Influence of feed drives on the structural dynamics of large-scale machine tools

Milling is one of the most widely used processes in the manufacturing industry and demands machines with high productivity rates. In large machine tool applications, the cutting capability is mainly limited by the appearance of structural chatter vibrations. Chatter arises from the dynamic interaction of the machining system compliance with the cutting process. For the specific case of large-scale machine tools, the low frequency resonances have modal shapes that generate relative displacements in the machine joints. This thesis presents new approaches to minimize the appearance of chatter vibrations by targeting and understanding the machine tool compliance, in particular, from the feed drive of the machine tool. A detailed model of the double pinion and rack feed drive system and the master-slave coupling improves the large machine tools modeling. As the vibrations are measured by the axes feedback sensors, a new strategy for feed drive controller tuning allows increasing the chatter stability using a judicious selection of the servo parameters. Then, in-motion dynamic characterizations demonstrate the important influence of the nonlinear friction on the machine compliance and improve the chatter stability predictions. Finally, an operational method for characterizing both tool and workpiece side dynamics while performing a cutting operation is developed. All the contributions of the thesis have been validated experimentally and tend to consider the influence of the feed drives on the structural dynamics of large-scale machine tools

Instationary modal Analysis for Impulse-type stimulated structures

In order to determine modal parameters, classical experimental modal analysis can be used in engineering application. This method finds a system frequency response function using fast Fourier Transform (FFT). The Fourier Transform is one type of global data analysis method. The frequency resolution is equal to the reciprocal of the total sample time. So applying the FFT is not suitable for any transient signal to reveal local characteristics. However, in modern manufacturing industries, processing forces are rapidly changing. The dynamic behavior may vary rapidly in a short time due to variations in the machining parameters and changes in boundary conditions. These nonlinear and non-stationary dynamic parameters are not constant during machining operations identification using FFT. In this research, an innovative transient signal analysis approach has been developed, which is based on an application of the least squares estimation. The proposed method provides transient information with high resolution and to identify the time-varying modal parameters during machining. Least squares estimation can be augmented with a sliding-window operation (SWLSE) to reveal the actual system dynamic behavior at any moment. The accuracy of this method depends on the window size, the noise ratio and the sampling rate etc. The estimation accuracy of modal parameters is discussed in this work. To examine the efficiency of the SWLSE method experimental tests are performed on a laboratory beam system and the results are compared with the classical experimental modal analysis (CEMA) method. The laboratory beam system is designed and assembled that the stiffness and damping ratio of the structure can be adjusted. Additionally, the proposed method is applied to the identification of the actual modal parameters of machine tools during machining operations. In another application, the proposed method provides also the process varied damping information in a process monitoring

