Fachbereich Maschinenbau und Mechatronik
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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.
Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers’ actions. Game elements are selected according to the work task and users’ preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting.
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.
The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.
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.
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.
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.
Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.
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.
Bei Schienenfahrzeugen, die mit dem Zugsicherungssystem ETCS betrieben sind, wird die Odometrie durch eine diskrete Ortung mittels physischen Balisen zurückgesetzt.
Diese Arbeit befasst sich mit der Innovation von virtuellen Balisen. Virtuelle Balisen, können eingesetzt werden, um physische, im Gleisbett montierte Balisen zu ersetzen. Durch den Einsatz von virtuellen Balisen soll der Infrastrukturausbau von ETCS vorangetrieben werden, indem sie als virtuelle Komponente auf Schienenfahrzeugen eingesetzt werden.
Im Rahmen dieser Arbeit wird die Fragestellung beantwortet, ob eine bordautonome Zugortung mittels virtuellen Balisen in einem ausgewählten Szenario mit einem akzeptablen Risiko verbunden ist? Das Szenario besteht aus einem Schienenfahrzeug, welches mit dem Zugsicherungssystem ETCS Level 2 auf einer eingleisigen Nebenstrecke betreiben wird. Hierzu werden zunächst die Grundlagen von ETCS und der satellitenbasierten Ortung erläutert. Des Weiteren werden die Grundlagen des CSM Prozesses und der expliziten Risikoabschätzung eingeführt.
Aufbauend auf diesen Grundlagen wird der CSM Prozess angewandt und dabei eine Systemdefinition mit den Schnittstellen des Systems zur Umwelt erstellt. Mit der Hazop-Methode werden die Gefährdungen der Schnittstellen erfasst und beurteilt. Die sicherheitsrelevanten Gefährdungen werden in einer FMEA bewertet. In der folgenden Diskussion werden sicherheitsrelevante Gefährdungen nochmals betrachtet.
Das Ergebnis der Arbeit ist, dass im ausgewählten Szenario, unter der Verwendung der CSM-Prozesse und der industriell anerkannten Methoden Hazop und FMEA, die Integration der Board-autonomen-Ortung mit einem akzeptablen Risiko verbunden ist.
There is a growing demand for more flexibility in manufacturing to counter the volatility and unpredictability of the markets and provide more individualization for customers. However, the design and implementation of flexibility within manufacturing systems are costly and only economically viable if applicable to actual demand fluctuations. To this end, companies are considering additive manufacturing (AM) to make production more flexible. This paper develops a conceptual model for the impact quantification of AM on volume and mix flexibility within production systems in the early stages of the factory-planning process. Together with the model, an application guideline is presented to help planners with the flexibility quantification and the factory design process. Following the development of the model and guideline, a case study is presented to indicate the potential impact additive technologies can have on manufacturing flexibility Within the case study, various scenarios with different production system configurations and production programs are analyzed, and the impact of the additive technologies on volume and mix flexibility is calculated. This work will allow factory planners to determine the potential impacts of AM on manufacturing flexibility in an early planning stage and design their production systems accordingly.
Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
Traditional vulcanization mold manufacturing is complex, costly, and under pressure due to shorter product lifecycles and diverse variations. Additive manufacturing using Fused Filament Fabrication and high-performance polymers like PEEK offer a promising future in this industry. This study assesses the compressive strength of various infill structures (honeycomb, grid, triangle, cubic, and gyroid) when considering two distinct build directions (Z, XY) to enhance PEEK’s economic and resource efficiency in rapid tooling. A comparison with PETG samples shows the behavior of the infill strategies. Additionally, a proof of concept illustrates the application of a PEEK mold in vulcanization. A peak compressive strength of 135.6 MPa was attained in specimens that were 100% solid and subjected to thermal post-treatment. This corresponds to a 20% strength improvement in the Z direction. In terms of time and mechanical properties, the anisotropic grid and isotropic cubic infill have emerged for use in rapid tooling. Furthermore, the study highlights that reducing the layer thickness from 0.15 mm to 0.1 mm can result in a 15% strength increase. The study unveils the successful utilization of a room-temperature FFF-printed PEEK mold in vulcanization injection molding. The parameters and infill strategies identified in this research enable the resource-efficient FFF printing of PEEK without compromising its strength properties. Using PEEK in rapid tooling allows a cost reduction of up to 70% in tool production.
Manufacturing companies across multiple industries face an increasingly dynamic and unpredictable environment. This development can be seen on both the market and supply side. To respond to these challenges, manufacturing companies must implement smart manufacturing systems and become more flexible and agile. The flexibility in operational planning regarding the scheduling and sequencing of customer orders needs to be increased and new structures must be implemented in manufacturing systems’ fundamental design as they constitute much of the operational flexibility available. To this end, smart and more flexible solutions for production planning and control (PPC) are developed. However, scheduling or sequencing is often only considered isolated in a predefined stable environment. Moreover, their orientation on the fundamental logic of the existing IT solutions and their applicability in a dynamic environment is limited. This paper presents a conceptual model for a task-based description logic that can be applied to factory planning, technology planning, and operational control. By using service-oriented architectures, the goal is to generate smart manufacturing systems. The logic is designed to allow for easy and automated maintenance. It is compatible with the existing resource and process allocation logic across operational and strategic factory and production planning.