Performance Of Machine Tool Research Articles

A Health Management Technology Based on PHM for Diagnosis, Prediction of Machine Tool Servo System Failures

The computer numerically controlled (CNC) system is the key functional component of CNC machine tool control systems, and the servo drive system is an important part of CNC systems. The complex working environment will lead to frequent failure of servo drive systems. Taking effective health management measures is the key to ensure the normal operation of CNC machine tools. In this paper, the comprehensive effect of fault prediction and fault diagnosis is considered for the first time, and a health management system for machine tool servo drive systems is proposed and applied to operation and maintenance management. According to the data collected by the system and related indicators, the technology can predict the state trend of equipment operation, identify the hidden fault characteristics in the data, and further diagnose the fault types. A health management system mainly includes fault prediction and fault diagnosis. The core of fault prediction is the gated recurrent unit (GRU). The attention mechanism is introduced into a GRU neural network, which can solve the long-term dependence problem and improve the model performance. At the same time, the Nadam optimizer is used to update the model parameters, which improves the convergence speed and generalization ability of the model and makes it suitable for solving the prediction problem of large-scale data. The core of fault diagnosis is the self-organizing mapping (SOM) neural network, which performs cluster analysis on data with different characteristics, to realize fault diagnosis. In addition, feature standardization and principal component analysis (PCA) are introduced to balance the influence of different feature scales, enhance the feature of fault data, and achieve data dimensionality reduction. Compared with the other two algorithms and their improved versions, the superiority of the health management system with high-dimensional data and the enhancement effect of fault identification are verified. The relative relationship between fault prediction and diagnosis is further revealed, and the adjustment idea of the production plan is provided for decision makers. The rationality and effectiveness of the system in practical application are verified by a series of tests of fault data sets.

Energy-saving strategy and method of spindle deceleration during no-load operation of machine tools for energy lean management

Computer Numerical Control (CNC) machine tools undergo periods of no-load motion, such as tool feeding, tool withdrawing, and tool changing, during workpiece processing. These intervals result in energy wastage as the machine tools remain idle without performing cutting operations. To address this issue, we propose a novel energy-saving strategy and method involving spindle deceleration during the no-load operation of machine tools for energy lean management. Specifically, we conducted three tasks: (1) analyzed the energy consumption characteristics of the CNC machine tool during no-load operation; (2) established a theoretical decision-making model for the energy-saving method of spindle deceleration; (3) discussed the energy-saving critical time for energy savings and the energy-saving effect of the deceleration strategy for the machine tool spindle through three machining cases. Furthermore, we conducted a case study using the CK6153i lathe to verify the effectiveness and feasibility of the proposed method. The results demonstrated significant energy savings of 1826.65 J, 2948.85 J, and 7650.05 J, along with reductions in energy waste of 14.99 %, 20.43 %, and 53.01 %, respectively, in the three machining cases through the implementation of the spindle deceleration strategy. We believe that the outcomes of this research can better assist engineers in the energy lean management of machine tools.

Thermal Characteristics of Spindle System Based on the Comprehensive Effect of Multiple Nonlinear Time-Varying Factors

The thermal characteristics of the spindle system for CNC machine tools are influenced by multiple factors which are nonlinear and time-varying. In this paper, a nonlinear time-varying thermal characteristics solving model for the spindle system was established based on the numerical solution method. Through theoretical deduction and data fitting, mathematical models of nonlinear time-varying factors including the friction torque generated by lubricants, convective heat transfer coefficient, and coolant and ambient temperature are constructed. The temperature and displacement of the spindle system at each time step are solved by considering the comprehensive effect of multiple nonlinear time-varying factors. And the actual temperature and axial deformation data of the spindle system are obtained through thermal characteristics detection experiments. By comparing solution results affected by multiple nonlinear time-varying factors and by non time-varying factors with experimental data, it can be concluded that the nonlinear time-varying thermal characteristics model has advantages in reflecting the trend of numerical changes and the accuracy of result solving over a method considering non time-varying factors and the solution values of temperature affected by multiple nonlinear time-varying factors are almost consistent with detection values and the relative errors are all within ±3%. The relative error of axial deformation between the value solved by the model and the detection value is close to −1%. This conclusion demonstrates the rationality and accuracy of the thermal characteristics solving model and the construction of nonlinear time-varying factors. This study is of great significance for exploring the thermal characteristics of the spindle system and improving CNC machine tool performance in depth.

