Performance Of Machine Tool Research Articles

The Analysis of Key Technologies for Sustainable Machine Tools Design

Machine tools as indispensable tools for manufacturing products are typical high-energy, high-carbon manufacturing systems due to their larger mass, longer life cycles and huge resources and energy consumption. The current research trend of sustainable machine tools aims to reduce cost, energy consumption and increase sustainability without compromising their functionality, usability, productivity, accuracy, etc. However, there is a lack of systematic reviews about what are the key technologies for sustainable machine tools design. Thus, a comprehensive literature review of machine tool design for sustainability is needed in order to make clear how to design and evaluate sustainable machine tools from the viewpoint of life cycle sustainability analysis. The aim of this paper is to review the sustainable design and assessment aspects of machine tool design from partial goals to integrated aims according to whole sustainability dimensions such as the environment, economy and society, as well as involving key techniques in different life cycle stages. Recent research and study on improving directly or indirectly sustainability performance of machine tools according to focus points could be summarized as: design optimization of components such as lightweight using topology and bionic methods; structure design with modular design and layout; reducing cutting fluids and lubricant oil by employing minimum quantity lubrication, dry and cryogenic machining; reducing energy consumption; waste reduction by reusing, remanufacturing and recycling; sustainability assessment i.e., energy model, life cycle cost and life cycle social benefit. This paper assists designers and manufacturers to improve sustainability of machine tools by specific optimization measures in their activities.

In-process digital twin estimation for high-performance machine tools with coupled multibody dynamics

Direct drive rotary and linear actuators significantly enhance the performance of multi-axis machine tools. The absence of mechanical gearing, however, increases the nonlinear dynamic coupling between the axes, making it challenging to identify accurate virtual models or so-called ‘digital twins’. This article presents a new approach to estimate nonlinear multivariable dynamic models non-intrusively, using in-process CNC data. Major influences, such as multi-rigid body motion, actuator force/torque ripples, nonlinear friction, feedforward/feedback control, and vibration modes, are systematically detected and identified. The new method is demonstrated in digital twin estimation for a 5-axis laser drilling machine.

Energy efficient machine tools

The growing global energy demand from industry results in significant ecological and economical costs. Aiming to decrease the impact of machining operations, an increasing number of research activities and publications regarding energy efficient machine tools and machining processes can be found in the literature. This keynote paper provides an overview of current machine- and process-related measures to improve the energy efficiency of metal cutting machine tools. Based on an analysis of the energy requirements of machine tool components, design measures to reduce the energy demand of main and support units are introduced. Next, methods for an energy efficient operation of machine tools are reviewed. Furthermore, latest developments and already available energy efficiency options in the machine tool industry are discussed. The paper concludes with recommendations and future research questions for more energy efficient machine tools.

Dynamic Performance Analysis of the micro-hole EDM Machine Tool

The EDM machine is special processing machine using the principle of EDM process of conductive materials. By means of modal analysis, ODS (Operational, Deflection, Shapes) analysis and order analysis, the static and dynamic performance parameters of the EDM machine tool are studied. According to the processing requirements, the structure of the machine tool is optimized, and the weak links are strengthened so as to reduce the aperture dispersion of the machined holes. Through the modal test this experiment firstly analyzes the natural frequency, damping ratio and modal shape in each mode of machine tool structure to understanding the characteristics of each order machine main mode. Then, through ODS (Operational Deflection Shapes) test, it analyzes the vibration characteristics of machine tool structure in operation condition. And it also analyzes the relation-shape between the vibration of rotating machinery and the speed of the machine through the order analysis to predict the vibration of actual machine tool structure in a certain band external or internal variety of vibration response. Finally, it makes a comprehensive study on the static and dynamic performance of machine tools, and provides a reference for the design and optimization of structure dynamic strength.

Extraction of modal parameters of CNC lathe bed using finite element and experimental method

Key performance parameters of the CNC machine tool are limited by its dynamic behavior. To improve the performance of machine tools, we need to understand their dynamic behavior in the design stage itself. Modal analysis serves as an important tool to determine inherent modal properties of the structure. The present work is aimed at determining modal parameters of the CNC lathe bed, as a step towards predicting the dynamics of machine tools. Modal analysis has been performed by both finite element simulation and experimental method. The experimental modal analysis is carried out by exciting the bed using an impact hammer and measuring its response to obtain its modal parameters. The correlation shows good agreement between two results.

Precision of prestressed ball screw thermal behaviour in machine tool operating conditions

Precision of prestressed ball screw thermal behaviour in machine tool operating conditions

A new solution of measurement using 3D artefact to identify all location errors related to rotary axis of five-axis machine tool

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.

