Approximate method for predicting the permanent set in a beam in vacuo and in water subject to a shock wave

An approximate method to compute the maximum deformation and permanent set of a beam subjected to shock wave laoding in vacuo and in water was investigated. The method equates the maximum kinetic energy of the beam (and water) to the elastic plastic work done by a static uniform load applied to a beam. Results for the water case indicate that the plastic deformation is controlled by the kinetic energy of the water. The simplified approach can result in significant savings in computer time or it can expediently be used as a check of results from a more rigorous approach. The accuracy of the method is demonstrated by various examples of beams with simple support and clamped support boundary conditions

Identical NC-code on Different Machine Tools - Similarities and Differences in Timing and Positioning

Process and tool condition monitoring systems are a prerequisite for autonomous production. For online monitoring, it is the state of the art to use reference signals of correct processes to improve failure sensitivity and reduce false alarms. Transferring these reference signals from other machines economizes on teach-in processes and complex simulations. However, the varying behaviour of the two machines leads to differences that need to be considered for the transfer. This work aims to identify similarities and differences in the timing and positioning of multiple machines when executing identical machining instructions. A comparison of process signals quantifies similarities and differences among machines. Results describe differences between process sequences, rapid traverse speeds, rapid traverse paths, machining feed speeds, machining feed paths, tool engagement time, and the temporal alignment of signals. Differences primarily originated from different control parameters and strategies as well as physical drive limitations. During machining differences occurred most frequently when axes were accelerated. Differences accumulated over prolong periods of machining and eventually became relevant from the perspective of online monitoring

Multivariate time series data of milling processes with varying tool wear and machine tools

Machining is an essential part of modern manufacturing. During machining, the wear of cutting tools increases, eventually impairing product quality and process stability. Determining when to change a tool to avoid these consequences, while still utilizing most of a tool's lifetime is challenging, as the tool lifetime can vary by more than 100% despite constant process parameters [1]. To account for these variations, all tools are usually changed after a predefined period of time. However, this strategy wastes a significant proportion of the remaining lifetime of most tools. By monitoring the wear of tools, all tools can potentially be used until their individual end of life. Research, development, and assessment of such monitoring methods require large amounts of data. Nevertheless, only very few datasets are publicly available. The presented dataset provides labeled, multivariate time series data of milling processes with varying tool wear and for varying machine tools. The width of the flank wear land VB is used as a degradation metric. A total of nine end milling cutters were worn from an unused state to end of life (VB ≈ 150 µm) in 3-axis shoulder milling of cast iron 600–3/S. The tools were of the same model (solid carbide end milling cutter, 4 edges, coated with TiN-TiAlN) but from different batches. Experiments were conducted on three different 5-axis milling centers of a similar size. Workpieces, experimental setups, and process parameters were identical on all of the machine tools. The process forces were recorded with a dynamometer with a sample rate of 25 kHz. The force or torque of the spindle and feed drives, as well as the position control deviation of feed drives, were recorded from the machine tool controls with a sample rate of 500 Hz. The dataset holds a total of 6,418 files labeled with the wear (VB), machine tool (M), tool (T), run (R), and cumulated tool contact time (C). This data could be used to identify signal features that are sensitive to wear, to investigate methods for tool wear estimation and tool life prediction, or to examine transfer learning strategies. The data thereby facilitates research in tool condition monitoring and predictive maintenance in the domain of production technology

Wear curve based online feature assessment for tool condition monitoring

The performance of a process monitoring system is determined by the information available to it. Existing methods for selecting relevant process information (features) work offline with data of faulty processes that is often unavailable or neglect random disturbances. This increases the risk of choosing non-sensitive features. Hence, this paper investigates whether a non-sensitive feature is detectable online in an initial selection of features presumed to be sensitive. A method for quantifying and assessing trends in features online is described. In the validation with turning and drilling processes, a single non-sensitive feature was detected successfully in seven out of eight test cases. © 2020 The Authors

Artificial Wear for the Assessment of Monitoring Performance

Various tool condition monitoring systems exist, that can increase machine availability and process reliability. Assessing and comparing their performance, however, requires high expenditure due to real process failures being scarce, too different or costly to reproduce. Hence, this paper investigates the reproducible simulation of flank wear. It introduces and validates a geometry for indexable inserts that results in process changes similar to those caused by natural flank wear. The validation considers turning processes with different feeds, depth of cut and cutting speeds in steel. Results demonstrate that the proposed geometry for indexable inserts affects process forces similar to natural flank wear

