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Parametric anti-resonance is a phenomenon that occurs in systems with at least two degrees of freedom; this can be achieved by periodically exciting some parameters of the system. The effect of this properly tuned periodicity is to increase the dissipation in the system, which leads to a raising in the effective damping of vibrations. This contribution presents the design of an open-loop control to reduce the settling time using the anti-resonance concept. The control signal consists of a quasi-periodic signal capable of transferring the system’s oscillations from one mode to another mode of the system. The general averaging technique is used to characterize the dynamics, particularly the so-called slow dynamics of motion. With this analysis, the control signal is designed for the potential application of a microelectromechanical sensor arrangement; for this specific example, up to 96.8% reduction of settling time is achieved.
By a simple femtosecond laser process, we fabricated metal-oxide/gold composite films for electrical and optical gas sensors. We designed a dripple wavelength AWG-spectrometer, matched to the plasma absorption wavelength region of the composite films. H2/CO absorptions fit well with the AWG design for multi gas detection sensor arrays
The main aims of this work are the validation of the developed process of gluing a single-mode optical fiber array with a photonic chip and the selection of a more suitable adhesive from the two adhesives being compared. An active alignment system was used for adjusting the two optical fiber arrays to a photonics chip. The gluing was done by two compared UV curable adhesives applied in the optical path. The insertion losses of glued coupling were measured and investigated at two discrete wavelengths 1310 nm and 1550 nm during temperature testing in the climatic chamber according to Telcordia GR_1209_Corei04 [3]. The measurement, investigation, and comparison of insertion losses of the glued coupling at the spectral band from 1530 nm to 1570 nm were done immediately after gluing process and after three temperature cycles in the climatic chamber with one month delay.
In 2021, a prominent Austria dairy producer suffered from an IT attack and was completely paralysed. Without clearly defined mitigation measures in place, major disruptions were caused alongside the whole supply chain, including logistics service providers, governmental food safety bodies, as well as retailers (i.e., supermarkets and convenience stores). In this paper, we ask the question how digitisation and digital transformation impact IT security, especially when considering the complex company ecosystems of food production and food supply chains in Austria. The problem statement stems from a gap in knowledge of key differences in approaches towards IT security, resilience, risk management and especially business interfaces between food suppliers, supermarkets, distributors, logistics and other service providers. In order to answer related research questions, firstly, the authors conduct literature research, and highlight common guidelines and standardisation as well as look at state-based recommendations for critical infrastructure. In a second step, the paper describes a quantitative and qualitative survey with Austrian food companies (producers and retailers) which is described in detail in the paper. A description of recommended measures for the industry, further steps, as well as an outlook conclude the paper.
Im vorliegenden Paper wird ein Vergleich zwischen Produktions-und Simulationsdaten präsentiert welches im Rahmen einer größeren Initiative zur Verwendung von Shopfloor Daten bei einem Projektpartner in der Automobilindustrie umgesetzt wurde. In diesem Projekt wurden die Daten die während der Füllbildsimulation entstehen mit den Daten aus der finalen Werkzeugabnahme verglichen um zu analysieren, wie genau diese miteinander über einstimmen. Je besser die Simulation ist, desto schneller kann der gesamte Werkzeugentwicklungsprozess abgewickelt werden, welcher als Kernprozess massives Einsparungspotenzial und damit Wettbewerbsvorteil mit sich bringt.
The usage of data gathered for Industry 4.0 and smart factory scenarios continues to be a problem for companies of all sizes. This is often the case because they aim to start with complicated and time-intensive Machine Learning scenarios. This work evaluates the Process Capability Analysis (PCA) as a pragmatic, easy and quick way of leveraging the gathered machine data from the production process. The area of application considered is injection molding. After describing all the required domain knowledge, the paper presents an approach for a continuous analysis of all parts produced. Applying PCA results in multiple key performance indicators that allow for fast and comprehensible process monitoring. The corresponding visualizations provide the quality department with a tool to efficiently choose where and when quality checks need to be performed. The presented case study indicates the benefit of analyzing whole process data instead of considering only selected production samples. The use of machine data enables additional insights to be drawn about process stability and the associated product quality.
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(2023)