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Ingenieurinformatik
(2023)
Umfassende Programmierkenntnisse werden für Ingenieur:innen immer wichtiger, vor allem im Bereich der Produktentwicklung. Die Autoren erklären die Grundlagen der Ingenieurinformatik beispielhaft anhand von MATLAB, Simulink und Stateflow.
Neben den Grundkenntnissen lernen Leser:innen auch die Vorteile von MATLAB im Vergleich zu anderen Programmiersprachen kennen und anzuwenden. Die dabei vorgestellten Zusammenhänge und Prinzipien sind allgemeingültig und lassen sich daher auch problemlos auf andere Programmiersprachen übertragen. Konkrete Beispiele und Problemstellungen aus der Ingenieurpraxis werden vorgestellt und Lösungsansätze aufgezeigt.
Das Lehrbuch richtet sich an Studierende aller ingenieurwissenschaftlichen Studiengänge. Es eignet sich besonders für die Bachelorausbildung in den Studienschwerpunkten Elektro- und Informationstechnik, Mechatronik, Maschinenbau, Automatisierungstechnik sowie Energie- und Gebäudetechnik.
Für die zweite Auflage wurde das Lehrbuch umfassend überarbeitet und an die aktuellen Programmversionen angepasst. Weitere Übungen mit Lösungen sowie Hinweise zur Erstellung eigener Apps und Programmbeispiele stehen auf plus.hanser-fachbuch.de zur Verfügung.
Der auf dem Cover abgebildete Programmcode und die animierte Rakete wurden im Projekt „water rocket“ an der Technischen Hochschule Rosenheim im Jahr 2021 unter der Leitung von Prof. Zentgraf entwickelt. Die Projekt-Unterlagen und der zugehörige Filmbeitrag können unter www.th-rosenheim.de/rt-WaterRocket eingesehen werden.
Previous research on identifying plastic types and differentiating plastics from environmental material is promising by utilizing the specific fluorescence lifetime, but the evaluation still has to be automated. Therefore, an automated Gaussian analysis is developed for evaluating frequency-domain fluorescence lifetime images of plastics and environmental materials. Furthermore, we applied a “Multilayer Perceptron” and “Random Forest Classifier” to the data resulting from the Gaussian analysis of the frequency domain fluorescence lifetime imaging microscopy data. The classification results show high F1-scores, whereby the best “Multilayer Perceptron” and “Random Forest Classifier” achieved an F1-score of 90%. Thus, identifying and differentiating plastics and environmental materials is possible by applying a “Multilayer Perceptron” or “Random Forest Classifier” to the Gaussian-analyzed imaged fluorescence lifetime data.
Environmental pollution by plastics is an increasing problem. However, state-of-the-art methods have significant disadvantages in detecting and identifying plastics directly in an environmental matrix. In this study, we propose a blob detection algorithm in combination with a neural network for fast and automated identification of plastics and non-plastics in a single fluorescence lifetime image. Therefore an artificial environmental matrix is prepared that contains soil, grass, spruce and HDPE (high density polyethylene) particles. Several FD-FLIM (frequency domain fluorescence lifetime imaging microscopy) images are taken, and the detection algorithm and the neural network are applied. We successfully demonstrated the suitability of the thresholding algorithm and the binary classification of the HDPE particles directly in the environmental matrix.
Existing plastic analysis techniques such as Fourier transform infrared spectroscopy and Raman spectroscopy are problematic because samples must be anhydrous and identification can be hindered by additives. This article describes a new approach that has been successfully demonstrated in which plastics can be classified by neural networks that are trained, validated, and tested by frequency domain fluorescence lifetime imaging microscopy measurements.
The FD-FLIM technique has a high potential for automated post-consumer wood sorting. A problem of analysing post-consumer wood fluorescence properties is the uncertainty of the post-consumer wood category as the origin of the samples are unknown. In this study, the fluorescence properties of actual post-consumer wood is compared with prepared wood samples. The post-consumer wood samples display slightly different fluorescence intensities and lifetimes due to environmental influences and a higher sample diversity. For improved training of evaluation algorithms for post-consumer wood sorting, the prepared sample set should be extended or the post-consumer wood should be additionally analysed in the laboratory.
Development of a Neural Network for Automatic Classification of Post-Consumer Wood Using Rapid-FLIM
(2023)
The economic use of wood is a growing sector, not only because of the significant advantage of wood to retain CO 2 . It is crucial to increase the material recycling of wood in several lifecycles, but currently, there is no reliable post-consumer wood sorting technique in line. This research measures 365 post-consumer wood samples of classes A1-4 four times with the frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) subset method rapid fluorescence lifetime imaging microscopy (Rapid-FLIM). The data is analyzed on their statistical features. Four neural networks based on Multilayer perceptron are then trained and tested with twelve statistical features extracted from the Rapid-FLIM images. The best model for this application contains the optimizer RMSprop, the activation function SELU and the loss function binary crossentropy. The best model of this structure could achieve a false positive ratio of 4.79 % over the ten folds.
The fast classification and identification of plastics presents a significant challenge. The study assesses the suitability of a Multilayer Perceptron to classify and identify commonly found plastic types using Rapid-FLIM, achieving an accuracy of 88.33%. @inproceedingsSchwarz:23, Increasing demand for wood products requires methods to determine its harvest origin and ensure sustainable and legal sourcing. In 15 out of 21 cases, the origin of Quercus robur was differentiable in FD-FLIM studies.
Investigation of tool wear of the trimming unit and resulting quality in the edgebanding process
(2023)
The edgebanding process, i.e. the covering of the raw edge of the laminated particleboard by means of decorative plastic or real wood veneer bands, is an important process step in the manufacture of furniture components. The quality of the final product is significantly influenced by this production step. The manufacturing process step within the edgebanding machine begins with the milling of the raw edge. The quality of the edgebanding process is determined by a large number of process input variables, such as the tool used and the cutting geometry, the type of laminate used for the wood-based material, adhesives, etc. The quality of the edgebanding process is also determined by the type of material processed. Particularly with regard to the materials, the increased use of recycled wood in the particleboard sector and different types of adhesives (with reduced formaldehyde emissions) results in increased demands on the milling process. Due to this developments, most of the earlier investigations (in the years 1990 - 2000) are not comparable with today’s general conditions. The mechanical and optical properties of the edge applied to the end product are decisively influenced by the quality of this joint. The milling technology used, as well as the tool used for this purpose and its condition, is a decisive influencing factor in the formation of quality. Tests on the indication of various influencing variables in the edgebanding process at the Rosenheim Technical University of Applied Sciences showed that in the case of chipboard milling, a decrease in the electrical power required for the cutting process can take place with increasing tool wear. It was also demonstrated that previous process steps in furniture production, such as panel dividing by means of sawing or milling/nesting, generally have a significantly different influence on the subsequent joining process during edge banding process. Furthermore, a direct correlation was determined between the mechanical properties of the end product and the condition of the tool used, which can be used as a measurable indicator. In addition to the effect of the tool condition on the mechanical properties of the edge banding, this also has an impact on the optical quality characteristics. Accordingly, it could be demonstrated here that an increase in the size and number of chippings takes place in the laminate of the board material to be processed.