A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone

Virtual Model Building for Multi-Axis Machine Tools Using Field Data

Accurate machine dynamic models are the foundation of many advanced machining technologies such as virtual process planning and machine condition monitoring. Viewing recent designs of modern high-performance machine tools, to enhance the machine versatility and productivity, the machine axis configuration is becoming more complex and diversified, and direct drive motors are more commonly used. Due to the above trends, coupled and nonlinear multibody dynamics in machine tools are gaining more attention. Also, vibration due to limited structural rigidity is an important issue that must be considered simultaneously. Hence, this research aims at building high-fidelity machine dynamic models that are capable of predicting the dynamic responses, such as the tracking error and motor current signals, considering a wide range of dynamic effects such as structural flexibility, inter-axis coupling, and posture-dependency. Building machine dynamic models via conventional bottom-up approaches may require extensive investigation on every single component. Such approaches are time-consuming or sometimes infeasible for the machine end-users. Alternatively, as the recent trend of Industry 4.0, utilizing data via Computer Numerical Controls (CNCs) and/or non-intrusive sensors to build the machine model is rather favorable for industrial implementation. Thus, the methods proposed in this thesis are top-down model building approaches, utilizing available data from CNCs and/or other auxiliary sensors. The achieved contributions and results of this thesis are summarized below. As the first contribution, a new modeling and identification technique targeting a closed-loop control system of coupled rigid multi-axis feed drives has been developed. A multi-axis closed-loop control system, including the controller and the electromechanical plant, is described by a multiple-input multiple-output (MIMO) linear time-invariant (LTI) system, coupled with a generalized disturbance input that represents all the nonlinear dynamics. Then, the parameters of the open-loop and closed-loop dynamic models are respectively identified by a strategy that combines linear Least Squares (LS) and constrained global optimization. This strategy strikes a balance between model accuracy and computational efficiency. This proposed method was validated using an industrial 5-axis laser drilling machine and an experimental feed drive, achieving 2.38% and 5.26% root mean square (RMS) prediction error, respectively. Inter-axis coupling effects, i.e., the motion of one axis causing the dynamic responses of another axis, are correctly predicted. Also, the tracking error induced by motor ripple and nonlinear friction is correctly predicted as well. As the second contribution, the above proposed methodology is extended to also consider structural flexibility, which is a crucial behavior of large-sized industrial 5-axis machine tools. More importantly, structural vibration is nonlinear and posture-dependent due to the nature of a multibody system. In this thesis, prominent cases of flexibility-induced vibrations in a linear feed drive are studied and modeled by lumped mass-spring-damper system. Then, a flexible linear drive coupled with a rotary drive is systematically analyzed. It is found that the case with internal structural vibration between the linear and rotary drives requires an additional motion sensor for the proposed model identification method. This particular case is studied with an experimental setup. The thesis presents a method to reconstruct such missing internal structural vibration using the data from the embedded encoders as well as a low-cost micro-electromechanical system (MEMS) inertial measurement unit (IMU) mounted on the machine table. It is achieved by first synchronizing the data, aligning inertial frames, and calibrating mounting misalignments. Finally, the unknown internal vibration is reconstructed by comparing the rigid and flexible machine kinematic models. Due to the measurement limitation of MEMS IMUs and geometric assembly error, the reconstructed angle is unfortunately inaccurate. Nevertheless, the vibratory angular velocity and acceleration are consistently reconstructed, which is sufficient for the identification with reasonable model simplification. Finally, the reconstructed internal vibration along with the gathered servo data are used to identify the proposed machine dynamic model. Due to the separation of linear and nonlinear dynamics, the vibratory dynamics can be simply considered by adding complex pole pairs into the MIMO LTI system. Experimental validation shows that the identified model is able to predict the dynamic responses of the tracking error and motor force/torque to the input command trajectory and external disturbances, with 2% ~ 6% RMS error. Especially, the vibratory inter-axis coupling effect and posture-dependent effect are accurately depicted. Overall, this thesis presents a dynamic model-building approach for multi-axis feed drive assemblies. The proposed model is general and can be configured according to the kinematic configuration. The model-building approach only requires the data from the servo system or auxiliary motion sensors, e.g., an IMU, which is non-intrusive and in favor of industrial implementation. Future research includes further investigation of the IMU measurement, geometric error identification, validation using more complicated feed drive system, and applications to the planning and monitoring of 5-axis machining process

