Machining of parts by using dedicated production systems has been, and continues to be, a viable manufacturing method. There are situations, however, where this type of system is not feasible due to changes in product type, customer demand, work-piece material, or design specification. From a competitive manufacturing environment, production system selection is a crucial issue for all component manufacturing companies. Improper selections could negatively affect the overall performance of a manufacturing system, for instance the productivity, as well as the cost and quality of manufactured components. In this paper, the application of system dynamics modelling and simulation of a complex manufacturing process is presented as a potential tool to investigate and analyse the performance of manufacturing system in response to disturbances in the system's inputs (e.g., volume of products). In order to investigate the model soundness, a case study applied to the manufacturing of an engine block will be examined. The model presented here has been developed based on current engine block production for the vehicle manufacturing industry. Such a model can assist manufacturing system selection-centered round the capacity to control machining system parameters -as a testable way to choose a machining strategy from pre-selected performance criteria. More specifically, the benefit of this research lies in the fact that it will enable companies to implement improved potential manufacturing system optimization that responds during unexpected demand fluctuations. In addition, it will help in understanding the complex interaction between the process and operational parameters of a manufacturing system and help identify those critical parameters, ones that can lead to an optimizing strategy in the manufacturing standards of engine block production.

This paper will introduce a novel methodology for the performance evaluation of machining strategies of engine block manufacturing. The manufacturing of engine components is vital to the automotive and vehicle manufacturing industries. Machining is critical processes in the production of these parts. To survive and excel in the competitive manufacturing environment, companies need to improve as well as update their machining processes and evaluate the performance of their machining lines. Moreover, the lines and processes have to be robust in handling different sources of variation over time that include such examples as demand fluctuations, work-piece materials or even any changes in design specifications. A system dynamics modelling and simulation approach has been deployed to develop a methodology that captures how machining system parameters from the machining process are interacted with each other, how these connections drive performance and how new targets affect process and machine tool parameters through time. The developed model could provide an insight of how to select the crucial machining system parameters and to identify the effect of those parameters on the output of the system. In response to such an analysis, this paper provides (offers) a framework to examine machining strategies and has presented model that is useful as a decision support system for the evaluation and selection of machining strategies. Here a system dynamics methodology for modelling is applied to the milling operation and the model is based on an actual case study from the engine-block manufacturing industry.

Comprehensive knowledge and information about the static and dynamic behaviour of machine tools, cutting processes and their interaction is essential for machining system design, simulation, control and robust operation in safe conditions. The very complex system of a machine tool, fixture and cutting tools during the machining of a part is almost impossible to model analytically with sufficient accuracy. In combination with increasing demands for precision and efficiency in machining call for new control strategies for machining systems. These strategies need to be based on the identification of the static and dynamic stability under both the operational and off-operational conditions. To achieve this it is necessary to monitor and analyze the real system at the factory floor in full production. Design information and operational data can then be linked together to make a realistic digital model of a given machining system. Information from such a model can then be used as input in machining simulation software to find the root causes of instability.

The work presented in this thesis deals with the static and dynamic capability of machining systems. The main focus is on the operational stability of the machining system and structural behaviour of only the machine tool, as well.

When the accuracy of a machining system is measured by traditional techniques, effects from neither the static stiffness nor the cutting process are taken into account. This limits the applicability of these techniques for realistic evaluation of a machining system’s accuracy. The research presented in this thesis takes a different approach by introducing the concept of operational dynamic parameters. The concept of operational dynamic parameters entails an interaction between the structural elements of the machining systems and the process parameters. According to this concept, the absolute criterion of damping is used to evaluate the dynamic behaviour of a machining system. In contrast to the traditional theory, this methodology allows to determine the machining system's dynamic stability, in real time under operating conditions. This framework also includes an evaluation of the static deformations of a machine tool.  In this context, a novel concept of elastically linked system is introduced to account for the representation of the cutting force trough an elastic link that closes the force loop. In addition to the elastic link which behaves as a static element, a dynamic non-contact link has been introduced. The purpose is to study the non-linear effects introduced by variations of contact conditions in joints due to rotational speed.

The increasing demands for precision and efficiency in machining call for new control strategies for machining systems based on the identification of static and dynamic characteristics under operational conditions. By considering the machining system as a closed-loop system consisting of a machine tool structure and a machining process, the join system characteristics can be analyzed. The capability of a machining system is mainly determined by its static and dynamic stiffness.

The goal of this thesis is to introduce some concepts and methods regarding the identification of machining system stability. Two methods are discussed, one for the static behaviour analysis of a machine tool, and one for dynamic stability of a machining system. Preliminary results are indicating unambiguous identification of capabilities of machining systems static and dynamic characteristics.