Due to the increasing customer demands, companies face the challenge of adapting their manufacturing facilities to produce batch size one parts. In this context, each component comes with specific customer requirements, significantly increasing the complexity of its manufacturing process. Traditional process planning done by employees is no longer feasible in the face of the growing complexity and diversity of batch size one parts. Therefore, there is a need for novel computer-aided process planning methods capable of autonomously learning and identifying the necessary machining features of these parts. We propose a configurable automated feature recognition framework tailored to batch size one parts to address this need. This framework comprises two main components. First, a customizable data generator is developed to create a dataset of computer-aided design models incorporating user-specific machining features. Second, a graph neural network is employed to learn these user-specific machining features by leveraging the graph structure represented by the vertices and edges in each computer-aided design model. We evaluate the effectiveness of our framework using a real-world example from the furniture industry. Specifically, we construct a dataset comprising over 7000 computer-aided design models of wooden boards using our framework's data generator. Each wooden board contains up to 30 randomly placed machining features for the application of connectors and fittings, randomly selected from 14 standard machining features commonly used in the furniture industry. An optimization algorithm adapts a graph neural network for classifying these specific machining features. The results demonstrate that our framework addresses the automated feature recognition problem without requiring data conversions, such as pixels or voxels, as other approaches often do. By introducing this configurable automated feature recognition framework, we solve the challenges posed by batch size one manufacturing. The framework's effectiveness and accuracy are demonstrated through extensive testing on the example of the furniture industry, showcasing its potential for enhancing manufacturing processes in various domains
In the whole field of woodworking, from carpentry to industry, new products are created and designed every day and manufacturers wonder if similar workpieces have already been produced in the company and if corresponding drawings, information, tools, jigs, etc. can be reused. Under certain circumstances, considerable duplication of work can be avoided and a more efficient production is possible. In order to find similar workpieces, it must be clarified what exactly is meant by similarity. The different fields of knowledge do not provide a clear definition. However, similarities are always used to compare objects. In woodworking, objects can be a wide variety of components and products, such as carcase sides, furniture fronts, fittings, tools or profile strips. The search for similar profiled elements – related to the potential, data structure and algorithms – is the focus of this paper. There is a wide range of different profiled elements, which are used constructively as well as decoratively, e.g. for baseboards, door frames, window frames or decorative moulding profiles. These profiles are manufactured in a multi-stage production process in which the workpieces are first machined with profiled tools before surface finishing takes place. Along this production chain, tools, machine settings and, in some cases, fixtures are used that are adapted to the respective profile and can be reused for the same or similar jobs. Inheritance of information offers the greatest potential of similarity search. Inheritance means that existing knowledge in the form of drawings, CNC programs, process parameters and setup specifications, etc., is transferred from existing profiles to a new profile. By inheriting existing information, for example, the effort required for process setting can be reduced by adopting spindle positions, positions of guides and stops, or feed and cutting speeds. However, this can only be done if the process knowledge and other technological information concerning a profile are sufficiently documented. This is the only way how all information is made available for the similarity search and inheritance, and also for setting the processes when the profile is manufactured once again. The profile data must therefore be stored in a meaningful structure without loss of information. Therefore, a holistic product data model was developed that combines the geometrical with the technological profile data. The developed model allows a combined search for geometrically and e.g. materially similar products – also with a weighted evaluation of the individual criteria. The research has shown that data modelling is the essential foundation for the implementation of modern AI algorithms to enable similarity search. In conclusion, the use of a search system for geometrically and technologically similar profiles represents a real innovation for wood processing companies. This paper presents a holistic approach for geometrical and technological similarity search presenting different algorithms
Die Technische Hochschule Rosenheim ist überregional bekannt für Ihre Expertise im Fachbereich Holz und Bau. Nach dem Vorbild des kooperativen Modells der Hochschule Landshut in Kooperation mit der TU München implementierte die TH Rosenheim im Jahr 2020 den Studiengang Ingenieurpädagogik für den Fachbereich Bautechnik mit der Option Holztechnik als Unterrichtsfach. Der Beitrag skizziert Motive, Strukturelemente sowie erste Entwicklungen. Dabei lassen erste deskriptive Ergebnisse die Hoffnung zu, dass sich über das Modell neue Zielgruppen für eine Karriere im Lehramt an beruflichen Schulen generieren lassen. Besonders auffällig für das Rosenheimer Modell ist die Bedeutsamkeit der Polyvalenz sowie das Interesse an einer praxisnahen Ausbildung rund um den Werk- und Baustoff Holz.