The Errors Recognition and Compensation for the Numerical Control Machine Tools Based on Laser Testing Technology

Abstract To improve the accuracy of numerical control machine tools error, this paper studies the application of laser testing technology in numerical control machine tool, and put forward a laser interferometer automatic aiming system which can conduct space error measurement. The system, in the process of the NC machine tool operating, can measure the machine tool space curve through changing the direction of the laser. The principle of laser interferometer and matlab analysis are adopted, through the experiment of laser interference technology in the numerical control machine tool, the law curve of error in NC machine tools is obtained, getting the method of error of NC machine tools. When conducting laser testing error experiment in NC machine tool, the results show that the laser testing can measure aggregated error and thermal error of NC machine tool better, with small control of environment and high accuracy of measurement.

Dynamic Characteristics Analysis and Finite Element Simulation of Steel–BFPC Machine Tool Joint Surface

Abstract The dynamic performance of the steel–Basalt fiber polymer concrete (BFPC) machine tool joint surface (referred to as the joint surface) has a significant impact on the overall BFPC machine tool performance; however, its dynamic characteristics remain unclear. In order to solve this problem, the influence of roughness and surface pressure on the dynamic performance of joint surface was studied experimentally, and a neural network prediction model for the dynamic performance of the joint surface was established. A BFPC bed was designed and manufactured, and BFPC bed’s dynamic performance was tested experimentally. The finite element simulation model of BFPC bed was established with equivalent spring-damper element. The BFPC bed’s dynamic performance without considering the influence of the joint surface and considering the influence of the joint surface was studied separately. The results show that the maximum error of the natural frequency of the BFPC bed was 6.937% considering the influence of the joint surface, which was much lower than the error without considering the influence of the joint surface. The maximum amplitude error of the X-axis and Z-axis acceleration of the BFPC bed was 6.917% and 5.15%, which were much smaller than the error without considering the influence of the joint surface. It proves the accuracy of the neural network prediction model for dynamic performance of the joint surface and the validity of the finite element simulation method for the joint surface. It provides theoretical support for the design analysis of BFPC machine tool.

A general framework of workpiece setup optimization for the five-axis machining

In five-axis machining, the setup of workpiece on the machine's table is an essential element of the kinematic chain that affects the performance of machine tools, such as the kinematic behavior and machining accessibility. In this paper, a mathematical model between singularity, a special kinematic behavior of five-axis machine tool, and the workpiece setup is built, and another model between accessibility of machine tool and the workpiece setup is presented. Regarding the above two models, a geometry-based approach is presented to unify and simplify them. By considering the two constraints of singularity-free and full accessibility, a general framework for the workpiece setup optimization of five-axis machining is established, from which the orientation and position of the workpiece on the table is optimized. To validate the advantage of the proposed framework, some physical cutting experiments and simulation are implemented toward a typical five-axis machine tool, testifying that the optimal setup can be achieved efficiently with the kinematic performance, surface machining quality as well as the machining efficiency significantly improved compared with the benchmark.

Machine tool reliability: an operational perspective

Machine tools, like any other system, are designed with the best possible reliability under given budget, time, and technology constraints. Appropriate maintenance policies are deployed to sustain reliability performance over the life of the system. From the operational perspective, the reliability performance of machine tools is not only dependent on inherent reliability and maintenance, but also significantly influenced by peripheral functions such as production planning and material supply decisions, etc. Moreover, the interaction effect of these functions with inherent reliability and maintenance policy makes the machine tools reliability modeling a complex problem. A holistic (considering various aspects together) and integrated (parametric-level consideration) approach is thus needed to optimize the performance of machine tools. The present paper aims to holistically consider machine tool reliability, maintenance, production, and material supply aspects to simultaneously optimize various decisions related to these functions. For pragmatic manifestation, a real manufacturing environment is considered, which is characterized by the stochastic nature of various functions and associated uncertainties. Furthermore, an exhaustive evaluation is performed over a broad range of manufacturing environment to demonstrate the superiority of the proposed approach.

Precision testing method of five‐axis NC machine tool based on ‘S’ specimen cutting

‘S’ specimen through its unique profile features makes it possible to fully mobilise the five-axis linkage function in the five-axis finishing stage. The continuous rotation direction of the rotating axis not only reflects the static error of the machine tool but also the servo system follow error, tool positioning error, profile error etc. The authors studied its influence on the accuracy of each axis of five-axis CNC machine tool by analysing the geometrical characteristics of a S specimen and using UG's CAM environment to process ‘S’ specimen. Finally, the corresponding program forming system for S specimen machining experiments is designed by LabVIEW, and the authors used macro instruction to do NC program trigger system to collect vibration signals segmentally, so that the processing and acquisition system can be synchronised. This provides a more complete basis for the test piece cutting method to evaluate performance of machine tools.

