Showing papers by "Konrad Wegener published in 2022"

Improving stability predictions in milling by incorporation of toolholder sound emissions

Abstract: In this paper, a new approach for the identification of tool-holder contact parameters is proposed. The identification strategy is based on the sound emitted from the tool-holder combination when impacted in free-free conditions. Additionally, a new contact model, which takes the non-uniform pressure distribution between tool and holder along the tool axes into account, is introduced. Contrary to previous approaches, the proposed method does not require any expensive measurement equipment but only a microphone and a hard object for the impact. The sound spectrum is recorded and model parameters are tuned in a nonlinear optimization until an agreement between the measured sound spectrum and the modeled receptance is observed. The proposed approach is validated in several application cases. Significant improvements in the predicted tooltip dynamics as well as in predicted stability charts are achieved when comparing the results obtained with the new approach against results obtained with a contact model and contact values proposed in literature.

Crack-reduced alumina/aluminum titanate composites additive manufactured by laser powder bed fusion of black TiO2-x doped alumina granules

Abstract: Laser powder bed fusion is an emerging industrial technology, especially for metal and polymer applications. However, its implementation for oxide ceramics remains challenging due to low thermal shock resistance, weak densification and low light absorptance in the visible or near-infrared range. In this work, a solution to increase the powder absorptance and to reduce cracking during laser processing of alumina parts is given. This is achieved by the use of a homogeneously dispersed and reduced titanium oxide additive (TiO 2−x ) within spray-dried alumina granules leading to formation of aluminum titanate with improved thermal shock behavior during powder bed fusion. The impact of different reduction temperatures on powder bed density, flowability, light absorption and grain growth of these granules is evaluated. Crack-reduced parts with a density of 96.5%, a compressive strength of 346.6 MPa and a Young's modulus of 90.2 GPa could be manufactured using powders containing 50 mol% (43.4 vol%) TiO 2−x . • Laser processing of black titanium oxide (TiO 2−x ) doped alumina granules. • Improved powder absorptance by color change upon reduction under Ar/H 2 atmosphere. • Crack-reduced parts by the formation of aluminum titanate from Al 2 O 3 and TiO 2−x . • Crack reduction successful starting from a TiO 2−x amount of 50 mol%. • Highest achieved part density and compressive strength of 96.5% and 347 MPa.

Analytical model for predicting tool wear in orthogonal machining of unidirectional carbon fibre reinforced polymer (CFRP)

Abstract: Abstract Progressive tool wear due to abrasive carbon fibres is one of the main issues in machining of CFRP and responsible for the short tool life. Because of occurring wear during machining, the tool’s micro-geometry changes continuously resulting in higher process forces and an increasing risk for workpiece damages. In this paper, a novel analytical model is presented in order to predict the wear-related change of the micro-geometry in orthogonal machining of CFRP depending on the fibre orientation and the initial tool geometry. For this purpose, a concept called the wear rate distribution is introduced which represents a measure to quantify the wear rate along the active micro-geometry. Based on experimental investigation, it is shown that the shape of an arbitrary wear rate distribution between two closely spaced wear states can be approximated and parameterised with a “line - curve - line” approach. Using the authors’ previously published analytical force model, the wear rate distribution can be calculated as function of five wear parameters that are used to parameterise the active micro-geometry of an arbitrary wear state. Based on an iterative solver, this is used to simulate the tool wear progression during machining. For model validation, the simulation is compared to experimental data in terms of the cutting edge profiles, the amount of worn tool material and the process forces. Accordingly, the wear model is capable to reproduce the most important wear characteristics, e.g. the cutting edge rounding, the decreasing clearance angle and the increasing contact length at the flank face.

Cutting Force Prediction of Ti6Al4V using a Machine Learning Model of SPH Orthogonal Cutting Process Simulations

Abstract: The prediction of machining processes is a challenging task and usually requires a large experimental basis. These experiments are time-consuming and require manufacturing and testing of different tool geometries at various process conditions to find optimum machining settings. In this paper, a machine learning model of the orthogonal cutting process of Ti6Al4V is proposed to predict the cutting and feed forces for a wide range of process conditions with regards to rake angle, clearance angle, cutting edge radius, feed and cutting speed. The model uses training data generated by virtual experiments, which are conducted using physical based simulations of the orthogonal cutting process with the smoothed particle hydrodynamics (SPH). The ML training set is composed of input parameters, and output process forces from 2500 instances of GPU accelerated SPH simulations. The resulting model provides fast process force predictions and can consider the cutter geometry in comparison to classical analytical approaches.

Acoustic roughness measurement of railway tracks: Implementation of an optical measurement approach & possible improvements to the standard

Abstract: The measure for assessing the acoustic quality of the rail surfaces, the acoustic roughness, is defined in the EN 15610 standard. It is shown that this standard contains gaps with regard to the applied procedures for processing the raw data to the quantity of acoustic roughness. Additions to the standard appear necessary to ensure better comparability of the results. A piece of rail tactilely measured by METAS (Swiss Federal Institute of Metrology) was used as a reference. Measurement data recorded by a laser triangulation sensor was used to quantify the adjustments to the standard. This paper provides an overview of the individual processing steps and systematically examines possible additions to the standard to improve the quality of the outcome. Special emphasis was given to a method for outlier removal, pre-filtering, spike removal, curvature correction and calculation of one-third octave bands. It becomes apparent that different implementations can have a significant impact on the final result. The filter used, the wavelength ranges, the methodology for removing outliers should be specified. The spike removal, curvature correction and the calculation of the one-third octave bands should be supplemented in detail to reduce ambiguities in the implementation.

