verification on a virtual CNC machine tool before they are actually machined. Computer implementation and practical examples are also presented in this paper. The proposed method enables the haptic-aided virtual prototyping and manufacturing planning of complex surface parts.     

Virtual prototyping and manufacturing planning by using tri-dexel models and haptic force feedback

This paper presents a new method of using the tri-dexel volumetric models and a haptics force feedback for virtual prototyping and manufacturing planning. In the proposed method, the initial polyhedral surface model is converted to a tri-dexel volumetric model by using a depth-peeling dexelization algorithm. In the virtual prototyping process, the tri-dexel volumetric model is updated by the swept volume of a moving cutter via a haptic force feedback interface device. A collision detection algorithm is proposed for the virtual sculpting and the pencil-cut planning with real-time haptic force feedback to the users. Tool paths are generated for machining the virtual sculpted parts via the simulation and verification on a virtual CNC machine tool before they are actually machined. Computer implementation and practical examples are also presented in this paper. The proposed method enables the haptic-aided virtual prototyping and manufacturing planning of complex surface parts.     

基于VERICUT包装容器模具数控加工仿真及优化技术

在包装容器生产中,关键的是容器模具的加工,而VERICUT是一款既能完成加工仿真又能进行较好优化的三维软件,可实现加工轨迹仿真和机床仿真,图形逼真,而且可通过已有经验数据库来调整各个工序的进给率等参数,提高加工效率,实现NC代码的优化.结合某塑料容器模具的实例展现了VERICUT环境下数控加工仿真及优化的过程,为包装容器模具的生产提供有意的指导.     

Intelligent tool path correction for improving profile accuracy in CNC turning

This paper presents the development of an intelligent predictive tool for improving the accuracy of parts produced on CNC turning centers. Actual dimensions and shape (form) produced on components during machining differ from the nominal dimensions commanded in the CNC program. These dimensional and form errors on parts depend on a variety of factors such as tool/work deflections, machine tool accuracy, machining conditions etc. These errors, if predicted, can be used to correct the ideal CNC code and thus improve the part accuracy in CNC machining. In the present work artificial neural networks are used to capture the complex relationship between the errors on the component and the input process conditions. Significant improvement in part accuracy has been obtained using the corrected CNC code during machining.     

基于直线往复单智能RGV系统单工序调度研究

针对直线布局轨道式智能加工系统单自动引导车(rail guide vehicle, RGV)单工序作业调度进行研究。考虑到智能RGV与数控机床(CNC machine tools)的特点,建立了给定时间内RGV与CNC机床配合物料加工下料用时之和最小化为目标的非线性整数规划模型。当加工物料数目比较多时,求解该问题非常耗时。根据RGV与CNC机床加工物料调度特征,提出计算机模拟仿真算法对问题进行求解。利用3组系统参数对模型及算法的有效性和实用性进行了检验分析,最后给出了最优调度计划的实际运行结果及结论。     

Machining error compensation using radial basis function network based on CAD/CAM/CAI integration concept

This paper presents a machining error compensation methodology using an Artificial Neural Network (ANN) model trained by an inspection database of the On-Machine-Measurement (OMM) system. This is an application of the CAD/CAM/CAI integration concept. First, to improve machining and inspection accuracies, the geometric errors of a three-axis CNC machining centre and the probing errors are compensated using a closed-loop configuration. Then, a workpiece is machined using the machining centre, and the error distributions of the machined surface are inspected using OMM. In order to analyse efficiently the machining errors, two characteristic error parameters, W err and D err , are defined. Subsequently, these parameters are modelled using a Radial Basis Function (RBF) network approach as an ANN model. Based on the RBF network model, the tool path is corrected to effectively reduce the errors using an iterative algorithm. In the iterative algorithm, the changes of the cutting conditions can be identified according to the corrected tool path. In order to validate the approaches proposed in this paper, an experimental machining process is performed, and the results are evaluated. As a result, about 90% of machining error reduction can be achieved through the proposed approaches.     

Automatic identification of aspect vectors and geometrical validation of 2.5D parts

A part can be viewed from infinite viewpoints, but it may look 2.5D from some specific viewpoints only. Its solid model may be arbitrarily oriented in space as per the designer's convenience in positioning it in an overall assembly. However, this orientation may not be suitable for proper and economic manufacturing. A manufacturing engineer has to reorient the part in such a way that it looks a 2.5D part, if possible. Manufacturing of 2.5D parts is economic and efficient since standard machine tools, cutters and clamping devices are used. An algorithm is presented to automatically determine the machining coordinate system that is convenient for machining. The selected coordinate system specifies the approach directions (aspect vectors) for machining the part. The underlying principle of the algorithm is the generation of machined faces on a three-axis CNC vertical milling machine with a set of flat-bottomed end-milling cutters and standard clamping devices. The part can have only planar and cylindrical faces under such machining conditions. Another algorithm is presented to validate whether or not a part falls under the 2.5D domain. Both algorithms are required since the present state of feature-recognition technology is limited to 2.5D parts. There is a need for a pre-processing system that automatically determines the aspect vectors for a 2.5D part and checks whether or not the design fed to the feature-recognition system is valid.     

Machining conditions-based preventive maintenance

In this study we propose an operating conditions-based preventive maintenance (PM) approach for computer numerical control (CNC) turning machines. A CNC machine wears according to how much it is used and the conditions under which it is used. Higher power or production rates result in more wear and higher failure rates. This relationship between the operating conditions and maintenance requirements is usually overlooked in the literature. On CNC turning machines we can control the machining conditions such as cutting speed and feed rate, which in turn affect the PM requirements of the CNC machine. We provide a new model to link the PM decisions to the machining conditions selection decisions, so that these two decision-making problems can be solved together by considering their impact on each other. We establish that our proposed geometric programming model captures the related cost terms along with the technological restrictions of CNC machines. The proposed preventive maintenance index function can be used to provide an intelligent CNC machine degradation assessment.     

Optimization of multipass turning operations with genetic algorithms

The paper proposes a new optimization technique based on genetic algorithms for the determination of the cutting parameters in multipass machining operations. The cutting process simultaneously considers multipass rough machining and finish machining. The optimum machining parameters are determined by minimizing the unit production cost subject to practical machining constraints. The cutting model formulated is a non-linear-constrained programming (NCP) problem with 20 machining parameter constraints. Experimental results show that the proposed genetic algorithm-based procedure for solving the NCP problem is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.     

The Perrego algorithm: a flexible machine-component grouping algorithm based on group technology techniques

The Perrego algorithm, which forms machining cells based upon the weighted importance of the parts which they produce, is presented. Classification and coding (C&C) and production flow analysis (PFA) were synthesized into one single algorithm using similarity coefficients and a cluster identification algorithm to combine the two methods. The resulting unique algorithm's advantage is the utilization of morphological information, such as manufacturing production quantity requirements, with the technological attributes of the parts: cells were formed with minimal amounts of parts travelling between cells. The algorithm also considers the economics of machine duplication for forming independent cells.