TRANSHUMANISM AS A TECHNOLOGY TO IMMORTALITY: HISTORICAL AND PHILOSOPHICAL RAMIFICATIONS

In the article analytical-systemic, anthropological, conceptual, comparative-empathic, historical-chronological, historical-comparative and other approaches are used that allow us to rely on the terms: theohumanism, classical humanism, mechanistic-functional humanism, posthumanism, neohumanism. During the ancient period, different sources and approaches to understanding man as a natural being began to appear. There are a variety of origins and currents of understanding humanism. At that time, there was a slave system in which slaves were viewed as tools of labor with the ability to speak, in contrast to oxen, carts, spades and plows. Such relationships cannot be called empathic relationships, but at the same time, slave owners showed empathy for equals in their social class. In the Middle Ages, humanism emerged as based on the essence of some kind of deification a person as a god, his relationships with his own kind and the world through the prism of theocentrism. This approach formed the theory of theohumanism, on the basis of which theotranshumanism was formed, which used religious and spiritual technologies to improve the soul. At this evolutionary stage of humanism, the body is seen as a source of brute egoistic desires and sins. Theotranshumanism opens the way to immortality through deliverance from sinful thoughts and actions, and relationships between people are based on love through the divine spark in each individual. During the Renaissance, there was a return to human naturalness, but on a biological basis. This humanism is based on anthropoempathy and uses body-oriented technologies to improve the individual. Anthropohumanism, in contrast to theohumanism, considers human bodily needs not as a sinful nature, but as a source that allows one to conquer animals and the nature of one’s will. This evolutionary stage of humanism is based on anthropocentrism and anthropoempathy and sees human improvement through body-oriented technologies. Thanks to the active development of a variety of technologies plants and factories appear, emphasis is placed on the need to meet the ever-growing needs of society, and man begins to be viewed as a naturally functioning phenomenon. Mechanistic humanism emerges, within which the individual is identified with a mechanism, a clock and a perpetual motion machine, and uses the features of the operation of machine tools, machines and other mechanisms to improve his physicality. The use of mechanistic technologies makes it possible to increase the functional capabilities of a person, and physicality acts as a spatio-temporal limitation. At this stage, posthumanistic tendencies emerge. While mechanistic humanism considers technologies to improve functioning processes, posthumanism applies them in the aspect of improving the quality of the bodily container, which is the limit of human existence. There is a deeper understanding of the possibilities of human functioning and the prospect of realizing humanity's ancient dream of achieving immortality. Within the framework of posthumanism, the problem of establishing the boundaries of human existence arises. After all, their techno-transhumanistic violation leads to deformation of anthropocentrism and leads to the leading positions of technology and egoism. Within the framework of posthumanism, a new attitude to understanding man as a biologically artificial phenomenon is being formed. When using bioethics, the limit of human understanding is constantly changing and depends on the progress of science and technology. All this leads to the formation of a new evolutionary stage of humanism – neohumanism, based on anthropobiocentrism and bioanthropoempathy, and influences the formation of the modern planetary worldview.

A method to manufacture spiral bevel gears by equivalent completing

As a transmission part for industrial application the manufacture of spiral bevel gear is particularly important. The present machining methods for manufacturing spiral bevel gears, including the so called five-cut method and completing method, have drawbacks such as low processing efficiency, requiring complex calculations and high requirements on the machine-tool performance, respectively. To solve the above problems, an equivalent completing method is proposed to process spiral bevel gear in this paper. Firstly the machine setting parameters by completing were translated from the Cradle-type hypoid generator to Cartesian-type hypoid generator and the workpiece is swing during process. CNC motion axes expression of Cartesian-type hypoid generator were expressed as sixth-order polynomial, the influences of coefficient on the tooth surface topology were researched. Then the method to machine spiral bevel gear was put forward by reducing the swing axis of workpiece, obviously a deviation of tooth surface was caused between theoretical and axis-reduced. As a response, a flank correction model was established and the other polynomial coefficients were adjusted to eliminate the deviation. Finally simulation and cutting experiment were carried out by a numerical example. The experimental results show that the proposed method is effective and feasible. The method proposed in this paper overcome and enrich the disadvantages of existing manufacture methods of spiral bevel gear.

Influence of cut parameters on mesh performance of spiral bevel gear by duplex spread blade method

Spiral bevel gears are key components in many mechanical transmission systems, and their production is always of great interest to industry, and hence, subjected to intensive research widely. The present machining methods for manufacturing spiral bevel gears, including the so called five-cut method and completing method, have drawbacks such as low processing efficiency, requiring complex calculations and high requirements on the machine-tool performance, respectively. To solve the above problems, the duplex spread blade method is proposed. Firstly, geometric parameters and machine setting parameters were comprehensively considered, and then a modified reference point was selected to deduce the machine setting parameters. Tooth contact analysis (TCA) model considering misalignment was established to check meshing performance, the influence of cutter parameters and misalignment on meshing performance was studied. As the research reveals that the cutter radius has an effect on the bias of contact trace, cutter number has an impact on the position of contact pattern. The experimental results are consistent with the theoretical which verified the effectiveness and feasibility of the proposed method. The results of this paper have a guiding significance and enrich the machining method for spiral bevel gear.