Acoustic Roughness Measurement of Railway Tracks: Implementation of a Chord-Based Optical Measurement System on a Train

Abstract: A large part of the noise emissions from rail traffic originates from rolling noise. This is significantly determined by the surface roughness of the wheel and the rail. To quantitatively assess the noise generation from the wheel–rail contact, it is necessary to measure the surface roughness of the rail network. Direct measurements via trolley devices are usually associated with the need for a free track and limitation in velocity. Indirect measurements of rail roughness, such as measuring axle-box accelerations, enable operation during regular passage but only estimate the acoustic roughness. In this study, the potential of an optical and consequently contact-free measurement method using laser triangulation sensors to measure rail roughness from the train is investigated. The approach can combine the advantage of operation during regular passage with the characteristics of a direct measurement, enabling large-scale monitoring of the rail network. A measurement run with a train was carried out on a meter-gauge track at speeds up to 80 km h−1 The results of the optical measurement approach were compared with a tactile reference measurement on the track. The results show good agreement of the new measurement setup for dry rail surface conditions at 50 km h−1, with a mean deviation of 1.48 dB.

Laser Preheating for Hot Crack Reduction in Direct Metal Deposition of Inconel 738LC

Abstract: Welding of precipitation-hardenable nickel-based super alloys that contain large amounts of Al and Ti is challenging due to their high susceptibility to hot cracking. For metal additive manufacturing (AM) by powder bed fusion (PBF) or direct metal deposition (DMD), various welding process adjustments may prevent the formation of cracks. The aim of this study is the development and experimental characterization of a laser preheating process for DMD of Inconel 738LC. Metallographic cross-sections of multiple test specimens were analyzed to quantify the effect of initial substrate temperature, specimen geometry, deposition parameters, and scanning strategy on the resulting crack density. The results show that increased substrate temperature by laser preheating and reduced specimen size leads to crack-free deposited structures. Therefore, the proposed preheating process may be applied for part fabrication or repair by DMD to reduce or even completely prevent the risk of hot cracking.

An action-oriented teaching approach for intelligent and energy efficient precision manufacturing

Abstract: Thermal errors of machine tools are a major contributor to inaccuracies of produced workpieces. Especially, the reduction of thermal errors without increasing the energy consumption of the machine tool and the shop floor due to exact air conditioning has a great social, scientific, and industrial relevance. Therefore, the Institute of Machine Tools and Manufacturing (IWF) at ETH Zürich set up a series of three lab courses to increase the awareness of undergraduate students on this important topic. In the first lab course the students elaborate how the carbon footprint of machine tools can be minimized over the whole live cycle including the manufactured products. Specifically, the students measure the energy demand and analyze the energy efficiency of the most important components of a 5-axis machine tool in different operating conditions. The second lab course focuses on the thermal chain of causes, which describes the physical fundamentals leading to the thermal deformations of machine tools. Temperature and displacement measurements as well as finite-element simulations of a purpose-built test bench visualize the characteristics of the thermal chain of causes. The third lab course completes the topic by dealing with model-based thermal compensation strategies, which enables a shift from resource-based towards intelligence-based reduction strategies for thermal errors. The students evaluate the thermal behaviour of a 5-axis machine tool with an on-machine measurement cycle and learn how to create physical and data-based thermal error compensation models.

Acoustic Roughness Measurement of Railway Tracks: Laboratory Investigation of External Disturbances on the Chord-Method with an Optical Measurement Approach

Abstract: For acoustic roughness monitoring of the railway network at train travelling speed, new direct measurement methods are required. Common direct measurement methods need the blocking of track sections, as they are based on manually operated devices. Indirect measurement methods such as accelerometer or microphone measurements can be installed on the train, but require a conversion of the obtained measurement data to rail roughness. Optical measurement methods allow a direct measurement from the moving train, even at higher speeds, due to the contact-free nature of the measurement. This paper investigates the influence of various disturbances on the measurement result, which are expected on the train. The frequently used chord method deploying laser triangulation sensors is used. Four sensors are integrated into the setup, thus providing the possibility to combine the results from four chord methods. The measurements of the optical system are compared with a tactile measurement of METAS (Swiss Federal Institute of Metrology) on a test bench equipped with a reference rail segment. It is shown that dust and water on the rail have a significant influence in the range of small wavelengths. Displacements and tilting of the sensor array, as well as vibrations, can be compensated to a certain level by the chord method, while a single sensor is significantly disturbed. The combination of four different chord lengths and selection of the theoretically optimal method for each one-third octave band shows an improvement of the measurement result. Based on the observations made, recommendations for practical tests on the train are concluded.

