In-Process Virtual Quality Monitoring

Chapter Ten - Setting up NC machine tools

In this paper are proposed two new approaches to maintenance strategies for Computer Numerical Control (CNC) machine tools. The analysis is done for different families of CNC machine tools from S.C. Elmet Bacau, a company specialized in aviation. In maintenance actions applied to CNC machine tools is very important to know the evolution of defects and critical state of electrical and mechanical components. The results of this analysis concludes that maintenance actions can be judged by the developing time period diagram, between failure appearance and interruptions in operation. It is also analyzed the financial impact, revealed from known maintenance strategies adopted on CNC machine tools, resulting in a positive approach of condition based maintenance.

In this paper, a new approach is proposed based on data fusing with vibration signals using time-frequency parameters, probabilistic principal component analysis (PPCA) and statistical inference, for improving the accuracy and visibility of damage identification for numerical control (NC) machine tools. Time-frequency feature principal components are put forward, which extracted from eight dimensionless parameters statistically in the time and frequency domains by PPCA. The Chi-2 statistic is established according to statistical inference principle, and the feature figure of principal components is built that can acquire damage distribution of tools by measured data. An empirical analysis in NC milling machine tools is developed, and the result shows high accuracy and visibility of the proposed approach.

In view of the characteristics of energy transmission in the running processes of numerical control (NC) machine tool driven by variable voltage variable frequency (VVVF), an energy flow model of main driving system is established. The power transition characteristics of main motor and mechanical transmission system and the energy loss on every section are analyzed. Finally, the dynamic power balance equation of the whole main drive system is established. Comparing with the equation of common machine tools, this equation has three characteristics. The wide application prospect of the equation is shown by the application analysis and practices.

The existing methods of determining testing period do not consider the effect of working condition covariates on reliability testing period of Numerical Control (NC) machine tools, which may lead to high-cost testing or low-precision assessment. Aiming at the problem, a new method of determining the testing period considering working condition covariates is proposed. The change rate of interval estimation of Mean Time between Failures (MTBF) is used as the criterion for determining the length of testing period. The reliability model of NC machine tools is established by the Cox proportional hazards model, and the two-step estimation method is used to estimate parameters of the baseline failure rate function and the coefficients of working condition covariates. The Bootstrap resamples are obtained by the Bootstrap resampling method. And then the parameters of the baseline failure rate function and the coefficients of working condition covariates are estimated simultaneously by maximum likelihood method, and thus interval estimations of MTBF under each covariate are obtained. The change rate models of MTBF interval estimation under each covariate level are established by Power function, and the testing periods under each covariate are obtained. Case study indicates that the testing periods under each covariate obtained by the proposed method are more accurate than those obtained by the others, when the same criterion and confidence level 1-α are set.

With the increasingly common use of industrial automation for mass production, there are many computer numerical control (CNC) machine tools that require the collection of data from intelligent sensors in order to analyze their processing quality. In general, for high speed rotating machines, an accelerometer can be attached on the spindle to collect the data from the detected vibration of the CNC. However, due to their cost, accelerometers have not been widely adopted for use with typical CNC machine tools. This study sought to develop an embedded miniature MEMS microphone array system (Radius 5.25 cm, 8 channels) to discover the vibration source of the CNC from spatial phase array processing. The proposed method utilizes voice activity detection (VAD) to distinguish between the presence and absence of abnormal noise in the pre-stage, and utilizes the traditional direction of arrival method (DOA) via multiple signal classification (MUSIC) to isolate the spatial orientation of the noise source in post-processing. In the numerical simulation, the non-interfering noise source location is calibrated in the anechoic chamber, and is tested with real milling processing in the milling machine. As this results in a high background noise level, the vibration sound source is more accurate in the presented energy gradation graphs as compared to the traditional MUSIC method.

The reliability of machine tool is getting more and more attention. Reasonable reliability allocation is beneficial to improve the inherent reliability of machine tool. However, the existing reliability allocation methods for machine tool have some limitations. For example, static part is selected as the reliability allocation object of machine tool, which cannot reflect the characteristics “function realized by motion”; factors affecting reliability allocation are not considered comprehensively, weights of experts are treated as the same, and the allocation results are not optimized or the impact of time on enterprise is neglected in the optimization. To solve these problems, a new multiobjective optimization reliability allocation method for machine tool is proposed in this paper. Firstly, the latest achievements about meta‐action are given, and meta‐action is set as the reliability allocation object. Secondly, more reasonable and comprehensive factors affecting reliability allocation are extracted. Thirdly, expert weight coefficient is brought to reduce the subjective impact of expert scoring. Fourthly, time factor is brought to make the optimized allocation results more reasonable and accurate. Finally, a numerical control (NC) machine tool made in China is taken as an example, with a comparison on the reliability allocation results of current methods and proposed method. The results verify the applicability, rationality, and accuracy of the proposed method, which lays a foundation for the subsequent study on the quality characteristics of machine tool based on meta‐action.

According to the required interval estimation precision of mean time between failures (MTBF) and reliability for numerical control (NC) machine tools, where failure processes can be described by the power law process model, the minimal testing truncated time and sample size of the reliability assessment test are given using Fisher information matrix method. The results show that there are two main factors which affect the truncated time and sample size. They are the log ratio of upper bound to lower bound and confidence of interval estimation for reliability indices, respectively. Among them, the minimal sample size increases significantly as the improvement of required precision of interval estimation for reliability indices and confidence increases, but the minimal testing truncated time is less affected by these two factors.