The static behaviour of a machine tool is evaluated by use of a loaded double ball bar (LDBB) device. The device reproduces the real interaction between the join system, the machine tool elastic structure and the cutting process. This load is not equivalent to real cutting forces, but it does have a similar effect on the structure. This has been investigated both trough simulation and experimental work.

It is possible to capture the process – ­machine interaction in a machining system by use of the model-based identification approach. The identification approach takes into consideration this interaction and can therefore be used to characterize the machining system under operational conditions. The approach provides realistic prerequisites for in-process machining system testing. The model parameters can be further employed for control and optimization of the cutting process. Using different classification schemes, the model-based identification method is promising for the detection of instability.

Furthermore, it is the author’s belief that a model-based stability analysis approach is needed to exploit the full potential of a model driven parts manufacturing approach.

A novel methodology for linking machining system capability to the accuracy of a machined part is presented. Using special testing equipment, force-deviation functions in the real machine workspace are obtained. An elastically linked multi-body simulation and FE model evaluates the volumetric deviations. The deviation values are then calculated for a particular tool path. The forces and the deviations along the tool path are computed and compared with results obtained from machining experiments. This approach yields elimination of laborious machining experiments and supports an unequivocal control of machining system conditions giving the required level of part accuracy.

In today’s highly competitive environment there is a need for fast and accurate methods to assess the capability of manufacturing units. The traditional estimation of the dynamic properties of machine tools is usually time consuming and assumes time-invariant properties. This paper introduces a method for analyzing machine tool structure dynamic properties by recursive estimation of modal and operational parameters. A contact-less excitation system and a specially designed tool were employed to enable spindle speed sweep. The primary contribution of this paper lies within the formulation and implementation of recursive parametric models for tracking the time-varying dynamic properties of a machine tool structure.

The spindle system is a critical part of a machine tool structure and its dynamic properties are important for the performance of the whole machining system. Currently the only way to extract the dynamic properties of a given structure is via experimental modal analysis. This approach, however, can only be employed on idle systems and is performed with the assumption that the dynamics of a system are independent of rotational speed. The latter assumption cannot be applied to spindle systems. This paper introduces a novel testing system for analysing machine tool spindles dynamic properties, consisting of real-time recursive estimation of modal and operational dynamic parameters, employed alongside a contactless excitation and response system. The presented approach allows analysing the spindle system condition and dynamic properties not only at discrete rotational speed intervals but also during continuous sweep of rotational speed.

The transition from conventional standalone metrology to integrated metrology has been accelerating in advanced manufacturing over the past decade. This keynote paper defines the concept of integrated metrology, which extends beyond parts inspection and encompasses processes and manufacturing equipment to enhance efficiency and productivity. The paper presents the characteristics, benefits, constraints, and future possibilities of integrated metrology for parts, processes, and equipment. It also includes a classification of the physical quantities of measurands, the corresponding measuring instruments, data and communication methods, uncertainty, and traceability. The paper also discusses future challenges and emerging trends.

The key to solve manufacturing quality and productivity problems in the machining of parts is to understand the physical attributes’ geometric/kinematic, static, dynamic, and thermal behavior of machine tools. In this chapter basic definitions, error sources, and instruments and methodologies for the identification and evaluation of machine tools’ physical attributes will be outlined.

The first section presents the background and answers “why” it is important to measure and evaluate machine tools under no-load and loaded condition. Basic concepts and definitions of metrological terms will be given. In the second part, error sources in machine tools are introduced, and in the third part, instruments and methodologies for the accuracy evaluation of machine tools will be given.

The paper introduces the concept of Elastically Linked Systems (ELS) to directly relate the machine tool positional and static accuracy to the machined part’s geometric errors and form deviation. Practical implementation of the ELS concept resulted in a novel test equipment, Loaded Double Ball Bar (LDBB) which is a precision mechatronic device with variable load. The test method based on the device is able to reveal machine tool characteristics not obtainable with existing methods as for instance the variation of stiffness in the entire working space. The LDBB is used to experimentally evaluate the stiffness and the corresponding accuracy of five machine tools.

Today’s test methods are analysing machine tool specific characteristics but leaves out to a great deal the machining process. In this paper an evaluation method for determining machining system dynamic characteristics is discussed. For machine capability analysis, the overall elastic structure must be considered, i.e., machine tool – fixture – workpiece – toolholder – tool. Regarding dynamic behaviour of machining systems, the stability can only be evaluated through the interaction between the two subsystems, elastic structure and cutting process. In order to analyse the join machining system, stochastic discrete models, ARMA models are used to identify the stability of the join system, elastic structure – machining process.

