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The recent amendment to the Ethernet physical layer known as the IEEE 802.3cg specification, allows to connect devices up to a distance of one kilometer and delivers a maximum of 60 watts of power over a twisted pair of wires. This new standard, also known as 10BASE-TIL, promises to overcome the limits of current physical layers used for field devices and bring them a step closer to Ethernet-based applications. The main advantage of 10BASE- TIL is that it can deliver power and data over the same line over a long distance, where traditional solutions (e.g., CAN, IO-Link, HART) fall short and cannot match its 10 Mbps bandwidth. Due to its recentness, IOBASE- TIL is still not integrated into field devices and it has been less than two years since silicon manufacturers released the first Ethernet-PHY chips. In this paper, we present a design proposal on how field devices could be integrated into a IOBASE-TIL smart switch that allows plug-and-play connectivity for sensors and actuators and is compliant with the Industry 4.0 vision. Instead of presenting a new field-level protocol for this work, we have decided to adopt the IO-Link specification which already includes a plug-and-play approach with features such as diagnosis and device configuration. The main objective of this work is to explore how field devices could be integrated into 10BASE-TIL Ethernet, its adaption with a well-known protocol, and its integration with Industry 4.0 technologies.
This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual
labour and increased productivity.
The fourth industrial revolution presents a multitude of challenges for industries, one of which being the increased flexibility required of manufacturing lines as a result of increased consumer demand for individualised products. One solution to tackle this challenge is the digital twin, more specifically the standardised model of a digital twin also known as the asset administration shell. The standardisation of an industry wide communications tool is a critical step in enabling inter-company operations. This paper discusses the current state of asset administration shells, the frameworks used to host them and their problems that need to be addressed. To tackle these issues, we propose an event-based server capable of drastically reducing response times between assets and asset administration shells and a multi-agent system used for the orchestration and deployment of the shells in the field.
In times of short product life cycles, additive manufacturing and rapid tooling are important methods to make tool development and manufacturing more efficient. High-performance polymers are the key to mold production for prototypes and small series. However, the high temperatures during vulcanization injection molding cause thermal aging and can impair service life. The extent to which the thermal stress over the entire process chain stresses the material and whether it leads to irreversible material aging is evaluated. To this end, a mold made of PEEK is fabricated using fused filament fabrication and examined for its potential application. The mold is heated to 200 ◦C, filled with rubber, and cured. A differential scanning calorimetry analysis of each process step illustrates the crystallization behavior and first indicates the material resistance. It shows distinct cold crystallization regions at a build chamber temperature of 90 ◦C. At an ambient temperature above Tg, crystallization of 30% is achieved, and cold crystallization no longer occurs. Additional tensile tests show a decrease in tensile strength after ten days of thermal aging. The steady decrease in recrystallization temperature indicates degradation of the additives. However, the tensile tests reveal steady embrittlement of the material due to increasing crosslinking.
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.
Virtual Reality (VR) offers novel possibilities for remote training regardless of the availability of the actual equipment, the presence of specialists, and the training locations. Research shows that training environments that adapt to users' preferences and performance can promote more effective learning. However, the observed results can hardly be traced back to specific adaptive measures but the whole new training approach. This study analyzes the effects of a combined point and leveling VR-based gamification system on assembly training targeting specific training outcomes and users' motivations. The Gamified-VR-Group with 26 subjects received the gamified training, and the Non-Gamified-VR-Group with 27 subjects received the alternative without gamified elements. Both groups conducted their VR training at least three times before assembling the actual structure. The study found that a level system that gradually increases the difficulty and error probability in VR can significantly lower real-world error rates, self-corrections, and support usages. According to our study, a high error occurrence at the highest training level reduced the Gamified-VR-Group's feeling of competence compared to the Non-Gamified-VR-Group, but at the same time also led to lower error probabilities in real-life. It is concluded that a level system with a variable task difficulty should be combined with carefully balanced positive and negative feedback messages. This way, better learning results, and an improved self-evaluation can be achieved while not causing significant impacts on the participants' feeling of competence.