Conference on Thermal Issues in Machine Tools: Proceedings

Inhomogeneous and changing temperature distributions in machine tools lead to sometimes considerable quality problems in the manufacturing process. In addition, the switching on and off of aggregates, for example, leads to further fluctuations in the temperature field of machine tools. More than 100 specialists discussed these and other topics from the field of thermal research at the 1st Conference on Termal Issues in Machine Tools in Dresden from 22 to 23 March.:Efficient modelling and computation of structure-variable thermal behavior of machine tools S. Schroeder, A. Galant, B. Kauschinger, M. Beitelschmidt Parameter identification software for various thermal model types B. Hensel, S. Schroeder, K. Kabitzsch Minimising thermal error issues on turning centre M. Mareš, O. Horejš, J. Hornych The methods for controlled thermal deformations in machine tools A. P. Kuznetsov, H.-J. Koriath, A.O. Dorozhko Efficient FE-modelling of the thermo-elastic behaviour of a machine tool slide in lightweight design C. Peukert, J. Müller, M. Merx, A. Galant, A. Fickert, B. Zhou, S. Städtler, S. Ihlenfeldt, M. Beitelschmidt Development of a dynamic model for simulation of a thermoelectric self-cooling system for linear direct drives in machine tools E. Uhlmann, L. Prasol, S.Thom, S. Salein, R. Wiese System modelling and control concepts of different cooling system structures for machine tools J. Popken, L. Shabi, J. Weber, J. Weber The electric drive as a thermo-energetic black box S. Winkler, R. Werner Thermal error compensation on linear direct drive based on latent heat storage I. Voigt, S. Winkler, R. Werner, A. Bucht, W.-G. Drossel Industrial relevance and causes of thermal issues in machine tools M. Putz, C. Richter, J. Regel, M. Bräunig Clustering by optimal subsets to describe environment interdependencies J. Glänzel, R. Unger, S. Ihlenfeldt Using meta models for enclosures in machine tools F. Pavliček, D. P. Pamies, J. Mayr, S. Züst, P. Blaser, P. Hernández-Becerro, K. Wegener Model order reduction of thermal models of machine tools with varying boundary conditions P. Hernández-Becerro, J. Mayr, P. Blaser, F. Pavliček, K. Wegener Effectiveness of modelling the thermal behaviour of the ball screw unit with moving heat sources taken into account J. Jedrzejewski, Z. Kowal, W. Kwasny, Z. Winiarski Analyzing and optimizing the fluidic tempering of machine tool frames A. Hellmich, J. Glänzel, A. Pierer Thermo-mechanical interactions in hot stamping L. Penter, N. Pierschel Experimental analysis of the heat flux into the grinding tool in creep feed grinding with CBN abrasives C. Wrobel, D. Trauth, P. Mattfeld, F. Klocke Development of multidimensional characteristic diagrams for the real-time correction of thermally caused TCP-displacements in precise machining M. Putz, C. Oppermann, M. Bräunig Measurement of near cutting edge temperatures in the single point diamond turning process E. Uhlmann, D. Oberschmidt, S. Frenzel, J. Polte Investigation of heat flows during the milling processes through infrared thermography and inverse modelling T. Helmig, T. Augspurger, Y. Frekers, B. Döbbeler, F. Klocke, R. Kneer Thermally induced displacements of machine tool structure, tool and workpiece due to cutting processes O. Horejš, M. Mareš, J. Hornych A new calibration approach for a grey-box model for thermal error compensation of a C-Axis C. Brecher, R. Spierling, M. Fey Investigation of passive torque of oil-air lubricated angular contact ball bearing and its modelling J. Kekula, M. Sulitka, P. Kolář, P. Kohút, J. Shim, C. H. Park, J. Hwang Cooling strategy for motorized spindle based on energy and power criterion to reduce thermal errors S. Grama, A. N. Badhe, A. Mathur Cooling potential of heat pipes and heat exchangers within a machine tool spindleo B. Denkena, B. Bergman, H. Klemme, D. Dahlmann Structure model based correction of machine tools X. Thiem, B. Kauschinger, S. Ihlenfeldt Optimal temperature probe location for the compensation of transient thermal errors G. Aguirre, J. Cilla, J. Otaegi, H. Urreta Adaptive learning control for thermal error compensation on 5-axis machine tools with sudden boundary condition changes P. Blaser, J. Mayr, F. Pavliček, P. Hernández-Becerro, K. Wegener Hybrid correction of thermal errors using temperature and deformation sensors C. Naumann, C. Brecher, C. Baum, F. Tzanetos, S. Ihlenfeldt, M. Putz Optimal sensor placement based on model order reduction P. Benner, R. Herzog, N. Lang, I. Riedel, J. Saak Workpiece temperature measurement and stabilization prior to dimensional measurement N. S. Mian, S. Fletcher, A. P. Longstaff Measurement of test pieces for thermal induced displacements on milling machines H. Höfer, H. Wiemer Model reduction for thermally induced deformation compensation of metrology frames J. v. d. Boom Local heat transfer measurement A. Kuntze, S. Odenbach, W. Uffrecht Thermal error compensation of 5-axis machine tools using a staggered modelling approach J. Mayr, T. Tiberini. P. Blaser, K. Wegener Design of a Photogrammetric Measurement System for Displacement and Deformation on Machine Tools M. Riedel, J. Deutsch, J. Müller. S. Ihlenfeldt Thermography on Machine Tools M. Riedel, J. Deutsch, J. Müller, S. Ihlenfeldt Test piece for thermal investigations of 5-axis machine tolls by on-machine measurement M. Wiesener. P. Blaser, S. Böhl, J. Mayr, K. Wegene