The paper presents a new approach to the modelling and simulation of a computer numerical control (CNC) machine tool feed drive. The hybrid model of the drive incorporates a distributed load, explicit damping factors and measured non-linear effects in order to achieve a realistic dynamic performance. In this way, the shortcomings of traditional modelling methods applied to CNC machine tool axis drives are overcome. A MATLAB/SIMULINK package was used to simulate this new model for a CNC machine tool feed drive. A novel hybrid model with a distributed load, explicit damping factors, backlash and friction was developed and shown to have a similar dynamic response to the machine tool feed drive system under the same conditions. The simulated results display resonance frequencies, while the lumped-parameter models generate only the response of a second-order element.

The point maximum likelihood and interval estimators of the parameters, as well as two reliability indices of the log-linear process model, including cumulative mean time between failures and reliability at given time are given. In tests for failure time trends, both the graphical methods include the mean cumulative function versus time plot and the total-time-on-test plot, and the analytical methods include the Laplace, the military handbook, and the Lewis-Robinson tests are used. A real case of failure dada with time truncation for multiple numerical control (NC) machine tools is given to illustrate the use of the proposed model.

Aim to adverse effects resulted from external disturbances, system internal parameters variations and unmodeled dynamics during the operation of gantry moving type numerical control (NC) machine tool, The paper presented that suspension air-gap of beam suspension system was controlled by using auto-disturbance-rejection control technology. Auto-disturbances-rejection controller can regard system model parameter variations and external disturbance effect of system as comprehensive disturbance, automatic online estimation and compensation. First the state variables were chosen based on the mathematical model of beam suspension system, nonlinear state equation of system was obtained; then coil voltages was regarded as controlled variable, double-loop (position loop and current loop) auto-disturbances-rejection controller of the suspension air-gap was designed, nonlinear control of the beam suspension system was realized. The simulation results show that the auto-disturbances-rejection controller can adapt well to the nonlinearity of suspension system and has strong robustness to system's parameter variations and the system's disturbances. The beam friction-free stable suspension can be realized.

Nowadays, computer numerical control (CNC) machine tool undertakes more processing tasks than other common machine tools because of its highly automated machining ability and high performance. However, due to the lack of intelligence in machining process planning, machining procedure of products mostly depends on process planners rather than CNC machine tools. To make product quality less dependable on process planner’s ability and improve the efficiency of process planning in order to fulfill changeable market, this paper presents an approach to design and develop CNC machining process knowledge base using cloud technology. The general standard STEP-NC is mapped to web ontology language (OWL) to describe machining process-related knowledge in a readable and comprehensible way. This mapping relation also makes knowledge suitable for storage in HBase. Through this ontology model, descriptive and logical knowledge can be collected. Hadoop platform is used in this approach to provide the NoSQL database HBase for large-scale knowledge storage and MapReduce programming model for large-scale knowledge processing. Taking advantage of MapReduce, knowledge query engine and reasoning engine can be developed. Users can submit task and resource descriptive files to the cloud through CNC controller and get machining process solutions from knowledge base. Evaluation mechanism is also adopted to filter low-quality knoweldge.

In order to guarantee the preciseness and scientific nature of Computerized Numerical Control (CNC) machine tools appearance design, appearance design evaluation has to be made on CNC machine tools so as to change the randomness and uncertainty existed in traditional appearance design, and to establish a scientific method for CNC machine tools appearance design that meets the modern aesthetic needs. The evaluation index of hierarchical structure has been set up from four aspects as stylization, form-orientation, colorization and agreeableness that may influence the appearance design, adopting both qualitative and quantitative methods; weight for each evaluation index has been determined in accordance with Analytic Hierarchy Process ; and a two-level fuzzy synthetic evaluation model for CNC machine tools appearance design evaluation has been made and a comprehensive evaluation has been conducted through fuzzy mathematical method. By analyzing the appearance design of 2MKM95 series CNC precision vertical universal machine tools determined by Tianjin No.2 Machine Tool Corporation, this paper illustrates the preciseness and scientific nature of fuzzy synthetic evaluation model.

The frequent occurrence of early failure has long been restricting the corrective of the reliability of domestic numerical control (NC) machine tools. At present, there is a lack of a systematic and effective method to eliminate the early failure of machine tools. The difficulty in eliminating the early failure of the machine tools lies in how to calculate its early failure period accurately and design the failure closed-loop elimination program properly. So, a 4-parameter non-homogeneous Poisson process (NHPP) modeling method and a closed-loop elimination system for the early failure of the machine tools were proposed to solve those problems in this paper. The method proposed in this paper is applied to the enterprise, and its feasibility is verified. The research of this paper lays a foundation for the elimination of the early failure and the improvement of the reliability level of the domestic NC machine tools.

In the manufacturing industry, computer numerical control (CNC) machine tool has been applied widely due to their high adaptability and precision in the machining of diversity shape, especially five-axis CNC machine tools. However, more error terms related to rotary axes, in which location errors are always considered as one of the most fundamental error sources, affect directly to machine tool performance. Thus, ensuring that a five-axis machine tool is machining within tolerance is a crucial demand in the market. This study investigates an efficient strategy using a specific 3D artifact to identify and characterize the location errors in rotary axes of a five-axis machine tool. The intended 3D artifact consists of a base plate, 2 standards ball with high roundness embedded on the top surface of the base. A Touch Trigger Probe will be utilized as the calibration instrument to capture the coordinate of 6 arbitrary contact points of the balls, then an optimization algorithm is applied to calculate the coordinate of the centers of the balls. By comparisons the relative position of the imaginary circles made of those centers with the ideal ones, all location errors will be measured individually.