Die Oberflächen dentaler Implantate sind definiert durch eine raue Oberfläche, um die Integration in den menschlichen Knochen zu optimieren. Entzündungen des umgebenden Zahnfleisches zählen dabei zu den häufigsten Komplikationen nach einer Implantation. Diese Entzündungen entstehen hauptsächlich durch bakterielle Infektionen des Weichgewebes an der Implantations-Stelle. Die raue Oberfläche trägt jedoch zu einer solchen Infektion bei. Da der Implantat-Kopf zum Teil aus dem Knochen herausragt, erfolgt beispielsweise beim Zähneputzen eine Freilegung der Implantat-Oberfläche. Die durch die Rauheit vergrößerte Oberfläche bietet dabei ideale Voraussetzungen für eine Bakterienansiedlung. In der aktuellen Forschung steht die Entwicklung einer Oberfläche im Vordergrund, die eine antibakterielle Funktionalisierung erzeugt. Diese verhindert die Bakterienansiedlung und wirkt einer Entzündung entgegen. Um die Beschichtung vor Verschleiß zu schützen und ihre Lebensdauer der antibakteriellen Wirkung zu erhöhen, ist es möglich die Oberfläche mit einer
Mikrostruktur zu versehen.
Das Ziel der vorliegenden Arbeit ist die Identifikation geeigneter Mikrostrukturierungen, die der antibakteriellen Beschichtung einen optimalen Schutz vor Verschleiß bieten. Am Beispiel von Titan-Zahnimplantaten wird der Schutz der aufgetragenen Biohybridbeschichtung gegen abrasiven Verschleiß untersucht. Im Vorfeld wird eine Analyse der fertigungstechnischen Möglichkeiten mit Blick auf dentale Implantate und Mikrostrukturen durchgeführt, um das ein passendes Verfahren zu identifizieren. Die Analogiebauteile als Probenkörper werden, mithilfe des zuvor ausgewählten Verfahrens, mit verschiedenen Mikrostrukturen versehen. Im Rahmen einer Versuchsdurchführung, die die mechanische Belastung bei einem Zahnputzdurchgang imitiert, werden die verschiedenen Mikrostrukturen auf ihre Eignung für diese Anwendung überprüft. Ein Vorversuch dient zur Identifizierung eines geeigneten Ankerpeptids, welches den bindenden Bestandteil der Biohybridbeschichtung darstellt. Aus
drei zuvor ausgewählten Ankerpeptiden wird das mit der besten Adhäsionsfähigkeit herausgestellt. Im finalen Versuchsdurchlauf wird das Ankerpeptid auf die Oberflächen, die mit den Mikrostrukturen versehen sind, aufgetragen. Dabei ist das Ziel eine Mikrostruktur
herauszustellen, die den höchstmöglichen Schutz bietet.
Durch eine Fluoreszenzprüfung mithilfe eines Flourescence Plate Readers wird jede Kombination nach den Belastungsversuchen auf den Restanteil der Beschichtung überprüft.
Das Ergebnis stellt eine Mikrostruktur dar, die den bestmöglichen Schutz bietet. Dies ist erkennbar durch den höchsten Anteil an Restbeschichtung. Eine Strukturierung mit sogenannten Micro-Grooves in Kombination mit dem MacHis-Ankerpeptid erzielte in der Analyse der Belastungssimulationen die besten Ergebnisse bezüglich des Schutzes der Beschichtung. Durch die Versuche bestätigte sich eine weitere
Annahme. Die Strukturierung der Oberfläche erzielt einen deutlich höheren Schutz im Vergleich zu einer unstrukturierten Oberfläche. Zudem hat sich herausgestellt, dass eine Beschichtung mit dem sogenannten PEO-Verfahren eine deutlich größere Adhäsion der
Biohybridbeschichtung erzielt. Dies wird jedoch Thema weiterführender Forschungen sein und kein Bestandteil der vorliegenden Arbeit.
In the Laser Powder Bed Fusion (LPBF) process, parts are built out of metal powder material by exposure of a laser beam. During handling operations of the powder material, several influencing factors can affect the properties of the powder material and therefore directly influence the processability during manufacturing. Contamination by moisture due to handling operations is one of the most critical aspects of powder quality. In order to investigate the influences of powder humidity on LPBF processing, four materials (AlSi10Mg, Ti6Al4V, 316L and IN718) are chosen for this study. The powder material is artificially humidified, subsequently characterized, manufactured into cubic samples in a miniaturized process chamber and analyzed for their relative density. The results indicate that the processability and reproducibility of parts made of AlSi10Mg and Ti6Al4V are susceptible to humidity, while IN718 and 316L are barely influenced.
Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures.
The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality.