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Schallschutz im Holzbau: Grundlagen und Vorbemessung: Holzbauhandbuch, Reihe 3, Teil 3, Folge 1
(2019)
Zeitverlaufsanalysen des Lärms in Gaststätten vor und nach einer raumakustischen Ertüchtigung
(2019)
Dämmstoffe aus nachwachsenden Rohstoffen in der Bauteilprognose mittels der Finiten-Elemente-Methode
(2020)
Bauakustik meets BIM
(2020)
Die Berechnung des bewerteten Norm-Trittschallpegels im Bau L'n,w erfolgt aktuell in der DIN 4109-2:2018 sowohl für den Massivbau als auch für den Holz-, Leicht- und Trockenbau unter Berücksichtigung relativ pauschaler Korrekturen für die flankierende Schallübertragung. Darüber hinaus unterliegen die derzeitigen Verfahren einigen weiteren gravierenden Beschränkungen des Anwendungsbereiches, die eine Überarbeitung der Verfahren wünschenswert erscheinen lassen. Basierend auf dem neuen vereinfachten Verfahren der DIN EN ISO 12354-2:2017 werden deshalb Berechnungsverfahren auf der Basis von Einzahlangaben vorgestellt, mit denen die direkte und die flankierende Trittschallübertragung, wie beim Luftschall, getrennt berechnet und anschließend aufsummiert werden. Hierdurch ergeben sich deutlich bessere Möglichkeiten, die tatsächliche Bausituation im Rechenmodell abzubilden und somit eine bessere Übereinstimmung zwischen dem prognostizierten und einem gemessenen Wert zu erhalten. Im Massivbau kann beispielsweise eine Vorsatzkonstruktion im Empfangsraum vor dem trennenden oder dem flankierenden Bauteil entsprechend ihrer schalltechnischen Wirkung berücksichtigt werden. Weiterhin können auch horizontale oder diagonale Übertragungssituationen oder die Trittschallübertragung von Treppen abhängig von der jeweiligen baulichen Situation berechnet werden. Die neuen Berechnungsverfahren ermöglichen damit eine wirtschaftlichere Dimensionierung der Bauteile.
Untersuchung des Einflusses von Vorsatzschalen vor Massivholzelementen auf das Stoßstellendämm-Maß
(2022)
Erfahrungen mit der DIN EN 15657:2017-10 und dem Empfangsplattenprüfstand an der TH Rosenheim
(2022)
Within the framework of a research focus at the TH Rosenheim on prediction methods for sound and impact sound insulation in timber constructions, methods of mathematical statistics and artificial intelligence are applied to sound insulation. To estimate the potential of those methods, one-third octave band spectra of measured sound insulation of sand-lime brickwork have been analyzed first. On selected data sets for certain building constructions, physically based calculation approaches according to the \backslashDIN{} series of standards, are compared with purely statistical methods such as GAMLSS (Generalized Additive Models for Location, Scale and Shape Parameters). The parameters derived from these procedures can be used for prediction purposes. The interval estimators resulting from these methods are compared. In addition, methods to classify the separating construction based on measurements are discussed. Thereby, in situ, measurements are used in addition to laboratory measurements.
Schallschutz von Gebäuden in Holzmodulbauweise Teil II - Messung und Simulation der Stoßstellen
(2024)
Strömungs- und Geräuschanalyse eines dezentralen Lüftungsgerätes mit PIV und akustischer Kamera
(2024)
Holzbasierte Bioökonomie und Kunststofftechnik: Nachwachsende Rohstoffe für technische Bauteile
(2024)
As generative AI (GenAI) becomes increasingly integrated into the professional workplace, offering significant productivity gains according to emerging research evidence, professionals and students need to build competencies to thrive in this new environment. In higher education, curricula must incorporate GenAI literacy to help students engage with this important and evolving technology. This research introduces results from a mixed-method study conducted among organisational practitioners, with the goal of creating an understanding of GenAI literacy needs across broad organisational contexts. We develop a Diamond Model of GenAI literacy for higher education to support curricular transformations needed to help students entering the GenAI-infused workplace. The suggested Diamond Model advocates for refining educational approaches to equip graduates with the capabilities to apply GenAI, maintain accountability, ensure authenticity and exercise agency in GenAI-driven workplaces.