Research and development of a reconfigurable robotic end-effector for machining and part handling.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF

Friction, Vibration and Dynamic Properties of Transmission System under Wear Progression

This reprint focuses on wear and fatigue analysis, the dynamic properties of coating surfaces in transmission systems, and non-destructive condition monitoring for the health management of transmission systems. Transmission systems play a vital role in various types of industrial structure, including wind turbines, vehicles, mining and material-handling equipment, offshore vessels, and aircrafts. Surface wear is an inevitable phenomenon during the service life of transmission systems (such as on gearboxes, bearings, and shafts), and wear propagation can reduce the durability of the contact coating surface. As a result, the performance of the transmission system can degrade significantly, which can cause sudden shutdown of the whole system and lead to unexpected economic loss and accidents. Therefore, to ensure adequate health management of the transmission system, it is necessary to investigate the friction, vibration, and dynamic properties of its contact coating surface and monitor its operating conditions

Model Referenced Condition Monitoring of High Performance CNC Machine Tools

Generally, machine tool monitoring is the prediction of the system’s health based on signal acquisition and processing and classification in order to identify the causes of the problem. The producers of machine tools need to pay more attention to their products life cycle because their customers increasingly focus on machine tool reliability and costs. The present study is concerned with the development of a condition monitoring system for high speed Computer Numerical Control (CNC) milling machine tools. A model is a simplification of a real machine to visualize the dynamics of a mechatronic system. This thesis applies recent modelling techniques to represent all parameters which affect the accuracy of a component produced automatically. The control can achieve an accuracy approaching the tolerance restrictions imposed by the machine tool axis repeatability and its operating environment. The motion control system of the CNC machine tool is described and the elements, which compose the axis drives including both the electrical components and the mechanical ones, are analysed and modelled. SIMULINK models have been developed to represent the majority of the dynamic behaviour of the feed drives from the actual CNC machine tool. Various values for the position controller and the load torque have been applied to the motor to show their behaviour. Development of a mechatronic hybrid model for five-axis CNC machine tool using Multi-Body-System (MBS) simulation approach is described. Analysis of CNC machine tool performance under non-cutting conditions is developed. ServoTrace data have been used to validate the Multi-body simulation of tool-to-workpiece position. This thesis aspects the application of state of art sensing methods in the field of condition monitoring of electromechanical systems. The ballscrew-with-nut is perhaps the most prevalent CNC machine subsystem and the condition of each element is crucial to the success of a machining operation. It’s essential to know of the health status of ballscrew, bearings and nut. Acoustic emission analysis of machines has been carried out to determine the deterioration of the ballscrew. Standard practices such as use of a Laser Interferometer have been used to determine the position of the machine tool. A novel machine feed drive condition monitoring system using acoustic emission (AE) signals has been proposed. The AE monitoring techniques investigated can be categorised into traditional AE parameters of energy, event duration and peak amplitude. These events are selected and normalised to estimate remaining life of the machine. This method is shown to be successfully applied for the ballscrew subsystem of an industrial high-speed milling machine. Finally, the successful outcome of the project will contribute to machine tool industry making possible manufacturing of more accurate products with lower costs in shorter time