Special Issue "Machine Tool Dynamics"

A special issue of Journal of Manufacturing and Materials Processing (ISSN 2504-4494).

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Prof. Dr. Erhan Budak
Website
Guest Editor
Manufacturing Engineering, Sabanci University, Orhanli, Tuzla, Istanbul 34956, Turkey
Interests: machining processes and machine tools; machine dynamics; cutting tools; precision manufacturing; process monitoring
Dr. Jokin Munoa
Website
Guest Editor
Dynamics &Control, IK4-Ideko, 20870 Elgoibar, Basque Country, Spain
Interests: machine tool dynamics; chatter; modelling

Special Issue Information

Dear Colleagues,

The dynamics of machine tools play an important role in productivity in machining processes, and the resulting part quality. The stability of the process against chatter strongly depends on the dynamic characteristics of the machine including the peripherals such as the tooling assembly. Various methods are used to measure, model and simulate the dynamics of machine tools. The results of these are essential in evaluating dynamic rigidity and machining process stability as well as weak parts and components of a machine tool. The research related to the theoretical, numerical and experimental modelling of machine tool dynamic properties will be covered in this Special Issue.
Some authors state that machine dynamics are the main source of errors in predicting stability. The variations of the dynamic parameters in high speed spindles due to thermomechanical effects have attracted strong attention in this field. For this reason, current dynamic characterization procedures have been questioned, and new experimental procedures have been proposed. Nowadays, impact hammer testing is the most common method for dynamic parameter identification. Different authors have proposed the use of alternative excitation methods closer to operational conditions by means of special devices. Some authors have also tried to identify the dynamic parameters under cutting conditions using inverse methods, OMA or controlled cutting force variations. They identified deviations compared to traditionally obtained FRFs.
The analysis of damping is especially interesting. The main source of damping is at the interfaces and joints of the system. Several attempts to increase damping have been reported including passive dampers, the creation of highly damped interfaces, and the introduction of special materials, coatings and foams has been proposed. This Special Issue will cover different attempts to increase the damping of machine tools.

  • Modelling of machine tool dynamics.
  • FEA of machine tools
  • Experimental identification of machine tool structural dynamics
  • Modal analysis of manufacturing systems
  • Operational modal analysis for machining
  • Application of receptance coupling in machine tools
  • Inverse methods based on cutting or chatter tests
  • Spindle dynamics
  • Non-conventional methods to measure dynamic parameters.
  • New concepts of vibration absorbers and dampers
  • Dynamic characterization of machine tool joints
  • Active damping and dampers
  • Dynamic validation of machine tools
  • Theoretical/experimental correlation and model updating of machine tools

Prof. Dr. Erhan Budak
Dr. Jokin Munoa
Guest Editors

Manuscript Submission Information

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Published Papers (6 papers)