Transfer of Process References between Machine Tools for Online Tool Condition Monitoring

Process and tool condition monitoring systems are a prerequisite for autonomous production. One approach to monitoring individual parts without complex cutting simulations is the transfer of knowledge among similar monitoring scenarios. This paper introduces a novel monitoring method which transfers monitoring limits for process signals between different machine tools. The method calculates monitoring limits statistically from cutting processes carried out on one or more similar machines. The monitoring algorithm aims to detect general process anomalies online. Experiments comprise face‐turning operations at five different lathes, four of which were of the same model. Results include the successful transfer of monitoring limits between machines of the same model for the detection of material anomalies. In comparison to an approach based on dynamic time warping (DTW) and density‐based spatial clustering of applications with noise (DBSCAN), the new method showed fewer false alarms and higher detection rates. However, for the transfer between different models of machines, the successful application of the new method is limited. This is predominantly due to limitations of the employed process component isolation and differences between machine models in terms of signal properties as well as execution speed

Grußwort

Die seit einem halben Jahrhundert bestehende Partnerschaft zwischen den Universitäten Hamburg und Bordeaux hat ihre praktische Umsetzung in vielerlei Formen gefunden. Vor allem zwei Gründe gaben den Ausschlag, dass jetzt zum ersten Mal in der langen Partnerschaftsgeschichte ein Jubiläum feierlich begangen wurde. Der eine davon war das Erscheinen eines umfangreichen, in enger Hamburg-Bordelaiser Historiker-Kooperation entstandenen Jubiläumsbandes. Den anderen Anlass bot die Verleihung der Würde eines Ehrendoktors der Universität Hamburg durch das Department Sprache, Literatur, Medien (SLM) II an den Bordelaiser Germanisten Jean Mondot für seine der europäischen Aufklärung insbesondere in Deutschland geltenden, Maßstäbe setzenden Forschungen.The partnership between the Universities of Hamburg and Bordeaux, which has existed for half a century, has been put into practice in many forms. There were two main reasons for the fact that this is the first time in the long history of partnership that an anniversary has been celebrated. One of these was the publication of an extensive anniversary volume, which was produced in close cooperation with the Hamburg-Bordelais historians. The other occasion was the conferral of an honorary doctorate from the University of Hamburg by the Department of Language, Literature and Media (SLM) II to the Bordelaiser German scholar Jean Mondot for his research on European Enlightenment, which set new standards, particularly in Germany

Thickness dependence of spin-orbit torques generated by WTe2

We study current-induced torques in WTe2/permalloy bilayers as a function of WTe2 thickness. We measure the torques using both second-harmonic Hall and spin-torque ferromagnetic resonance measurements for samples with WTe2 thicknesses that span from 16 nm down to a single monolayer. We confirm the existence of an out-of-plane antidamping torque, and show directly that the sign of this torque component is reversed across a monolayer step in the WTe2. The magnitude of the out-of-plane antidamping torque depends only weakly on WTe2 thickness, such that even a single-monolayer WTe2 device provides a strong torque that is comparable to much thicker samples. In contrast, the out-of-plane field-like torque has a significant dependence on the WTe2 thickness. We demonstrate that this field-like component originates predominantly from the Oersted field, thereby correcting a previous inference drawn by our group based on a more limited set of samples.Comment: 8 pages, 8 figure

A survey and critique of Marian antiphons in organ literature

Four Marian Antiphons - Alma Redemptoris Mater, Ave Regina Caelorum, Regina Caéli, and Salve Regina - are plainchants written approximately during the twelfth century for use at the close of Compline in the Roman Catholic liturgy of the Divine Office. These plainchants were assigned to specific times in the liturgical year: Alma Redemptoris Mater, first Sunday in Advent until the Feast of Purification, February 2; Ave Regina Caelorum, following the close of the Feast of Purification until the Holy Thursday of Lent; Regina Caéli, following Compline of Holy Saturday until the Saturday after Pentecost; Salve Regina, Trinity Sunday to the evening before Advent Sunday. This paper is a survey of organ compositions based on one of the Marian Antiphons, and includes a critique of each piece as to their compositional style and technical difficulty. The works span the years between the fifteenth century and 2019. Over two hundred-five works were found.Ope