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Im Institut für angewandte Forschung (IAF) der FH Offenburg wird derzeit eine Chipkarte entwickelt, mit der Temperaturzeitreihen über längere Zeiträume aufgezeichnet werden können. Die zur Datenerfassung erforderlichen Systemkomponenten sind auf nur einem Halbleiterchip zusammengefaßt, wodurch sich bei großen Produktionsstückzahlen ein sehr niedriger Herstellpreis erzielen läßt. Die 'Thermologger' genannte Chipkarte kann zudem mit Standard-Chipkartenlesern und einer dedizierten Software auf jedem PC konfiguriert, gelesen und ausgewertet werden.
In den Unternehmen der Automobilbranche herrscht ein beträchtlicher Rationalisierungsdruck mit einem daraus folgenden hohen Automatisierungsgrad. Den erheblichen Investitionen in modernste Fertigungstechnologien und Montageanlagen steht zunehmend die Forderung eines Return of Investment mit zweistelligen Prozentsätzen gegenüber. Betriebliche Abläufe und Fertigungsprozesse werden daher sehr detailliert geplant, wobei 'minutiöse' Planungen oftmals nur die Beherrschung komplexer Prozeßabläufe vortäuschen. Ungeplante Einflußfaktoren und Störungen lassen manche Planung schnell zu Makulatur verkommen.
Geschäftsprozeßmodellierung und dynamische Simulationen von Fertigungsprozessen mittels zeitbewerteter Petri-Netze, bieten ausgezeichnete Möglichkeiten, komplexe Zusammenhänge transparenter zu machen und neue Erkenntnisse über die Einflüsse von Störungen oder Qualitätsschwankungen auf die Produkt- und Prozeßqualität zu erhalten. In einem Teilbereich der Produktion der Daimler-Benz AG in Gaggenau wurden Qualitätsstörungen und ihre Wirkungen auf den Fertigungsprozeß von Drehmomentwandlern untersucht. Die im Fertigungsverlauf auftretenden qualitätsbeeinflussenden Störungen wurden in Petri-Netz-Modellen abgebildet und in diversen Szenerien simuliert. Die Auswirkungen auf die Anlagenverfügbarkeit, Durchlaufzeiten, Lagerstrategien und die Kostensituationen wurden verdeutlicht und erste Maßnahmen mit den zugehörigen Voraussetzungen aufgezeigt.
A platform of an electronic capsule is being developed for multi-task medical assistant application. It includes a near field telemetry unit for bidirectional communication system of 115 KHz low carrier frequency for inductive data transmission suited for human body energy transfer. The system triggers an actuator for drug delivery in various time and release forms via wireless external control, it has the ability to record temperature, measure pH of the body (additional sensors), and retrieve data to the outside. It consists of a 32bit processor, memory, external peripheries, and detection facility. The complete system is designed to fit small-size mass medical application with low power consumption, size of 7x25mm. The system is designed, simulated and emulated on FPGA. A final layout of the complete chip design is still under progress.
A new electronic capsule with bidirectional communication system is being developed for multi-task application. The capsule is designed to be a platform for medical assistant application inside the body. The designed telemetry unit is a synchronous bidirectional communication block using continuous phase DQPSK of 115 kHz low carrier frequency for inductive data transmission suited for human body energy transfer. The communication system can assist the electronic pill to trigger an actuator for drug delivery, to record temperature, or to measure pH of the body. It consists additionally to a 32bit processor, memory, external peripheries, and detection facility. The complete system is designed to fit small-size mass medical application with low power consumption, size of 7x25mm. The system is designed, simulated and emulated on FPGA. A final layout of the complete chip design is still under progress.