The majority of test methods used for determine a machining systems status, are machine tool oriented and do not take into consideration the characteristics of the machining process. In this paper an evaluation method for determining a machining system static characteristics are discussed. The importance of joint stiffness and damping in elastic structures of machine tool is emphasized. In this context the new type of double ball bar (DBB) is described which applies a preload on the structure, thus creating more realistic conditions for accuracy measurements. Also, for machine capability analysis, the overall elastic structure must be considered, i.e., machine tool-fixture-workpiece-tool holder-tool.

The key concept of the identification procedure in this paper is to find a feature of the measured random response (sound pressure) that can be used to discriminate between stable and unstable process-machine interaction (PMI) in milling. The dynamic condition of the machining system is represented by the operational dynamic parameters (ODP), which refer to the contribution of the structural vibration modes and process vibration modes resulting during machining system operation. It is shown that the sound pressure level acquired by a microphone, located in the machine’s working area, is able to follow rapid changes in the process dynamics and therefore may be used as input in the recursive estimation scheme. The primary contribution of this paper lies within the formulation and implementation of recursive parametric models for the study of the real-time dynamics of a face milling operation PMI. A comparison between the experimental, simulated, and identified results is outlined.

This paper presents a novel test device for the evaluation of the accuracy of NC machine tools. The design concept is similar to a double ball bar (DBB) with the difference that an adjustable load generated by the device can be applied between spindle nose and machine tool table. This load eliminates the play existing in machine tool joints, thus reproducing the testing conditions that exist during machining. Collected data can be used to plot diagrams displaying important aspects of machine tool performance and a number of key figures such as static stiffness may be determined. The data can also be used for trend analysis; to predict any accuracy problems, and further to conduct preventive maintenance instead of emergency calls. The determined static behaviour could also be used to improve digital models for process simulations and compensation of errors caused by deflection.

The aim of this paper is to introduce a novel methodology, based on a finite element (FE) computation engine for validating of real-time identification schemes applied in machining. FE modelling of the milling process has the purpose of being accountable for a thorough validation of the parametric identification approach, and of providing a good physical insight into the phenomena investigated. The system considered here has a lower number of degree-of-freedoms which permits a thorough analysis. However, when taking into account the system’s nonlinear and time-varying nature, it is clear that the results are far from being trivial. Therefore, the analysis of the milling process, taking into account nonlinearities restricting the growth of response amplitudes in the case of chatter-type instability, provides some intrinsic information of the basic features on the system that might be of both fundamental interest and practical use.

The accuracy of machine tools is affected to a large extent by the behavior of the system's joints. In this paper the equivalent stiffness approach identifies and calculates the contribution of joint error sources to the total deviation measured between toolholder and workpiece under loaded conditions. The force–deviation functions are measured at different locations in the machine workspace. Joint deviations are then computed and compared with results obtained from measurements. The results show the effectiveness of the proposed method in determining joint errors in machines.

The demand for enhanced performance of production systems in terms of quality, cost and reliability is ever increasing while, at the same time, there is a demand for shorter design cycles, longer operating life, minimisation of inspection and maintenanceneeds. Experimental testing and system identification in operational conditions still represent an important technique for monitoring, control and optimization. The term identification refers in the present paper to theextraction of information from experimental data and is used to estimate operational dynamic parameters for machining system. Such approach opens up the possibility of monitoring the dynamics of machining system during operational conditions, and to be used for control and/or predictive purposes

In this chapter the subject of statistical dynamics are discussed and non-parametric and parametric models for machining system identification are derived. The common characteristic for all discussed models is that they may be used for computing the operational dynamic parameters (ODP) of the closed loop machining system. Though the input to these models originates from the machining operations, not all models can be implemented for real-time identification. Generally, non-parametric models may be used solely for off-line identification, i.e., first recording the vibration signal from machining operations and then analysing the signal and identifying the nature of the excitation. Parametric models implemented in recursive algorithms are used for real-time identification of machining systems dynamic characteristics. 

The main objectives of the chapter are: (i) the development of parametric and non-parametric models based on identification techniques with the purpose of integrating into a single step within the estimation of dynamic parameters characterising the machining system, (ii) in non-parametric identification, implementing techniques for ODPs and random excitation estimation, (iii) in parametric identification, the development of the recursive computational model of the machining system based on the data obtained during the actual operational regime. Through these contributions, a step is taken beyond the classical approach to analyse the dynamics of a machining system by separately identifying the structural and process parameters. In the proposed process, the two substructures, tool/toolholder and workpiece/fixture, are coupled, in addition to the open loop (elastic structure of the machine tool), by a feedback loop closing the energy loop, through the thermoplastic chip formation mechanism.