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Research

Open AccessArticle
Learning-Based Prediction of Pose-Dependent Dynamics
J. Manuf. Mater. Process. 2020, 4(3), 85; https://doi.org/10.3390/jmmp4030085 - 31 Aug 2020
Abstract
The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to [...] Read more.
The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to vibrations, which can deteriorate the quality of the machined workpiece surface. The prediction of tool vibrations based on the used NC path and process configuration can be achieved by, e.g., applying geometric physically-based process simulation systems prior to the machining process. However, recent research showed that the dynamic behavior of the system, consisting of the machine tool, the spindle, and the milling tool, can change significantly when using different inclination angles to realize certain machined workpiece shapes. Intermediate dynamic properties have to be interpolated based on measurements due to the impracticality of measuring the frequency response functions for each position and inclination angle that are used along the NC path. This paper presents a learning-based approach to predict the frequency response function for a given pose of the tool center point. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessArticle
In-Process Monitoring of Changing Dynamics of a Thin-Walled Component During Milling Operation by Ball Shooter Excitation
J. Manuf. Mater. Process. 2020, 4(3), 78; https://doi.org/10.3390/jmmp4030078 - 03 Aug 2020
Abstract
During the milling of thin-walled workpieces, the natural frequencies might change radically due to the material removal. To avoid resonant spindle speeds and chatter vibration, a precise knowledge of the instantaneous modal parameters is necessary. Many different numerical methods exist to predict the [...] Read more.
During the milling of thin-walled workpieces, the natural frequencies might change radically due to the material removal. To avoid resonant spindle speeds and chatter vibration, a precise knowledge of the instantaneous modal parameters is necessary. Many different numerical methods exist to predict the changes; however, small unmodelled effects can lead to unreliable results. The natural frequencies could be measured by human experts based on modal analysis for an often interrupted process; however, this method is not acceptable during production. We propose an online measurement method with an automatic ball shooter device which can excite a wide frequency range of the flexible workpiece. The method is presented for the case of blade profile machining. The change of the natural frequencies is predicted based on analytical models and finite element simulations. The measurement response for the impulse excitation of the ball shooter device is compared to the results of impulse modal tests performed with a micro hammer. It is shown that the ball shooter is capable of determining even the slight variation of the natural frequencies during the machining process and of distinguishing the slight change caused by different clamping methods. An improved FE model is proposed to include the contact stiffness of the fixture. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessArticle
The Basics of Time-Domain-Based Milling Stability Prediction Using Frequency Response Function
J. Manuf. Mater. Process. 2020, 4(3), 72; https://doi.org/10.3390/jmmp4030072 - 16 Jul 2020
Cited by 1
Abstract
This study presents the fundamentals of the usage of frequency response functions (FRF) directly in time-domain-based methods. The methodology intends to combine the advantages of frequency- and time-domain-based techniques to determine the stability of stationary solutions of a given milling process. This is [...] Read more.
This study presents the fundamentals of the usage of frequency response functions (FRF) directly in time-domain-based methods. The methodology intends to combine the advantages of frequency- and time-domain-based techniques to determine the stability of stationary solutions of a given milling process. This is achieved by applying the so-called impulse dynamic subspace (IDS) method, with which the impulse response function (IRF) can be disassembled to separated singular IRFs that form the basis of the used transformation. Knowing the IDS state, the linear stability boundaries can be constructed and a measure of stability can be determined using the Floquet multipliers via the semidiscretization method (SDM). This step has a huge importance in parameter optimization where the multipliers can be used as objective functions, which is hardly achievable using frequency-domain-based methods. Here we present the basic idea of utilizing the IDS method and analyze its convergence properties. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessArticle
Design of Chatter-Resistant Damped Boring Bars Using a Receptance Coupling Approach
J. Manuf. Mater. Process. 2020, 4(2), 53; https://doi.org/10.3390/jmmp4020053 - 03 Jun 2020
Cited by 1
Abstract
Deep hole boring using slender bars that have tuned mass dampers integrated within them make the boring process chatter vibration resistant. Dampers are usually designed using classical analytical solutions that presume the (un)damped boring bar which can be approximated by a single degree [...] Read more.
Deep hole boring using slender bars that have tuned mass dampers integrated within them make the boring process chatter vibration resistant. Dampers are usually designed using classical analytical solutions that presume the (un)damped boring bar which can be approximated by a single degree of freedom system, and the damper is placed at the free end. Since the free end is also the cutting end, analytical models may result in infeasible design solutions. To place optimally tuned dampers within boring bars, but away from the free end, this paper presents a receptance coupling approach in which the substructural receptances of the boring bar modelled as a cantilevered Euler–Bernoulli beam are combined with the substructural receptances of a damper modelled as a rigid mass integrated anywhere within the bar. The assembled and damped system response thus obtained is used to predict the chatter-free machining stability limit. Maximization of this limit is treated as the objective function to find the optimal mass, stiffness and damping of the absorber. Proposed solutions are first verified against other classical solutions for assumed placement of the absorber at the free end. Verified models then guide prototyping of a boring bar integrated with a damper placed away from its free end. Experiments demonstrate a ~100-fold improvement in chatter vibration free machining capability. The generalized methods presented herein can be easily extended to design and develop other damped and chatter-resistant tooling systems. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessArticle
Effect of Rack and Pinion Feed Drive Control Parameters on Machine Tool Dynamics
J. Manuf. Mater. Process. 2020, 4(2), 33; https://doi.org/10.3390/jmmp4020033 - 21 Apr 2020
Abstract
In large heavy-duty machine tool applications, the parametrization of the controller that is used for the positioning of the machine can affect the machine tool dynamics. The aim of this paper is to build a Multiple-Input and Multiple-Output model that couples the servo [...] Read more.
In large heavy-duty machine tool applications, the parametrization of the controller that is used for the positioning of the machine can affect the machine tool dynamics. The aim of this paper is to build a Multiple-Input and Multiple-Output model that couples the servo controller and machine tool dynamics to predict the frequency response function (FRF) at the cutting point. The model is experimentally implemented and validated in an electronically preloaded rack and pinion machine tool. In addition, the influence of each control parameter on the machine tool’s compliance is analysed. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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Open AccessArticle
Machining Chatter Prediction Using a Data Learning Model
J. Manuf. Mater. Process. 2019, 3(2), 45; https://doi.org/10.3390/jmmp3020045 - 08 Jun 2019
Cited by 6
Abstract
Machining processes, including turning, are a critical capability for discrete part production. One limitation to high material removal rates and reduced cost in these processes is chatter, or unstable spindle speed-chip width combinations that exhibit a self-excited vibration. In this paper, an artificial [...] Read more.
Machining processes, including turning, are a critical capability for discrete part production. One limitation to high material removal rates and reduced cost in these processes is chatter, or unstable spindle speed-chip width combinations that exhibit a self-excited vibration. In this paper, an artificial neural network (ANN)—a data learning model—is applied to model turning stability. The novel approach is to use a physics-based process model—the analytical stability limit—to generate a (synthetic) data set that trains the ANN. This enables the process physics to be combined with data learning in a hybrid approach. As anticipated, it is observed that the number and distribution of training points influences the ability of the ANN model to capture the smaller, more closely spaced lobes that occur at lower spindle speeds. Overall, the ANN is successful (>90% accuracy) at predicting the stability behavior after appropriate training. Full article
(This article belongs to the Special Issue Machine Tool Dynamics)
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