An underrepresentation of women in executive positions has persisted for decades. This paper aims to analyze the financial impact of women in executive positions in German companies by examining the economic value added and exploring the effects of Environmental, Social, and Governance (ESG) factors and female supervisory board members on female board members. The results indicate that in the 200 largest German companies, the share of female executives increased between 2018 and 2022. Regardless of industry, female executives started at very low levels at around 4% in 2018; in 2022, this figure reached around 11%. Thereby, the financial sector showed the highest share of female executives at around 14% in 2022, and the industrial sector at around 9%. A closer look reveals that large companies have higher shares of female executives than smaller companies. Large companies show an average of 17% compared to small ones, and in 2022, only 8%. There is a positive correlation between the share of female supervisory board members and female executives, arguing that female supervisory board members seem to hire more female executives. Companies with more female executives tend to have lower ESG controversy scores, and companies with more female executives, measured by the economic value added, perform better financially than companies with few or no women. Companies with female executives show about 2 percentage points higher economic value added than those with the lowest share of females (no or few female executives). Thus, it seems that female executives matter and make a difference in companies.
Zielsetzung
Zur Stärkung der gesundheitlichen Resilienz der Bevölkerung in Deutschland soll der öffentliche Gesundheitsdienst (ÖGD) neu strukturiert werden. Die Prävention nicht-übertragbarer Erkrankungen soll am Bundesinstitut für Prävention und Aufklärung in der Medizin angesiedelt werden, in dem auch die Bundeszentrale für gesundheitliche Aufklärung aufgeht, während das Robert Koch-Institut für Infektionskrankheiten zuständig bleibt. Vor diesem Hintergrund soll durch den Vergleich von Ländern mit einer guten präventiven Versorgung untersucht werden, welche Strukturen und Maßnahmen für die Impfprävention förderlich sind.
Material & Methoden
Durch eine systematische Literaturrecherche wurden Länder mit hohen Impfquoten gegen Influenza identifiziert. Für den Ländervergleich wurden ein staatliches Gesundheitssystem sowie je eines mit sozialem bzw. privatem Krankenversicherungssystem herangezogen. Die Organisation der Public Health-Institutionen, ihre Aufgaben, Maßnahmen und Effizienz bei der Versorgung mit Schutzimpfungen wurden in dem jeweiligen Land analysiert und miteinander verglichen.
Ergebnisse
Großbritannien (GB), die Niederlande (NL) und die USA wurden in den Vergleich auf Grund ihrer Impfquoten gegen Influenza (81%, 73,%, 73% (OECD 2023)) eingeschlossen. In diesen Ländern unterstehen die Behörden dem nationalen Gesundheitsministerium, wobei sie in NL und den USA weisungsungebunden sind. In GB sind die Zuständigkeiten für infektiöse und nicht-infektiöse Erkrankungen auf zwei Behörden verteilt. Deutliche Unterschiede sind zwischen den Gesundheitssystemen in GB und NL und dem System der USA bei der Durchführung von Präventionsmaßnahmen erkennbar: Die starke Vernetzung zwischen dem ÖGD und der medizinischen Primärversorgung in GB und NL, Maßnahmen wie die Implementierung von Impfregistern, der Versand von Einladungen und Erinnerungen (NL) oder der „No-Reply-SMS-Service“ mit angeschlossenem digitalen Terminmanagement (GB) ermöglichen eine bürgernahe und gezielte Information über Impfungen. In der föderalen Struktur der USA liegt die Verantwortung für den Gesundheitsschutz zum Teil bei den Bundesstaaten bzw. den Bürgern. Die Aufgaben der Bundesbehörde beschränkt sich auf die Überwachung von Erkrankungen, der Gesundheitsdatenanalyse, Entwicklung von Präventionsstrategien und Durchführung von Aufklärungskampagnen.