The machining system can only be completely analysed only in closed loop i.e. in operational conditions since specially designed off-line experiments with controlled input, such as modal testing, give the response from only the open loop.

This paper presents a novel test device for the evaluation of the accuracy of machine tools. The design concept is similar to a double ball bar (DBB) with the difference that an adjustable load generated by the device can be applied between spindle nose and machine tool table. The device, called Loaded Double Ball Bar (LDBB), can be used either as an ordinary double ball bar system with no load applied to the structure, or with a predefined load applied to the structure. The load that is generated by the LDBB is generally not equivalent to real cutting forces. However, from the static deflection point of view the effect of the load on the machine tool structure has similar impact on the static behaviour of the system. For instance, the load can in some cases eliminate existing play in ball screws, plays that under normal machining condition will be eliminated by the effect of cutting forces on the structure. With the help of this test device, not only can the identifiable errors by an ordinary DBB be evaluated but also machine tool elastic deflection in different directions. It is also possible to track different error patterns to the applied load.

The aim of this paper is to introduce a novel methodology, based on a finite element (FE) computation engine for simulation of process machine interaction occurring in machining systems. FE modelling of the milling process has the purpose of being accountable for a thorough validation of the parametric identification approach, and of providing a good physical insight into the phenomena investigated. The system considered here has a lower number of degree-of-freedoms which permits a thorough analysis. However, when taking into account the system’s nonlinear and time-varying nature, it is apparent that the results are far from being trivial. Therefore, the analysis of the milling process, taking into account nonlinearities restricting the growth of response amplitudes in the case of chatter-type instability, provides some intrinsic information of the basic features on the system that might be of both fundamental interest and practical use.

The invention pertains to a method for determining machine parameters of a mechanical device in which a first element and a second element are mutually movable in settable patterns of movement, the method comprising placing a measuring arm between the first and second elements, displacing the first and second elements mutually in a predetermined intended movement path, applying a predetermined force between the first element and the second element substantially in the longitudinal direction of the measuring arm, recording the resulting actual movement path by means of the measuring arm, thereby determining a difference between the intended movement path and the actual movement path, and deriving, based on the determined difference, machine parameters indicating a condition of the mechanical device, characterized in that the predetermined force comprises a dynamically varying portion. The invention furthermore pertains to a test assembly for performing said method.

This paper presents a novel test concept for the evaluation of the accuracy of NC machine tools. The evaluation of machine tools deformations is performed by help of a device similar to the double ball bar (DBB) with the difference that an adjustable load generated by the device can be applied between spindle nose and machine tool table. This load eliminates the play existing in machine tool joints, thus reproducing the testing conditions that exist during machining. Collected data are used to plot diagrams displaying characteristic aspects of achine tool performance and a number of key figures such as static stiffness may be etermined. The data can also be used for trend analysis; to predict any accuracy deviations, and further to conduct preventive maintenance instead of emergency calls. The determined static behaviour could also be used to improve digital models for process simulations and compensation of errors that are caused by deflection.

Machine tools require high geometric accuracy and stiffness. Both of these characteristics affect the radius of a radially loaded circular test. By using various loads, the machine's volumetric compliance can be studied as a function of position, orientation, and load. Further processing of the data using a kinematic and compliance model of the machine allows the equivalent joint compliances to be estimated. This model also allows to produce the characteristic patterns of loaded telescopic double ball bar readings associated with each compliance term. The compliance model contains numerous superfluous and confounded terms that are pruned from the model. The analytical model is then used to produce a numerical identification Jacobian that is further applied to estimate the compliances from test data gathered at various force levels. By using all force data at once global compliance values are estimated whereas using only adjacent force level data allows observing the change in compliance with force. The new nomenclature is introduced where each compliance term has three subscripts. The first subscript is the direction of the displacement, the second subscript is the applied force direction, and the third subscript is the relevant joint or axis. The dominant compliances are the X-axis on-axis compliance CXXX (confounded with the lateral compliance of the Y-axis CXXY) and CYYY (confounded with CYYX). It is observed that as the load increases from 76 to 706 N (by increments of 126 N), the dominant compliances increase by around 5%. Type A uncertainties of the calculated compliances are estimated from repeated measurements and are found to be relatively small. Some non-dominant compliances, such as the torsional compliance of the Y-axis CCCY account for deflection of less than 0.5% of that for the main compliances and has a negative value which is mechanically unexpected. It is explained in detail in the results and discussion section.