Structural design optimization of moving component in CNC machine tool for energy saving

Abstract With the increase of energy price and environment problem, the energy consumption of machine tool is attracting more attention. The moving components of machine tools consume a large amount of energy in the operating stage. Structure optimization of moving components is a key strategy for energy saving in machine tools design. Traditionally, structural optimization of machine tools is carried out for reducing energy consumption or improving static and dynamic performance. Given that these factors are important to the structure optimization in machine tools design, this paper presents a structural design optimization method for comprehensively considering energy consumption, static and dynamic performance of machine tool. Firstly, the energy consumption model of the moving components is proposed, and the structural performance indicators of the moving components are analyzed. Then, based on the experiment data obtained by uniform design method, five structure parameters that have great influence on performance indicators are selected as decision variables through sensitivity analysis. To improve the computation efficiency, approximation functional relationship between the five decision variables and the four performance indicators are built through response surface method (RSM). After that, an optimization objective is formulated by combining the four performance indicators through principal component analysis (PCA). Finally, a new hybrid algorithm which integrates Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithm is developed to solve the structure optimization problem. Through calculation and analysis, it is found that there is a linear relationship between the moving part mass and energy consumption. The results show that the energy consumption of optimized structure is reduced while ensuring the static and dynamic performance.

Research on green design framework and support system of metal cutting machine

In order to improve the green design level of metal cutting machine tools, the framework and implementation methods for enhancing the green performance of machine tool’s design process were studied. Analysing the environmental impact of design process, studying the green key points in the design process of materials, structures, hydraulics, lubrication and cooling, a green design framework for the metal cutting machine was established. Centering on the machine tool design process; Researching on the machine tool design support technology and implementation tools, a basic support system for green design of metal cutting machine that integrates technical support layer, interaction layer, tool support layer, technical support layer and user service layer was established. The green design support system for gear making machine was developed and applied to verify the guiding role of green framework and support system in the green design process of metal cutting machine tool.

Analytical and graphical modelling of the cutting scheme when generating with a pinion cutter

The teeth generation in the case of the cylindrical gears with involute profile is frequently realized with tools of pinion cutter type, on specialized slotting machine tools. In general, during gear teeth machining, several teeth of the tool are concomitantly in contact with the worked part, each one detaching a separate chip. The process is characterized by important unevenness of these chips cumulated area, depending on the relative position between the pinion cutter and the worked part. This transforms into cutting force and cutting torque unevenness and negatively influences both machine tool operating and tool life. The paper addresses the problem of smoothing the detached chips cumulated area at the consecutive strokes of the tool, along the rolling motion between it and the worked part, in order to obtain a main cutting torque as uniform as possible. In this purpose, the analytical modelling of the tool/worked part contact is realized at first, in the cases of generating both exterior and interior gears with involute straight teeth. Then, because the analytical solution is very laborious, a modelling algorithm is developed in one of the most performant graphical environments, which is CATIA. By implementing the graphical solution, the variation of detached chips cumulated area can be determined and the required variation law of the rolling feed, leading to process smoothing, can also be found. A numerical approached case study, concerning the teeth machining for an exterior gear is also presented.

Actively lubricated hybrid journal bearings based on magnetic fluids for high-precision spindles of machine tools

The research work reported in this article is focused on the use of magnetic fluids as active lubricant for improving the performance of hybrid journal bearings, with application to high-precision machine tools. Prototype design was optimized following numerical computation of Reynolds equation and computational fluid dynamics calculations, in both cases with Herschel–Bulkley model for the magnetorheological fluid. This fluid (LORD Corp. MRF 122-2ED) was experimentally characterized in detail. The improvement of the hydrodynamic effect in journal bearings was demonstrated with 50% higher load capacity and stiffness, mainly at half of shaft eccentricity 0.4 < ε < 0.7. Active hydrostatic lubrication achieved quasi-infinite stiffness within working limits (load and speed), at low frequencies. For high dynamic response, the active lubrication based on magnetorheological valves did not show good response. The feasibility of using magnetic fluids for developing high performance machine tool spindles and the validity of the simulation models was demonstrated experimentally.