Application and evaluation of classic and demand oriented cooling strategies in context of machine tools

AbstractEnergy consumption is an important factor in the operation of machine tools. Recent studies showed that in average, $${1}/{5}$$ 1 / 5 of the machine tools total energy demand is caused by internal cooling systems. The continually rising performance of machine tools, together with the importance of thermal stability, reasons the requirement for demand oriented cooling approaches, which could significantly reduce the energy consumption for internal machine cooling. This study applied classic and demand oriented cooling strategies on a machine tool frame, which is one of the most complex machine tool components from a thermal point of view. The demand oriented cooling is based on volume flow control and can either be configured close to the environmental temperature or close to the thermal steady state, which can be obtained by loss forecast in combination with an FE model or measurement. The impact of the strategies on the thermal reaction as well as the energy consumption is compared, showing a significant reduction of energy demand without significant impairment of the thermal stability.

Modification of CNC Machine Tool Operations and Structures Using Finite Element Methods: A Review

Modification of CNC Machine Tool Operations and Structures Using Finite Element Methods: A Review

Finite element analysis and structure optimization of a gantry-type high-precision machine tool

The high-precision machine tool’s dynamic, static, and rigid nature directly affects the machining efficiency and surface quality. Static and dynamic analyses are essential for the design and improvement of precision machine to ensure good tool performance under difficult and demanding machining conditions. In this study, the performance of a high-precision machine tool was analyzed using its virtual model created using CAD. Static and model analysis using ANSYS Workbench software was conducted to establish the tool's static deformation and static stiffness. Furthermore, the static and dynamic characteristics of the tool were explored using a finite element modeling approach to study their performance. In particular, the structure, static force, modal, frequency spectrum, and topology optimization of machine tools were primarily analyzed. Using model analysis, we found the first four different frequencies (22.5, 28.9, 40.6, and 47.4 Hz) and vibration type, which suggested of a weak link. Further static structural analysis revealed that the deformation of the spindle was 67.26 μm. An experimental static rigidity analysis was performed, and the experimental deformation values of the tool and spindle were obtained. The static and dynamic characteristics, as well as the accuracy and efficiency of the finite element model, were verified by comparing the data with the finite element analysis (FEA) results. Subsequently, we modified the settings and analysis model to ensure that the analysis results were consistent with the experimental findings. The error between the two results was within 1.56%. For an applied load of 5000 N on the spindle nose, the tool nose transient response was 0.5 s based on transient analysis. Under the condition that the structural deformation is as constant as possible, the lightweight structure may achieve the minimum weight and enhance the natural frequency; thus, the ideal structure will be obtained, and finite element analysis will then be performed. The optimal conditions for topology optimization include a lightweight structure, reduced structural deformation, and increased natural frequency of the structure. The developed method improves structural optimization, increases the ability of the product to be manufactured, and offers designers a variety of price-effective options.

Topology Optimization and Analysis of the Compound Boring and Milling Machining Center TX1600g Bed Structure

The overall performance of the machine tool bed of the boring and milling center has an important impact on the accuracy of the overall machining, in order to improve the machining accuracy and structural performance of the overall machine tool, the structure optimization design of the machine bed is carried out for the TX1600g composite boring and milling center. The maximum static displacement and mass of the bed were used as the evaluation index to optimize the topology and structure of the bed. An orthogonal test of 5 factors and 5 levels was designed, the maximum displacement generated by different positions in work was analyzed, the frequency under this working condition was explored, and modal analysis was conducted. The Hyperwork selective variable density method is used to optimize the beam structure with multiple objective topologies. By comparing and optimizing the performance parameters of the front and rear beams, the total static displacement is reduced by 9%, which proves the effectiveness of this method to solve the multi-objective optimization problem.