A novel elasto-geometric model is introduced that simultaneously estimates joint compliances and geometric error parameters by employing the loaded double ball bar apparatus. The model parameters are estimated from tests at different force levels by distinguishing between errors that change with the applied force (compliance effect) from those that do not (geometric effects). At lower forces, the geometric errors are dominant while at higher forces compliance errors dominate. Using all data to build a single global geometry and compliance set of parameters (global constant compliance model), the radial volumetric variations due to geometric errors and compliance are estimated at 0.019 mm and 0.046 mm, respectively, making compliance dominant by more than three times. The impact of dominant and non-dominant equivalent global compliance CXXX, CYYY, CXYX, CCXY, CCYY, and CCCY on the loaded circular test readings at the highest force level of 742 N are predicted to be around 0.045, 0.034, 0.00058, 0.0022, 0.0014, and 0.0045 mm peak-to-peak, respectively. The impact of loaded geometric parameters EXX1, EYY1, EYX2, EXY2, EC(0Y)X, EXt0, and EYt0 on the loaded circular test readings is predicted to be around 0.019, 0.014, 0.0074, 0.012, 0.00017, 0.0076, and 0.0012 mm peak-to-peak, respectively. The dominant global compliances are CXXX and CYYY at 0.0619 and 0.0461 μm / N , respectively.

Additive manufacturing (AM) has recently been accorded considerable interest by manufacturers. Many manufacturing industries, amongst others in the aerospace sector, are already using AM parts or are investing in such manufacturing methods. Important material properties, such as microstructures, residual stress, and surface topography, can be affected by AM processes. In addition, a subtractive manufacturing (SM) process, such as machining, is required for finishing certain parts when accurate tolerances are required. This finish machining will subsequently affect the surface integrity and topography of the material. In this research work, we focused on the surface integrity of Ti-6Al-4V parts manufactured using three different types of AM and finished using an SM step. The aim of this study was to gain an understanding on how each process affects the resulting surface integrity of the material. It was found that each AM process affects the materials’ properties differently and that clear differences exist compared to a reference material manufactured using conventional methods. The newly generated surface was investigated after the SM step and each combination of AM/SM resulted in differences in surface integrity. It was found that different AM processes result in different microstructures which in turn affect surface integrity after the SM process.

Machining vibrations is a critical phenomenon in the industry as they negatively affect the quality and tool-life. One common avoidance strategy for machining vibrations is the fine-tuning of process parameters, thus leading to longer production time. Our research addresses this challenge and uses different streams of data to classify problematic processes. Data streams of machining parameters, tool position, loads, vibration sensors, together with process plan data and cutting tool usage information, are visualized. Experiments are performed to derive classification criteria. These results are then used to observe vibrations in a five-axis machining center for further process adjustment.

Titanium alloys are known to produce shear-localized chips during machining, resulting in cyclic variations in cutting forces which in turn could cause severe problems with vibrations. However, at low cutting speeds and feed rates, continuous chips are formed, with an increase in both parameters favoring the transition to shear-localized chips. This transition is affected by work material microstructure, where a coarse microstructure gives anisotropic effects, e.g., when the size of alpha colonies is on the same order of magnitude as the primary cutting zone. The change in chip morphology with an increase in cutting parameters will then be dependent on the orientation of alpha colonies within the cutting zone. The microstructure of work material can show large variations depending on product form, e.g., cast, wrought, or sheet material, thus affecting whether the chip formation is isotropic or anisotropic. Other sources of variations also exist that can be found within the same component, such as segregation of alloying elements and differences in thermo-mechanical history during processing due to geometry. In this study, the interaction between work material microstructure, process parameters, and the machining system’s structural characteristics is studied. The aim is to further increase the knowledge about vibrations during machining of titanium and the role of microstructure and machining system properties. Different microstructures were produced by adding boron to cast Ti-6Al-4V material, where the resulting colony sizes gave both isotropic and anisotropic chip formation within the chosen cutting data range. The machining systems dynamic properties were varied by using different tool overhangs, thereby simulating different configurations of natural frequencies and stiffness. The results show the influence of both microstructure and machining system’s structural characteristics on the dynamic response of the system for different process parameters. This information can be used to increase robustness of machining operations taking into consideration this three-way relationship.

Hardness measurement is a vital step for quality assurance in manufacturing of a wide range of products. Today, the standard hardness measurement tests, such as Vickers, are based on microscope image-based evaluation methods. Since these methods are limited to the geometry of the indentation in 2D images, their precision are highly dependent on the samples’ surface finish. A novel method based on 3D surface topography of the indentation is introduced for more robust Vickers hardness measurement. The 3D evaluation method with information in Z direction offers a high level of precision in hardness measurement on surfaces with different surface qualities.