Investigating the learning performances between sequence‐ and context‐based teaching designs for virtual reality (VR)‐based machine tool operation training

AbstractBackgroundTraining workers in machine tool operations is indispensable. Because training course at school with real machine tools is costly and dangerous, most researchers have concentrated on developing and adopting virtual reality (VR)‐based applications. However, to improve students’ learning performance levels, teaching design is imperative.PurposeThis study hopes to investigate the performance differences between sequence‐ (traditional) and context‐based teaching designs along with a self‐developed VR computer numerical control (VRCNC) training environment.MethodExperimental design, sequence‐ and context‐based teaching designs were developed for this study. Forty male senior students were recruited from the department of mechanical engineering at an industrial high school. Then, corresponding pretests, teaching activities and posttests were implemented based on the proposed teaching and experimental designs. Finally, experiment‐, questionnaire‐, and interview‐based performance evaluations were utilized to conduct the final comparison and conclusion.ResultsAveragely, the context‐based teaching design exhibited superior results for mostly the learning performances. The survey results also revealed that the students obtain more satisfaction and self‐confidence after the context‐based teaching.ConclusionsAccording to the results, the context‐based teaching design has obvious improvement on the performance of machine tool operation training. Three types of evaluation results provides a comprehensive support for the proposed context‐based teaching design along with the VRCNC in machine tool education.

A modal parameter identification method of machine tools based on particle swarm optimization

The dynamic characteristics of the computerized numerical control (CNC) machine tool directly affect its machining quality, and it is necessary to carry out the working mode analysis of the CNC machine tool. The traditional manual analysis and identification process is complicated and inefficient. In the industrial environment of big data, how to use the working modal analysis method to quickly and accurately obtain the dynamic characteristic parameters of the machine tool processing from these data has become the research difficulty at the current stage. This paper proposes an optimized particle swarm optimization algorithm to solve this problem. Based on the working modal analysis theory, the semi-self-power spectrum of the output signal can replace the frequency response function for modal parameter identification. The optimized semi-self-power spectrum signal is used as the objective function of the algorithm, and the ability of the algorithm to preprocess the data is optimized, so that the improved algorithm can automatically analyze the structural mode of the machine tool during processing. Comparing the experimental results, it is found that the natural frequency identification error of the cantilever beam is less than 1%, and the natural frequency identification error of the CNC milling machine is not more than 7%. The results show that the particle swarm optimization algorithm based on modal analysis theory can be applied to the automatic analysis of modal parameters under machine tool operating conditions, and it is efficient and accurate.

Simulation thermal model of CNC machine tool operating with variable modes

The article presents the approach and the thermal modeling technique of CNC machine tools, implemented at the stage of operation. In the work, as a practical implementation of the fast modeling technology, a simulation method based on the Matlab Simulink application was used. In the work to build a thermal model of the machine tool, we used analytical solutions of the heat conduction equation. This method is applied to the machine tool operating in conditions of variable thermal processes due to varying cutting speeds. The conditions for the coordination of the thermal characteristics of the machine tool at their boundaries, corresponding to the changing spindle rotation speeds, determine the peculiarity of their construction. A feature of the implementation of the mathematical model is the use of experimental modal analysis. In this case, the modal parameters of the approximating functions are determined by solving the optimization problem. To coordinate the adjacent thermal characteristics at their borders, a special condition was adopted. Regardless of the number of temperature modes used in the model, the initial level of the first temperature mode for the next mode of operation of the machine tool was taken to be equal to the achieved level of the thermal characteristic of the machine tool at the last time interval of the current mode of operation.

Investigation of rotary axes geometric performance of a five-axis machine tool using a double ball bar through dual axes coordinated motion

The accuracy of coordinated motion involving multiple axes of five-axis machining is critical to surface finish quality and geometric tolerances. However, the lack of existing criteria to benchmark such accuracy causes severe problems in maintaining machining accuracy. Therefore, this paper proposes a novel method to identify the geometric performance of rotary axes of a five-axis machine tool with a tilting head and a rotary table using a double ball bar (DBB). A new measuring trajectory only involving two rotary axes simultaneous movement is presented. A DBB was employed to sample the complex motion, causing a semi-conical surface in a 3D space formed by the DBB poses. The asynchronisation between the resultant speed of the spindle tool cup during the B- and C-axes coordinated motion and the DBB sampling rate has been resolved, enabling the true reflection of machine tool error conditions. Simulation models were built to compare with the testing results, suggesting the estimation of PIGEs of both rotary axes. Disagreements in the simulation and experimental results were analysed and possible reasons causing such disagreements were given. The results show that the compensation of the PIGEs diagnosed with the proposed method will significantly enhance the coordinated motion of the B- and C-axes and result in geometric accuracy improvement due to the promotion of the geometric and kinematic behaviour of the target five-axis machine tool.