Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts

The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.

METHOD FOR SUPPRESSING CUTTING CHATTER IN NUMERICAL CONTROL MACHINE TOOLS

A new method for suppressing cutting chatter is studied by adjusting servo parameters of the numerical control （NC） machine tool and controlling the limited cutting width. A model of the cutting system of the NC machine tool is established. It includes the mechanical system, the servo system and the cutting chatter system. Interactions between every two systems are shown in the model. The cutting system stability is simulated and relation curves between the limited cutting width and servo system parameters are described in the experiment. Simulation and experimental results show that there is a mapping relation between the limited cutting width and servo parameters of the NC machine tool, and the method is applicable and credible to suppress chatter.

Bayesian networks modeling for thermal error of numerical control machine tools

The interaction between the heat source location, its intensity, thermal expansion coefficient, the machine system configuration and the running environment creates complex thermal behavior of a machine tool, and also makes thermal error prediction difficult. To address this issue, a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented. The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques. Due to the effective combination of domain knowledge and sampled data, the BN method could adapt to the change of running state of machine, and obtain satisfactory prediction accuracy. Ex- periments on spindle thermal deformation were conducted to evaluate the modeling performance. Experimental results indicate that the BN method performs far better than the least squares (LS) analysis in terms of modeling estimation accuracy.

Bayesian zero-failure reliability modeling and assessment method for multiple numerical control(NC) machine tools

A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.

Real-Time Data and Visualization Monitoring of Computer Numerical Control Machine Tools Based on Hyper Text Markup Language 5

In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.

Carbon Emission Modeling and Analysis in Manufacturing Process for Numerical Control Machine Tools

Reducing carbon emissions( CEs) is the urgent demand all over the world. In order to realize the low-carbon numerical control( NC) machining, the evaluation model of a part's manufacturing carbon emission with NC machine tools was built by considering the influences of the cutting tool geometrical parameters.The manufacturing CEs were produced by electric power,cutting tools,and cutting fluid consumed in manufacturing process. The parameters of cutting tools affected not only the CEs,but also the machining quality. Then the actual constraint models of the machine performance,machining quality were given in order to optimize the cutting parameters and achieve the low-CEs. Finally,a case was given to analyze the influences of the cutting tool angles on the manufacturing CEs. The results show that the CEs decrease as the rake angle and edge angle increase under the constraints of the machine specifications and machining quality.

Specialized Numerical Control Plasma Cutting Machine

The large thermal cutting equipment——The DHG. CNC numerical control plasma cutting machine is produced by The Ha’erbin Welding & Cutting Equipment Co. It specializes in the precise formation and baiting of nonferrous boards and thin carbon steel plates at a high speed. It avoids the disadvantage of flame cutting, which cannot cut nonferrous and thin steel plates.

CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

Building cyber-physical system(CPS) models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control(CNC) system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control(NC) processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.

Patterns of CNC Machine Tool Reference Return and Its Trouble Shooting Methods

This paper presents four patterns of reference-return positions for CNC machine tools and analyses some causes of return reference troubles by showing typical examples of trouble shooting.Finally,it introduces several methods of trouble shooting.

Toward Intelligent Machine Tool

With the development of modern information technology-and particularly of the new generation of artificial intelligence(AI)technology-new opportunities are available for the development of the intelligent machine tool(IMT).Based on the three classical paradigms of intelligent manufacturing as defined by the Chinese Academy of Engineering,the concept,characteristics,and systemic structure of the IMT are presented in this paper.Three stages of machine tool evolution-from the manually operated machine tool(MOMT)to the IMT-are discussed,including the numerical control machine tool(NCMT),the smart machine tool(SMT),and the IMT.Furthermore,the four intelligent control principles of the IMT-namely,autonomous sensing and connection,autonomous learning and modeling,autonomous optimization and decision-making,and autonomous control and execution-are presented in detail.This paper then points out that the essential characteristic of the IMT is to acquire and accumulate knowledge through learning,and presents original key enabling technologies,including the instruction-domain-based analytical approach,theoretical and big-data-based hybrid modeling technology,and the double-code control method.Based on this research,an intelligent numerical control(INC)system and industrial prototypes of IMTs are developed.Three intelligent practices are conducted,demonstrating that the integration of the new generation of AI technology with advanced manufacturing technology is a feasible and convenient way to advance machine tools toward the IMT.

The Innovation of CNC Machine Interface Based on DNC System

This paper describes the innovation schemes of the interface of a CNC machine which cannot communicate with a computer by a Direct Numerical Control(DNC)interface and the functions of a DNC interface system.One architecture of hardware and software of a practi- cal single-chip computer based on DNC interface system developed by the authors is given. Without any change of the original hardware and software,this DNC interface system has been used to innovate the CNC machine's interface to implement the direct communication between a computer and a CNC machine and to achieve no tape transmission of a part program and ma- chine parameters.It has been demonstrated that this DNC interface system has certain practical values in improving the reliability,efficiency and production management of CNC/NC machine.