This paper introduces a novel design for boring bar with enhanced damping capability. The principle followed in thedesign phase was to enhance the damping capability minimizing theloss in static stiffness through implementation of composite materialinterfaces. The newly designed tool has been compared to a conventional tool. The evaluation criteria were the dynamic characteristics, frequency and damping ratio, of the machiningsystem, as well as the surface roughness of the machined workpieces.The use of composite material in the design of damped tool has been demonstrated effective. Furthermore, the autoregressive moving average (ARMA) models presented in this paper take in to consideration the interaction between the elastic structure of themachine tool and the cutting process and can therefore be used to characterize the machining system in operational conditions.

Ultraprecision (UP) components have become common in everyday life products such as mobile phones or compact high resolution digital cameras. Thus the need of producing such components with high accuracy and low production cost. UP machine tools are capable of extremely high accuracy in tool positioning but still today the workpiece is positioned by hand, hence the high production cost of UP components. A fully automated chain of production has been developed within the EU-IP project “Production 4 micro”. This paper describes the active alignment chuck for workholding in UP machining. The chuck has been provided with a high damping interface (HDI) and to evaluate its efficiency the chuck has undergone an experimental modal analysis (EMA) as well as machining tests. The chosen operation was grooving by fly cutting using a diamond tool. The EMA showed that the HDI was effective for those modes where there was relative displacement between one side and the other of the HDI. This result was confirmed by the machining tests as well. The HDI resulted being effective in damping high frequency modes (around 4 – 5 kHz), hence one expected benefit would be a longer tool life.

With advances in material technology come challenges to productivity. New materials are, in fact, more difficult to machine with regards to tool wear and especially machine tool stability. This paper proposes to extend the stability limits of the machining system by enhancing the structure’s damping capability. The aim of the research work presented here is to introduce a unified concept based on the distribution of damping within the machining system components exploiting the dynamic properties of the existing joints. To maintain a high level of static stiffness, it was chosen to adapt hydrostatic clamping systems to the tools. Damping is designed in the structure via high damping interfaces (HDI), intentionally introduced interfaces where the damping ratio is enhanced by introduction of viscoelastic polymer metal composites between the two metallic surfaces composing the interface. In this paper HDI are introduced at two joints, between tool and turret and between turret and lathe. The tests show that the designed-in damping is effective and allows extending the stability limits of the machining system. The implementation of designed-in damping allows the end user to select the most suitable parameters in terms of productivity avoiding the hassle of tuning the devices, having to acquire a deep knowledge in structural dynamics or having to use additional control systems. In addition to this, the enhanced machine tool system becomes less sensitive to stability issues provoked by difficult-to-machine materials or even fluctuations of the work material properties that might occur in everyday production processes.

The performance of a machine tool is directly influenced by the characteristics of the floor, subsoil, and their interaction with the installed machine. Installing a machine tool in its operational environment poses a distinct challenge that bridges mechanical and civil engineering disciplines. This interdisciplinary issue is often overlooked within the individual separate disciplines. However, effectively addressing this challenge requires a comprehensive understanding of mechanical and civil engineering principles. To address this problem, the present study proposes a method for improved modeling of the dynamic properties of the machine tool by considering the foundation and the subsoil on which it is installed. The method is based on finite element modeling. Linear models of the system components and the connections between them were used. These, supplemented with damping expressed by complex stiffness, made it possible to determine the natural frequencies, mode shapes, and frequency response functions (based on which the transmissibilities were obtained). Based on the experimentally verified models of vertical and horizontal lathes, the sensitivity analysis aimed at estimating the impact of changes in system parameters on vibration transmissibility for a floor-type and a block-type foundation was conducted. Thus, it was possible to identify those machine tool-support-foundation-subsoil system parameters that had the most significant impacts on the vibration's transmissibility. After analyzing the cases discussed, it became evident that the transmissibility of vibrations is primarily influenced by two key factors. First and foremost, the properties of the structural loop of the machine tool played a significant role. Additionally, the characteristics of the subsoil on which the foundation was situated emerged as a crucial determinant in the observed vibration transmissibility.

Advanced technologies for the calibration of machine tools are presented. Kinematic errors independently of their causes are classified into errors within one-axis as intra-axis errors, errors between axes as inter-axis errors, and as volumetric errors. As the major technological elements of machine tool calibration, the measurement methods, modeling theories, and compensation strategies of the machine tool errors are addressed. The criteria for selecting a combination of the technological elements for machine tool calibration from the point of view of accuracy, complexity, and cost are provided. Recent applications of artificial intelligence and machine learning in machine tool calibration are introduced. Remarks are also made on future trends in machine tool calibration.