Stable isotope data from hypogene (i.e., below the line of weathering) iron oxides and gangue minerals from BIF-hosted iron ore deposits in Australia, South Africa, and Brazil have significantly assisted in constraining different hydrothermal fluid sources and fluid flow models during the upgrade of BIF to iron ore. The δ18O values on iron oxides from BIF and different paragenetic stages of enrichment display a consistent decrease from unenriched BIF (4–9‰) to as low as −10‰ for high-grade iron ore. This large shift in oxygen isotope values is interpreted as evidence for enormous incursion of ‘ancient’ meteoric water into fault and fracture zones at the time of iron enrichment during the Archean and Paleoproterozoic time. The δ18Ofluid values of paragenetically early iron oxides of > 4‰ suggest the involvement of magmatic fluids in greenstone belt-hosted Carajás-type iron ore deposits, and basinal brines in basin-hosted Hamersley-type deposits. In contrast, the paragenetically late stage iron oxides in the metamorphosed, basin hosted iron ore deposits of the Quadrilátero Ferrífero display δ18Ofluid values > 6‰. This reflects the renewed deep crustal, hypogene (metamorphic or magmatic) fluid influx. Carbon and oxygen isotope data on carbonates in BIF and hydrothermally altered iron ore indicate that carbon in the latter is not derived from BIF units, but represents either magmatic carbon in the case of the Carajás-type deposits or carbon within the underlying basin stratigraphy as in the case of the Hamersley-type iron deposits. The systematic decrease of δ18O values in iron oxides from the early to late paragenetic stages and from the distal to proximal alteration zone, including the ore zone, may be used as a geochemical vector. In this case, oxygen isotope analyses on iron oxides provide a potential exploration tool, particularly for targeting the extension of iron ore bodies or entirely concealed high-grade iron ore deposits, in which hematite/magnetite are frequently the only mineral that can be readily analysed.
Das Force Concept Inventory ist ein international etabliertes Diagnoseinstrument für das Konzeptverständnis der Newtonschen Mechanik. Wir haben über einen Zeitraum von zehn Jahren von knapp 5000 Studierenden der Ingenieurwissenschaften an der TH Rosenheim zu Studienbeginn Testdaten erhoben. Die Auswertung mittels Item Response Curves erlaubt für jede Frage die Analyse sowohl der richtigen als auch aller falschen Antwortoptionen. Insbesondere lassen sich auf diese Weise Distraktoren identifizieren, die gängige Fehlvorstellungen widerspiegeln. Es zeigt sich, dass die am häufigsten gewählten Distraktoren auf der Annahme beruhen, jeder Bewegung müsse eine Kraft in Bewegungsrichtung zu Grunde liegen. Daten von Universitäten der USA zeigen ein vergleichbares Ergebnis. Die vorgestellte Analyse dient als Grundlage zur Verbesserung von Lehrsequenzen.
This article examines interweaving collective histories in different formerly colonized regions of the world: 1. Migratory movements from the territory of the former Ottoman Empire to the Americas, specifically to Brazil, and 2. transregional migration between different regions within China. On the basis of empirical data, we discuss sociological biographical research as an approach to analyzing migration and social mobility as transgenerational processes. In the case of Syrians in Brazil who have fled from the civil war, these processes are reflected in transnational family structures, transgenerational mandates, and knowledge transmission. In the case of domestic migration within China, the “mission” that families give their children is social advancement through education (e.g., Crabb 2010; Fong 2004). In the context of anti-Western discourses in China, it can be demonstrated that postcolonial discourses are functional in the effort to regain former international strength and national prosperity, and that discourses on “becoming a modern citizen” pervade family aspirations. The article is intended as a plea for i) taking a closer look at historical and contemporary South-South relations, and ii) situating current migration movements historically. It ties into global historical and sociological debates on “shared/common histories” and “intertwined histories."
Der Artikel beschreibt die Änderungen der Zuordnungstabellen für das Brandverhalten von Baustoffen bei Klassifizierung nach EN 13501-1, speziell aus dem Blick der Technischen Isolierung. Hierbei ist insbesondere zwischen "linearen Rohrdämmstoffen" und Dämmstoffen als "sonstige Bauprodukte" zu unterscheiden.