Studies of layout of world machine tools industry based on patent analysis

As the foundation of an industrialized country nowadays,machine tools industry is regarded as the engine of industrial development of a country.The developed countries,such as USA,Germany and Japan,have widely deployed the technology of using the patent in order to keep their strength in various fields.This research examins the CNC machine tools industry in the world by using the patent analysis method.It first gives an overview about the world patent application in CNC machine tools industry from 1963 to 2010 and divides the development of the industry into five stages.It also lists the patent application of the world top 20 countries,where the top 5 countries are compared.The patents of the world top 10 companies of machine tools manufacturers are mapped according to the international patent classification(IPC),and the future trends of world machine tools industry are discussed.Finally conclusions and suggestions are presented.

柔性模块化CNC工装在离散型制造中的应用

电力装备零件加工具有小批量、多品种、加工复杂度不高的离散型制造特性,但频繁的装夹和换型调试会严重影响设备综合效率(Overall Equipment Effectiveness,OEE),导致加工效率偏低。研究结果表明:通过柔性组合工装设计,将大部分装夹过程转移至设备外,可减少停机等待时间;通过模块化安装节点设计,快速提升工装安装速度,可缩短换型时间。通过对某数控机床(Computer Numerical Control,CNC)设备的工装进行柔性模块化改造,产品装夹时间和换型时间分别缩短了56.71%和41.18%,设备OEE水平提升了26.17%。经过3年推广应用,企业CNC设备的OEE已由45%~55%提升为70%~80%,产品交付效率显著提高,产品竞争力逐步增强。此外,该柔性模块化工装改造新模式,可为国内广大制造业厂家提供一种新的降本增效思路。

STUDY ON THE FEEDFORWARD COMPENSATION OF THE MOTIONERRORS OF NC MACHINE TOOLS

A feedforward compensation naethod of the motion errors of NC machine tools imple- mented with software is proposed , with which the motion errors can be compensated whithout changing the original computer control systems of the NC machine tools. The experimental results show that the circular interpolation profile machining errors decrease by a factor of 2/3 after com- pensated.

Reliability Analysis of Electrical System of Computer Numerical Control Machine Tool Based on Bayesian Networks

The core of computer numerical control(CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis(FTA) method is not applicable. Bayesian network(BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree(DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty;the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.

某超长条结构件柔性工装平台结构设计与实现

针对某超长条结构件加工过程中由于使用传统工装夹具造成的工艺准备时间长、工装数量多、材料浪费严重等问题,开展一种柔性工装平台的研究。该工装平台采用多个可旋转夹臂替代传统夹具进行夹持,在工件外形变化时,可通过更换夹臂长度、按压角度等保持良好夹持效果,满足柔性工装的需求。对该工装平台结构进行设计,对关键参数进行建模和校核,通过样机对工装效果进行验证。结果表明,该工装平台在加工相同工件的情况下,可节省约3%的零件材料,缩短310 min工艺准备时间,同时由于该工装平台采用了新型柔性固持方案,还提高了加工连续性,避免由于工艺变化造成大量的夹具浪费,为超长条结构件的加工提供了一种新的工装固持方案。

基于虚拟仿真技术的高精度数控机床自动控制系统

为实现高精度数控加工,设计基于虚拟仿真技术的高精度数控机床自动控制系统。该系统依托SolidWorks、Deep Exploration等软件,建立数控机床虚拟仿真三维模型,设计数控机床控制约束关系,获取数控机床运行数据,并将该数据内的跟随误差、误差积分、误差微分等作为控制输入变量,设计由神经网络和PID组成的混合控制器,利用该混合控制器输出数控机床自动控制量,实现高精度数控机床自动控制。实验表明:该系统在各种运行环境下的软件移植完整程度均超过95%,在控制数控机床运动速度时,跟随误差始终保持在-50~50 mm/min,应用效果较为显著。

数控机床电气控制部分的维护和保养研究

数控设备是一种集机械、电气、液压、气动和数控系统为一体的高科技产品。数控机床维护和保养水平的高低,直接决定了一台数控机床运行的可靠性程度和故障率。本文就数控机床电气控制部分的维护和保养进行了系统阐述,针对数控机床电气控制部分如何更高效且方便地维护及查找故障,进行了开发性的研究,提出了一种高效查找强电故障的方法;为能实现更高层次的智能诊断建立了硬件基础。

薄壁零件数控加工质量的提升策略

薄壁零件在机械制造中的应用越来越广泛,但其加工难度较大。提升薄壁零件的数控加工精度,可以改善零件质量,提高生产率,降低费用,进而推动先进设备制造业的发展。文章分析影响薄壁零件数控加工质量的因素,包括加工工艺、外部荷载、温度系数及刀具等,并提出提高加工质量的措施,如合理选用刀具、选择合理的切削用量和技术方案、保证尺寸的精度以及适当延长切削时间等。

复杂曲面零件的五轴数控加工技术研究

随着科技水平的不断提升,精密复杂曲面零件的应用越来越广泛。曲面驱动是复杂曲面零件加工的重要方法,驱动刀轨的规划直接关系到曲面物理特性的调控,应用五轴数控加工技术能够提升复杂曲面零件的加工质量。文章主要研究复杂曲面零件的五轴数控加工技术,以佛像这个复杂曲面零件为例,分析了曲面驱动刀轨规划、工装方案设计、加工策略以及试制加工过程。在实际加工过程中,技术人员应充分理解驱动刀轨规划思路与原理,在粗加工、精加工中完善刀轨设计,并进行试制加工。