This research outlines the methodology and application of quasi-static loaded circular testing on serial articulated industrial robots using the Loaded Double Ball Bar (LDBB). The article focuses on measuring the quasi-static path accuracy and repeatability of industrial manipulators to evaluate their performance in industrial contact applications such as trimming, grinding, or deburring. The manipulator is measured under quasi-static loads of 100, 350, 500, and 600N using circular testing following the guidelines of ISO 230-4. The data can be used to discuss core aspects of process planning with industrial manipulators such as workpiece placement, optimal robot pose selection for dexterity as well as stiffness optimization. The article contains a case study of quasi-static loaded circular testing of a mid-size articulated industrial robot from ABB using the LDBB and a Leica AT960 laser tracker for validation. At a load of 600N the path accuracy for both Clock-Wise (CW) and Counter Clock-Wise (CCW) were 2:4 mm, measured with the LDBB, compared to 2.9 mm, measured with the AT960. Finally, the paper ends with a discussion about the opportunities and challenges for the implementation of loaded circular testing for elasto-geometrical calibration of industrial manipulators. 

As a result of digitalization, data is collected at every level of production as an enhancer for decision-making. However, including more sensors to collect additional information does not directly contribute to increasing the system reliability but instead raises challenges for optimal data utilization. This work presents an evaluation approach based on FMSA (Failure mode and symptoms analysis) combined with FMECA (Failure mode, effects and criticality analysis) prioritization methods. The different methods are applied to a feed-drive system to evaluate the suitability of the currently implemented detection and monitoring techniques. The recommendations derived from the evaluation can be utilized to maximize confidence in the monitoring and to minimize the sensors utilization and data collection. Since the FMEA family of assessment tools present shortcomings such as bias and uncertainty associated with their results, this work also aims at mitigating these effects in obtaining the monitoring priority numbers and their respective categorization and prioritization.

Industrial manipulators are desired to be commonly used for material removal applications due to their high flexibility, low cost, and large working space. However, their lower stiffness (compared to a machine tool) leads to a reduction in path accuracy. This reduction directly affects the dimensional accuracy of the machined part. Additionally, the low stiffness in the presence of dynamic process forces creates vibrations influencing the surface quality, tool life, and service life of the manipulator. Static stiffness models, optimization, and compensation techniques exist to minimize force-induced deflections. Multi-body dynamics analytical models still lack the required accuracy in predicting the position-dependent dynamics of the manipulator. Dynamics data-driven models are rising to tackle the uncertainties in modeling the robot properties. This study presents the position-dependent variation of the dynamic characteristics, namely frequency and damping, of a mid-size articulated industrial manipulator, which were determined through experimental modal analysis. The position-dependent dynamics is investigated and quantified in a low-frequency range and is discretely measured and presented in two perpendicular planes (horizontal and vertical) of the robot working space. The study concludes with a discussion on the potential to apply the dynamic information obtained experimentally for the process planning and working space optimization in contact applications. 

This article presents the measurement and analysis of the influence of velocity on the quasi-static deflections of industrial manipulators of three different manufacturers. Quasi-static deflection refers to the deflection of the end effector position of articulated robots during movement at low velocity along a predefined trajectory. Based on earlier reported observations by the authors, there exists a difference in the static and quasi-static deflections considering the same points along a trajectory. This work investigates this difference to assess the applicability of robotic compliance calibration at low velocities. For this assessment, the deflections of three industrial articulated robots were measured at different speeds and loads. Considering the similarity among the robot models used in this investigation, this work also elaborates on the potential influence of the measurement procedure on the measured deflections and its implications for the compliance calibration of articulated robots. For all industrial articulated robots in this investigation, the quasi-static deflections are significantly larger than the static ones but similar in trend. Additionally, the magnitude of the quasi-static deflections presents a proportional relationship to the Cartesian velocity.

Industrial articulated robots appeal to high force processes such as material removal applications mainly due to their high flexibility and large working space. However, due to the articulated robot's lower stiffness, significant deformations arise in the presence of process forces which reduces the robot's positioning accuracy. To improve the positioning accuracy in tasks performed under load, offline or online compliance compensation methods are implemented. This study presents an experimental comparison of the implementation and performance of offline and online compliance compensation strategies in a high-force application, i.e., loaded circular trajectory, characterized by the presence of quasi-static forces. The performance of the two compensation strategies was evaluated by calculating the mean deformation (comparison between unloaded and loaded trajectories). The results indicate that the performance of the online compensation strategy exceeded the offline compensation strategy performance for the case study analyzed. The limitations and potentialities of the different compensation strategies are discussed in terms of implementation and applicability for contact applications.