In-situ monitoring of powder bed fusion of metals using eddy current testing

Abstract: Powder bed fusion of metals (PBF-LB/M) is the most commonly used additive manufacturing process for the layerwise production of metal parts. Although the technology has developed rapidly in recent years, manufactured parts still lack consistent quality primarily owing to process-inherent variability, and the lack of effective sensing technologies enabling the ability to control the process during part production. Thus, there are high costs caused by rigorous post-process part inspection steps required to provide compliant part certificates. In contrast to typically deployed in-situ sensing technologies, eddy current testing (ECT) is a standardized nondestructive testing (NDT) technique able to provide compliant part certificates during post-process inspection according to existing standards. This study investigates the potential of ECT as an in-situ process monitoring technology for PBF-LB/M. Parts made from AlSi10Mg were manufactured on a PBF-LB/M machine using different process parameters yielding different relative densities ranging from 99%– 99.7%. During the build cycle, the parts were measured layer-by-layer with an ECT system mounted on the machine recoater. Signal analysis methods were developed which effectively separate and calibrate the electrical conductivity component (relative electrical conductivity) and the distance component (lift-off) of the ECT signals. The relative electrical conductivity was then compared to X-ray micro-computed tomography ( μ CT) measurement data demonstrating that layer-to-layer differences in relative density of about 0.1% can be successfully detected via ECT. In addition, the lift-off was used to monitor the thickness of the consolidated layers and the layer-to-layer part height. The results show that ECT is an effective technology for in-situ monitoring of the relative part density paving the way for deploying ECT for in-situ NDT of PBF-LB/M-manufactured parts.

Cloud-based thermal error compensation with a federated learning approach

Abstract: Thermal error compensation is one of the most research-oriented topics in manufacturing with rising importance in the industry. This paper presents an innovative Industry 4.0 application of thermal error compensation for precision engineering. A federated learning-based thermal error compensation approach running in the cloud is applied to two machine tools, one located at ETH Zürich, and another one at TU Wien. Although environmental conditions and thermal error behaviour of both machines differ, the implemented knowledge transfer across machines is a viable compensation strategy, albeit with limited precision. A detailed comparison of the two machines of the same type under the same load conditions shows foreseeable similarities in behaviour, but also clear differences due to the different configurations and lifetime status. The cloud-based compensation reduced the crucial thermal errors in the best case of both machine tools by more than 80% under heavier conditions. • A new cloud-based thermal error compensation approach is introduced. • Federated learning in terms of cloud and edge computing for reaching the required high level of safety and security is presented for thermal error compensation. • Detailed analysis of the same manufacturer and same type of machine tool with different wear and slightly different configuration. • Proof of concept for the transferability of the machine tool thermal error compensation model calibration period (learning phase) is reached by model transfer (transfer learning). • Compensation results already reduce the thermal error up to 80%.

Residual Stresses Measurements in Laser Powder Bed Fusion Using Barkhausen Noise Analysis

Abstract: In recent years, the advancement of technology brought the laser powder bed fusion process to its industrialisation step. Despite all the advancements in process repeatability and general quality control, many challenges remain unsolved due to the intrinsic difficulties of the process, notably the residual stresses issue. This work aimed to assess the usability of Barkhausen noise analysis (BNA) for the residual stress in situ monitoring of laser powder bed fusion on Maraging steel 300 (18Ni-300/1.2709). After measuring the evolution of grain size distribution over process parameter changes, two series of experiments were designed. First, a setup with an external force allows to validate the working principle of BNA on the chosen material processed using LPBF. The second experiment uses on-plates samples with different residual stress states. The results show a good stability in microstructure, a prerequisite for BNA. In addition, the external load setup acknowledges that signal variation correlates with the induced stress state. Finally, the on-plate measurement shows a similar signal variation to what has been observed in the literature for residual stress variation. It is shown that BNA is a suitable method for qualitative residual stresses variation monitoring developed during the LPBF process and underlines that BNA is a promising candidate as an in situ measurement method.

Dry Cutting Experiments Database Ti6Al4V and Ck45

Abstract: The numerical simulation of metal cutting processes requires material data for constitutive equations, which cannot be obtained with standard material testing procedures. Instead, inverse identifications of material parameters within numerical simulation models of the cutting experiment itself are necessary. The intention of the present report is the provision of results of a large scale experimental study of dry orthogonal cutting experiments of Ti6Al4V (3.7165 Grade 5) and Ck45 (AISI 1045) along with their documentation and interpretation. The process forces are evaluated and each cutting insert geometry has been measured prior to the experiments to determine the cutting edge radii for each experiment. The resulting chip forms are analysed and the averaged chip thicknesses are determined. A material characterization is performed, which includes microstructural investigations on the raw materials and is reported together with tensile test results. The assembled data set can be used for parameter identification when the experimental conditions are reproduced in numerical simulations. The cutting test results are finally used to derive coefficients for Kienzle’s force model. The data is stored in the pCloud and contains process force measurement data, cutting edge radii scans, pictures of chip geometries and etched chips.