Investigation of the effects of MQL and material hardness on energy consumption, vibration, and surface roughness in hard turning of AISI 52100 steel for a sustainable manufacturing

Turning hardened steels is more advantageous than cylindrical grinding. However, the machinability of hardened steel is difficult. Therefore, in this experimental study, two different AISI52100 steels with 45 and 50 HRC were machined with varying cutting parameters (feed rate: 0.15, 0.25, 0.35 mm/rev; cutting speed: 140, 155, 170 m/minute; depth of cut: 0.08, 0.12, 0.16 mm) under three different cooling conditions (dry, coolant, and MQL). According to the experimental result the lowest surface roughness, vibration, and energy consumption were obtained in cutting with MQL. With increasing feed rate and depth of cut, vibration, power consumption, and surface roughness increased, while energy consumption decreased because the machining time was shortened. With increasing cutting speed, surface roughness, tool vibration, and energy consumption decreased, while instantaneous power consumption and chuck vibration increased. For the lowest energy consumption, surface roughness, vibration, and highest machine tool performance for the ideal cutting condition, high hardness (50 HRC) using MQL, high cutting speed (145 m/minute), low feed rate (0.1 mm/rev), and high depth of cut (0.3 mm) should be preferred. Thus, 3.88% energy consumption, 58.25% surface roughness value, 10.06% chuck vibration value, and 28.80% tool vibration have decreased according to the average cutting conditions.

Countenance Evaluation of Virtual Reality (VR) Implementation in Machining Technology Courses

This study aims to evaluate whether virtual reality (VR) learning media can be used in Machining Technology courses which are practical learning but implemented virtually. The research using the Stake Countenance evaluation method was carried out at the Department of Mechanical Engineering FT-UNP in the July-December 2021 semester with 60 students as research subjects. This study was mix method by using sequential explanatory design. which is the collection of quantitative and qualitative data that is carried out sequentially. Data related to the antecedents, transaction, and outcomes phases were collected using questionnaires, interviews, and observations. The research begins with developing VR media that is implemented to learning materials in the field of Machining Technology and then applied to learning. Then first stage is carried out using quantitative then the next stage or the second stage is carried out using qualitative. The result of research showed that this VR application can help students understand the theory of introducing machine tool operations but have not been able to run machine. This study imply that students’ learning process should be enjoyable and also influence existing practices of Student-Centered Learning. The novelty of this study showed the evaluation result of technology, especially virtual reality can be implemented in the practice learning course, it can be reference for educator to consider implementing technology in practice learning. This study will contribute to existing knowledge and various instructional method that can be implemented by educator

Dynamic Evaluation of the Degradation Process of Vibration Performance for Machine Tool Spindle Bearings.

Real-time condition monitoring and fault diagnosis of spindle bearings are critical to the normal operation of the matching machine tool. In this work, considering the interference of random factors, the uncertainty of the vibration performance maintaining reliability (VPMR) is introduced for machine tool spindle bearings (MTSB). The maximum entropy method and Poisson counting principle are combined to solve the variation probability, so as to accurately characterize the degradation process of the optimal vibration performance state (OVPS) for MTSB. The dynamic mean uncertainty calculated using the least-squares method by polynomial fitting, fused into the grey bootstrap maximum entropy method, is utilized to evaluate the random fluctuation state of OVPS. Then, the VPMR is calculated, which is used to dynamically evaluate the failure degree of accuracy for MTSB. The results show that the maximum relative errors between the estimated true value and the actual value of the VPMR are 6.55% and 9.91%, and appropriate remedial measures should be taken before 6773 min and 5134 min for the MTSB in Case 1 and Case 2, respectively, so as to avoid serious safety accidents that are caused by the failure of OVPS.

Modeling and static modal analysis of lathe bed using conventional and composite materials using FEM

The bed has a significant impact on a machine tool's performance. The Bed of the Machine Tool has to be appropriately robust to absorb all vibrations and rigid enough to avoid deflections under different cutting forces transferred over the tool-post and carriage to the Lathe Bed. In general, the various permanent and moveable Lathe parts are supported by the Lathe bed. Typically, cast iron or mild steel are used to make lathe beds. When dealing with really large machinery, the bed may be constructed from two or more segments that are connected together to achieve the appropriate length. Large and robust, the lathe bed has a large ability to absorb machine vibrations during machining.This paper summaries, static structural and mode forms analysis are done on the lathe bed under maximum load circumstances. By incorporating ribs and reducing volume where loads and deflection are less caused, these simulated outcomes are utilized to lighten the lathe bed without sacrificing its structural integrity and dampening ability. As an alternative material, FEA analysis of a modified lathe bed is conducted using CAST IRON, MILD STEEL, and CFRP, this is a blend of epoxy resin hardener and granite. The efficiency of both materials is compared with regard to generated stresses, deformation, and weight reduction. CATIAV5 Modeling software was used to create lathe bed CAD Models. ANSYS 16.2 was used to generate the FE Model. ANSYS is used to perform the analysis. The observations are calculated and presented as contour plots to analyse the impact of reduced weight on the machine bed's structural strength prior to and after weight reduction, and decisions on the ideal design are made.