Industrial manipulators are rarely used in high-force processes even though they provide flexibility, adaptability, relatively low cost, and a large workspace. This limited utilization is mainly due to their inherent low stiffness, which results in significant deformation. Hence, it is necessary to improve their accuracy in order to achieve high-precision requirements while performing tasks under load. This paper focuses on the development and implementation of an online compliance error compensation system for industrial manipulators. The proposed algorithm computes the compensation based on an elasto-geometric robot model and process forces measured with a force sensor mounted between the robot mechanical interface and the end effector. The performance of the compensation system is evaluated experimentally in two high payload robots from different manufacturers in which the compensation was carried out to reduce the mean deformation of circular trajectories under load.

Models of manufacturing resources as machine tools, fixtures and cutting tools contribute to efficient and simplified operation planning. With operation planning domain concept, defined in ontology and used during modelling of coherent ISO 10303-214 conforming data models of manufacturing resources, stable implementation solutions are ensured while capable of representing current manufacturing resources and resources developed in the future. Using similarities between different types of resources, a unified modelling approach may be applied independent of the type of object. Information classes as interfaces, kinematics, performance and behavior are identified and related to corresponding construct of the standardized product generic schema. With the common representation of shared information between applications domains as operation planning, maintenance and factory layout design, presented result contributes to set the basis for a digital factory used in virtual manufacturing to continuously improve the production system.

The accuracy of a three-dimensional (3D) positioning system can ultimately be evaluated via measurement of a 3D vector between command and actual end-effector positions at arbitrary points over the entire workspace. This is a simple, yet challenging, metrological problem. The motion accuracy of a machine tool is traditionally evaluated on an axis-to-axis basis, with every error motion of every axis being independently measured as part of a one-dimensional measurement process in a different setup. Toward the ultimate goal of 3D position measurement over the entire workspace, research efforts have offered several new, practical measurement technologies.

This special issue covers the technical and academic efforts regarding the evaluation of machine tool accuracy. The papers in this special issue clarify the latest research frontiers regarding machine tool accuracy from a metrological viewpoint. In the first paper, by Montavon et al., error calibration technologies and their management are reviewed within the Internet of production concept. Long-term accuracy monitoring and management are clearly among the most crucial technical challenges faced regarding machine tools, and the work by Xing et al. is related to them. Ibaraki et al. presented machining tests to evaluate the thermal distortion of a machine tool. Peukert et al. studied the dynamic interaction between machine tools and their foundations. Various 3D measurement schemes for determining machine error motions have been investigated by many researchers, and some have been implemented in industrial applications. Kenno et al. and Florussen et al. investigated 3D measurement using the R-test for five-axis machines. Miller et al. studied simultaneous measurement of six-degree-of-freedom error motions of a linear axis. Nagao et al. presented an error calibration method for a parallel kinematic machine tool.

The editors appreciate the contributions of all the authors, as well as the work of the reviewers. We are confident that this special issue will further encourage research and engineering work for improving the accuracy and performance of machine tools.

As long as industrial robots are programmed by teachprogramming, their positioning accuracy is unimportant.With a wider implementation of offline programmingand new applications such as machining, ensuringa higher positioning accuracy of industrial robotsover the entire working space has become very important.In this paper, we first review the measurementschemes of end effector poses. We then outline kinematicmodelsof serial articulated industrialmanipulatorsto quantify the positioning accuracy with a focuson the extension of the classical Denavit-Hartenberg(DH) models to include rotary axis error motions.Subsequently, we expand the discussion on kinematicmodels to compliant robot models. The review highlightscompliance models that are applied to calculatethe elastic deformation produced by forces, namelygravity and external loads. Model-based numericalcompensation plays an important role in machine toolcontrol. This paper aims to present state-of-the-arttechnical issues and future research directions for theimplementation of model-based numerical compensationschemes for industrial robots.

The early identification of a defect that is developing in a bearing is crucial for avoiding failures in rotating machinery. Frequency domain analysis of the vibration signals has been shown to contribute to a better understanding of the nature of a developing defect. Early signs of degradation might be more noticeable in certain frequency bands. The advantages in identifying and monitoring these bandwidths are several: prevention of serious machinery damages, reduction of the loss of investments, and improvement of the accuracy in failure predicting models. This paper presents and compares two approaches for the diagnosis of bearing faults. The first approach was knowledge-based. It relied on principles of mechanics to interpret the measured vibration signals and utilized prior knowledge of the bearing characteristics and testing parameters. The second approach was data-driven whereby data were acquired exclusively from the vibration signal. Both approaches were successfully applied for fault diagnosis by identifying the frequencies of the vibration spectra characteristic for the bearing under study. From this, bandwidths of interest for early fault detection could be determined. The diagnostic abilities of both approaches were studied to analyze and compare their individual strengths regarding the aspects of implementation time, domain knowledge, data processing associated knowledge, data requirements, diagnostic performance, and practical applicability. The advantages, apparent limitations as well as avenues for further improvement of both approaches are discussed.