Remote measurement of the physiology, so-called biotelemetry, is a key technology in the modern veterinary medicine. The usage of wireless implants has less impact on the behavior of animals than manual measurement methods and cause less disturbance than wired devices. But, common biotelemetry still uses proprietary communication and power concepts focused on small systems with one animal. Therefore, the University of Applied Sciences Offenburg is developing a low-cost RFID system called muTrans1, which is able to measure ECG, pressure, temperature, oxygen saturation and activity. The muTrans uses an own RFID sensor transponder and standardized commercial components and combines them to a scalable RFID system able to build-up RFID sensor networks with a nearly unlimited size.
In this paper, a complete passive transponder device has been discussed which is meant to monitor leakage in silicone breast implants. The passive tag operates in the HF frequency range of 13.56MHz using RFID ISO 15693 standard. The complete system consists of the transponder, reader and a PC. This paper focusses on the development of such a state of the art passive RFID transponder to monitor the wellness of the silicone breast implants periodically in order to detect leakage in the same. Keyword: RFID (Radio frequency identification device), EM (Electromagnetic) field, Passive Transponder, Silicone breast implants.
Short-term load forecasting (STLF) has been playing a key role in the electricity sector for several decades, due to the need for aligning energy generation with the demand and the financial risk connected with forecasting errors. Following the top-down approach, forecasts are calculated for aggregated load profiles, meaning the sum of singular loads from consumers belonging to a balancing group. Due to the emerging flexible loads, there is an increasing relevance for STLF of individual factories. These load profiles are typically more stochastic compared to aggregated ones, which imposes new requirements to forecasting methods and tools with a bottom-up approach. The increasing digitalization in industry with enhanced data availability as well as smart metering are enablers for improved load forecasts. There is a need for STLF tools processing live data with a high temporal resolution in the minute range. Furthermore, behin-the-meter (BTM) data from various sources like submetering and production planning data should be integrated in the models. In this case, STLF is becoming a big data problem so that machine learning (ML) methods are required. The research project “GaIN” investigates the improvement of the STLF quality of an energy utility using BTM data and innovative ML models. This paper describes the project scope, proposes a detailed definition for a benchmark and evaluates the readiness of existing STLF methods to fulfil the described requirements as a reviewing paper.
The review highlights that recent STLF investigations focus on ML methods. Especially hybrid models gain more and more importance. ML can outperform classical methods in terms of automation degree and forecasting accuracy. Nevertheless, the potential for improving forecasting accuracy by the use of ML models depends on the underlying data and the types of input variables. The described methods in the analyzed publications only partially fulfil the tool requirements for STLF on company level. There is still a need to develop suitable ML methods to integrate the expanded data base in order to improve load forecasts on company level.
Protecting software from illegal access, intentional modification or reverse engineering is an inherently difficult practical problem involving code obfuscation techniques and real-time cryptographic protection of code. In traditional systems a secure element (the "dongle") is used to protect software. However, this approach suffers from several technical and economical drawbacks such as the dongle being lost or broken.
We present a system that provides such dongles as a cloud service, and more importantly, provides the required cryptographic material to control access to software functionality in real-time.
This system is developed as part of an ongoing nationally funded research project and is now entering a first trial stage with stakeholders from different industrial sectors.
Blockchain frameworks enable the immutable storage of data. A still open practical question is the so called "oracle" problem, i.e. the way how real world data is actually transferred into and out of a blockchain while preserving its integrity. We present a case study that demonstrates how to use an existing industrial strength secure element for cryptographic software protection (Wibu CmDongle / the "dongle") to function as such a hardware-based oracle for the Hyperledger blockchain framework. Our scenario is that of a dentist having leased a 3D printer. This printer is initially supplied with an amount of x printing units. With each print action the local unit counter on the attached dongle is decreased and in parallel a unit counter is maintained in the Hyperledger-based blockchain. Once a threshold is met, the printer will stop working (by means of the cryptographically protected invocation of the local print method). The blockchain is configured in such a way that chaincode is executed to increase the units again automatically (and essentially trigger any payment processes). Once this has happened, the new unit counter value will be passed from the blockchain to the local dongle and thus allow for further execution of print jobs.