Application of fuzzy control based feed rate strategy design in NC machining error automatic compensation

With the continuous development of manufacturing industry, the application range of NC machining technology has been further expanded. The contour accuracy is strongly related to the NC machining quality as a key machine tool performance indicator. Its application efficiency is plainly low as the majority of offline compensation-based contour accuracy adjustments rely heavily on manual experience. Moreover, the isolated research on automatic error compensation and its combination with algorithms does not start with the characteristics of contour accuracy in data processing. Therefore, based on the advantages of strong the robustness of the fuzzy algorithm and the high effectiveness of parameter adjustment, an automatic compensation method for NC machining contour error based on fuzzy control is proposed. The contour error prediction model is designed according to the machining path, and then the automatic compensation strategy for contour error under fuzzy control is designed based on the feed speed. The results showed that under this method, the contour error can reach a maximum of 0.06 and a minimum of 0.025, which was 0.015 lower than the minimum contour error of genetic algorithm. This indicated that the method greatly reduced the CNC machining contour error and improved the contour accuracy, as well as reducing the time cost of contour error compensation, improving the efficiency of contour error compensation, and realizing the automation of error compensation control capability. This is helpful for advancing CNC machining automation technology and supporting the intelligent development of machinery manufacturing.

Modification of CNC Machine Tool Operations and Structures Using Finite Element Methods, A Review

Modification of CNC Machine Tool Operations and Structures Using Finite Element Methods, A Review

A dynamic failure mode and effect analysis (FMEA) method for CNC machine tool in service

To solve the problems such as uncertain evaluation information, high dependence on experts, and no consideration of the degradation of machine operating performance to failure risk in the practical application of FMEA in CNC machine tool operation and maintenance, a dynamic failure mode and effect analysis (FMEA) method for CNC machine tool in service is proposed, operation and maintenance data is introduced to the traditional failure risk analysis, which makes semantics criteria and data-driven method are systematically integrated, resulting in better performance of quantitative assessment and risk ranking of dynamic fault risk. Afterward, the fault classification and maintenance strategy of the CNC machine tool based on risk priority number (RPN) is proposed, which provides decision support for efficient operation and maintenance of the CNC machine tool. Finally, a machining center is taken as an example to verify the feasibility and effectiveness of the method.

Kinematics and geometric features of the s-cone test piece: identifying the performance of five-axis machine tools using a new test piece.

The design of machine parts of different sizes and shapes has become relevant in the manufacturing industry which requires five-axis machine tools of high dynamic performance; different machining test pieces have been used to test and reflect the machine tool's performance. The S-shaped is still under development and consideration of which a new test piece better than the S-shaped part has been recommended to be put forward making the NAS979 the only standardized test piece; however, it has some limitations. Hence, this study proposes a new test piece to objectively satisfy the demand for machine tools with higher dynamic performance, which shows much improvement over the standard NAS979 and is the best alternative to the S-shaped test piece, and it combines the geometric and kinematic features of both test pieces. Geometrically, it has non-uniform surface continuity, variable twist angle, and variable curvature; and the cutting tool moves in close and opened angles along the tool path; there is sudden rise and fall of axes' velocity, acceleration, and jerk with much impact during machining which makes the S-cone test piece be machined by only five-axis machine tools with high dynamic performance, and has a better dynamic performance identification effect than the S-shaped test piece based on the trajectory test. Detailed work on the validation of the machine tool's dynamic performance using the S-cone part will be captured next part of this study.

Intelligent prediction of machine tool performance in micro turning using textured inserts

Intelligent prediction of machine tool performance in micro turning using textured inserts

Roughness prediction of end milling surface for behavior mapping of digital twined machine tools

Background: The quality of machined parts is considered as a relevant factor to evaluate the production performance of machine tools. For mapping the production performance into a digital twin machine tool, a virtual metrology model for surface roughness prediction, which affects products' mechanical capacity and aesthetic performance, is proposed in this paper. Methods: The proposed model applies a three-layer backpropagation neural network by using real-time vibration, force, and current sensor data collected during the end milling machining process. A grid search plan is used to settle down the number of neurons in the middle layer of the backpropagation neural network. Results: The experimental results indicate that the model with multiple signals as input performs better than it with a single signal. In detail, when the model input is the combination of force, vibration, and current sensor data, the prediction accuracy reaches the optimum with the mean absolute percentage error of 1.01%. Conclusions: Compared with the state-of-the-art convolutional neural network method with automatic feature extraction ability and other commonly used traditional machine learning methods, the proposed data preprocessing procedure integrated with a three-layer backpropagation neural network has a minimum prediction error.