Zusammenfassung und Diskussion
Aus der Organisationsform der Gesundheitsbehörden lässt sich der Erfolg von Impfmaßnahmen in den untersuchten Ländern nicht ableiten. Vielmehr scheinen der Grad der Zusammenarbeit der Akteure, die Verfügbarkeit von Surveillancedaten, die wirksame Aufklärung der Bevölkerung sowie die klare Zuweisung von Verantwortlichkeiten eine wesentliche Rolle zu spielen.
Die Gärtnerei Demmel in dem knapp 3.000 Einwohner großen Ort Seeshaupt am Starnberger See blickt auf eine über 100-jährige Geschichte zurück. 1902 gegründet, wird das Unternehmen in Familienbesitz von drei Generationen betrieben. 2002 wurde die Gärtnerei an einen langjährigen Mitarbeiter verpachtet, doch 2020 endete die Pacht, um das Gelände weiterentwickeln zu können. Studierende des 3. Semesters Architektur entwickeln Vorschläge für eine Revitalisierung des Geländes. Die Aufgabe ist der Entwurf eines neuen Gebäudes im Eingangsbereich. Es markiert den Zugang zum Gelände und steht beispielhaft für die Verbindung von Tradition und Moderne. Das Konzept basiert auf den suffizienten Prinzipien von „Einfach Bauen“: der Reduktion auf das Wesentliche und dem Verzicht auf alles Überflüssige.
Neue Erkenntnisse zur Wichtigkeit ausreichender Tageslichtversorgung im Innenraum haben planungsrelevante Änderungen normativer Vorgaben nach sich gezogen. Renate Hammer und Mathias Wambsganß veranschaulichen die neuen Anforderungen und erläutern die Möglichkeiten zur planerischen Umsetzung. Die Autoren klären, wann Tageslichtversorgung und Besonnung als ausreichend gelten, welche Qualitäten die Sichtverbindung nach außen erfüllen muss und wie Blendung durch Tageslicht zu begrenzen ist. Angaben zur melanopischen Wirkungsweise von Tageslicht bieten einen Einstieg in den planerischen Umgang mit nicht-visuellen Kriterien. Ein weiteres Kapitel zeigt die Schnittstellen mit anderen Aspekten der Bauplanung.
In the following article, we construct an interaction model of general language change. This contributes in particular to quantitative studies on reversible language change initiated by G. Altmann by adding explanatory character in tracing global features of general language change back to the individual interaction of speakers. Although the corresponding coupled differential equations are (presumably) non-integrable, we use methods from the theory of dynamical systems to deduce the long-term behaviour (depending on four interaction parameters) of the model for any given initial constellation of speakers. Subsequent numerical analysis of real data on language change is used to justify the relevance of the constructed model for the practicing quantitative linguist. We show how data-fitting methods can be used to determine the four interaction parameters and predict from them the long-term behaviour of the system, i.e. if complete language change or reversible language change will take place.
Adaptable Machining Process Identification based on Expert Knowledge and Artificial Intelligence
(2022)
The demand for product individuality increased enormously in recent years and thus affects directly manufacturers and their employees. Due to the increasing demand for batch-size-one production, every product needs specific manufacturing processes. Usually, employees determine these manufacturing steps with provided product data. This research proposal aims to contribute to the extraction of machining processes from product data and their assignment to suitable machinery. We plan to develop an organic computing system based on artificial intelligence methods to solve these problems by including customer-specific designs and employee expertise. The overall objective is to support employees in manufacturing facilities by simplifying the manufacturer and customer interaction.
Cutting and Packing problems are occurring in different industries with a direct impact on the revenue of businesses. Generally, the goal in Cutting and Packing is to assign a set of smaller objects to a set of larger objects. To solve Cutting and Packing problems, practitioners can resort to heuristic and exact methodologies. Lately, machine learning is increasingly used for solving such problems. This paper considers a 2D packing problem from the furniture industry, where a set of wooden workpieces must be assigned to different modules of a trolley in the most space-saving way. We present an experimental setup to compare heuristics, constraint optimization, and deep reinforcement learning for the given problem. The used methodologies and their results get collated in terms of their solution quality and runtime. In the given use case a greedy heuristic produces optimal results and outperforms the other approaches in terms of runtime. Constraint optimization also produces optimal results but requires more time to perform. The deep reinforcement learning approach did not always produce optimal or even feasible solutions. While we assume this could be remedied with more training, considering the good results with the heuristic, deep reinforcement learning seems to be a bad fit for the given use case.
Driven by increasing customer demands, manufacturing processes encompass increasingly intricate workflows. The industry relies on computer-aided process planning software to effectively manage the intricacies of these complex manufacturing processes. This software is crucial to analyze computer-aided design data for a product and determining the required machining steps. However, a notable challenge arises, particularly in the case of custom products, where the machining steps can significantly vary depending on the available machinery and the employees' preferences.This study introduces a configurable automated feature recognition framework based on expert knowledge. Experts can encode their insights and expertise within this framework using a configurable synthetic data generator. Modern graph neural networks learn from the data generated by this data generator, achieving an average recognition accuracy up to 80% (F1-score) with a runtime performance of 21.98 milliseconds per model. Importantly, it accomplishes this even when confronted with highly intersecting machining features without requiring data conversion into alternative formats, such as voxel or pixel representations.
A mechanically tunable planar single-turn inductor in air is proposed. The bistable flexible deflection of axially compressed wire segments is used for variation of the loop area of regular polygonal loop inductors. We present analytical expressions for the loop inductance and confirm the theoretical findings by magneto-quasi-static field simulation on exemplary polygonal circuits.
In the 1990s, China implemented educational reforms to expand access to education. However, the focus on neoliberal ideologies and educational success has led to significant social implications in the context of social strata. As a result, students now face pressure to perform in the educational system to achieve success and therefore social upward mobility. Families encourage their children to pursue education as a means of social advancement, and this has become a defining feature of Chinese society to have or not have social quality (suzhi). In this presentation, I will discuss how this focus on education impacts the social upward mobility and biographical orientations of elite students in China. I will discuss social mobility and stratification through the lens of habitus theory. According to P. Bourdieu, this theoretical perspective suggests that achievement in the context of social mobility is not solely dependent on economic capital but also on cultural capital. Biographically, this is highly interesting, as families represent the essential point of reference for educational decisions and impact making. Families play a crucial role in shaping educational decisions and aspirations; if individuals lack the necessary economic, social and cultural capital, they may seek opportunities in transnational contexts as a form of outsourcing and even biographical illusion.
A reinforcement of concrete structures is needed because of the low tensile strength of concrete. Corrosion of the usually used steel reinforcments cause issues during time. Therfore, alternative reinforcements produced from non-corosive materials - like polymer fibers - become more interesting. A polymer fiber has to reach high mechanical properties and a good bonding ability to concrete. Both properties can be influenced by the selection of polymer and the used production process. Two polymers, polypropylene and aliphatic polyketone are tested within this study. First mono-material fibers of each material are produced and tested, later the materials are combined in a core-shell fiber. All fibers are produced by standard extrusion or coextrusion and a later drawing process. The mechanical properties are determined by tensile tests. The calculation of interfacial shear strength from single fiber pull-out tests allows an evaluation of the bonding ability. Additionally, fiber surface before and after pull-out is examined using reflected light microscopy. Contact angle measurements are done to evaluate possible influences of the surface energy and polarity. Density measurements are used to compare weight potential of the different mono-material and core-shell fibers. The results show good mechanical properties for all fiber materials. The interfacial shear strength is ≈ 2-3 times higher for fibers with polyketone compared to the ones with polypropylene at the fibers surface, which can be explained by higher surface energy and polarity of the polyketone compared to polypropylene and different surface deformation during pull-out. Lower densities are reached by fibers containing polypropylene.
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.
Dieses Buch bietet Studierenden über 80 Übungsaufgaben und fünf Fallstudien inklusive ausführlicher Lösungen zu ausgewählten Themen der Produktionswirtschaft und Industrie 4.0. Jedes Kapitel enthält eine kurze Einleitung sowie zu erreichende Lernziele. Querverweise auf das Lehrbuch „Produktionswirtschaft“ von Kellner/Lienland/Lukesch erleichtern das Selbststudium und ermöglichen eine optimale Prüfungsvorbereitung. Die 3. Auflage wurde redigiert und um neue Rechenaufgaben sowie eine weitere Fallstudie zum Themenbereich Industrie 4.0 ergänzt.
This research examines the potential outputs, outcomes, and impacts of the German Act on Corporate Due Diligence Obligations in Supply Chains (LkSG) on the smallholder cocoa farmers in West Africa. The study primarily relies on a literature review and an impact pathway to conduct a systematic analysis to identify the potential effects of the LkSG on smallholder cocoa farmers. The findings indicate that some, but not all of the risks addressed by the LkSG align with those faced by smallholder cocoa farmers and their families. Additionally, the research also reveals weaknesses, particularly in managing environmental risks, which the LkSG does not adequately cover. Our findings show that in the short- and medium-term, the LkSG has no potential effects on smallholder cocoa farmers. Furthermore, the potential positive impacts of the law on smallholder cocoa farmers will take a long time to realize, as the LkSG considers primarily tier-1 suppliers. Companies in Germany might reassess their supply chains to strive for an LkSG-risk-free supply chain, which could in the long term have sustained impacts on smallholder cocoa farmers. However, we recommend a comprehensive risk analysis of the cocoa supply chain to enhance the human rights of cocoa farmers.
Environmental pollution by plastics is a global issue of increasing concern. However, microplastic analysis in complex environmental matrices, such as soil samples, remains an analytical challenge. Destructive mass-based methods for microplastic analysis do not determine plastics’ shape and size, which are essential parameters for reliable ecological risk assessment. By contrast, nondestructive particle-based methods produce such data but require elaborate, time-consuming sample preparation. Thus, time-efficient and reliable methods for microplastic analysis are needed. The present study explored the potential of frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) for rapidly and reliably identifying as well as differentiating plastics and natural materials from terrestrial environments. We investigated the fluorescence spectra of ten natural materials from terrestrial environments, tire wear particles, and eleven different transparent plastic granulates <5 mm to determine the optimal excitation wavelength for identification and differentiation via FD-FLIM under laboratory conditions. Our comparison of different excitation wavelengths showed that 445 nm excitation exhibited the highest fluorescence intensities. 445 nm excitation was also superior for identifying plastic types and distinguishing them from natural materials from terrestrial environments with a high probability using FD-FLIM. We could demonstrate that FD-FLIM analysis has the potential to contribute to a streamlined and time-efficient direct analysis of microplastic contamination. However, further investigations on size-, shape-, color-, and material-type detection limitations are necessary to evaluate if the direct identification of terrestrial environmental samples of relatively low complexity, such as a surface inspection soil, is possible.
Microplastic pollution of the environment has been extensively studied, with recent studies focusing on the prevalence of microplastics in the environment and their effects on various organisms. Identification methods that simplify the extraction and analysis process to the point where the extraction can be omitted are being investigated, thus enabling the direct identification of microplastic particles. Currently, microplastic samples from environmental matrices can only be identified using time-consuming extraction, sample processing, and analytical methods. Various spectroscopic methods are currently employed, such as micro Fourier-transform infrared, attenuated total reflectance, and micro Raman spectroscopy. However, microplastics in environmental matrices cannot be directly identified using these spectroscopic methods. Investigations using frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) to identify and differentiate plastics from environmental materials have yielded promising results for directly identifying microplastics in an environmental matrix. Herein, two artificially prepared environmental matrices that included natural soil, grass, wood, and high-density polyethylene were investigated using FD-FLIM. Our first results showed that we successfully identified one plastic type in the two artificially prepared matrices using FD-FLIM. However, further research must be conducted to improve the FD-FLIM method and explore its limitations for directly identifying microplastics in environmental samples.
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.