Imaging in-stent restenosis: an inexpensive, reliable, and rapid preclinical model.

Preclinical models of restenosis are essential to unravel the pathophysiological processes that lead to in-stent restenosis and to optimize existing and future drug-eluting stents. A variety of antibodies and transgenic and knockout strains are available in rats. Consequently, a model for in-stent restenosis in the rat would be convenient for pathobiological and pathophysiological studies. In this video, we present the full procedure and pit-falls of a rat stent model suitable for high throughput stent research. We will show the surgical procedure of stent deployment, and the assessment of in-stent restenosis using the most elegant technique of OCT (Optical Coherence Tomography). This technique provides high accuracy in assessing plaque CSAs (cross section areas) and correlates well with histological sections, which require special and time consuming embedding and sectioning techniques. OCT imaging further allows longitudinal monitoring of the development of in-stent restenosis within the same animal compared to one-time snapshots using histology

A Comparative Study of Machine Learning Approaches for Anomaly Detection in Industrial Screw Driving Data

This paper investigates the application of Machine Learning (ML) approaches for anomaly detection in time series data from screw driving operations, a pivotal process in manufacturing. Leveraging a novel, open-access real-world dataset, we explore the efficacy of several unsupervised and supervised ML models. Among unsupervised models, DBSCAN demonstrates the best performance with an accuracy of 96.68% and a Macro F1 score of 90.70%. Within the supervised models, the Random Forest classifier excels, achieving an accuracy of 99.02% and a Macro F1 score of 98.36%. These results not only underscore the potential of ML in boosting manufacturing quality and efficiency, but also highlight the challenges in their practical deployment. This research encourages further investigation and refinement of ML techniques for industrial anomaly detection, thereby contributing to the advancement of resilient, efficient, and sustainable manufacturing processes. The entire analysis, comprising the complete dataset as well as the Python-based scripts are made publicly available via a dedicated repository. This commitment to open science aims to support the practical application and future adaptation of our work to support business decisions in quality management and the manufacturing industry

Real time grid congestion management in presence of high penetration of wind energy

With the increased use of wind energy the power generation several Transmission System Operators (TSO) have increasing difficulties for congestion forecasting due to the unpredictable nature of the energy source. This paper proposes to enhance the congestion management using a real time supervisor. This supervisor is developed to perform automatic and dynamic re-dispatching using both wind and conventional generators. In order to reduce the production constraints to the minimum, the real time congestion management is based on an indicator of the efficiency of a re-dispatching on the power flowing in the overloaded line. This approach leads to reduced re-dispatching costs and increased network reliability. The simulation of the supervisor and the test grid is realized using by the EUROSTAG [1]. It is shown that the real-time supervisor allows maximization of renewable production during congestions while ensuring network reliability.Power management ;Power transmission;Energy system management;Wind energy ; Variable speed drive

Optimal network congestion management using wind farms

With the increased use of wind energy for the power generation several TSO have increasing difficulties for congestion forecasting due to the unpredictable nature of the energy source. An actual method used to deal with days-ahead congestion planning is based on an order of disconnection of the generation of the type “last generation installed, first generation limited”. This paper proposes to enhance the congestion management using a real time supervisor. This supervisor is developed to perform automatic and dynamic re-dispatching using both wind and conventional generators. In order to reduce the production constraints to the minimum, the real time congestion management is based on an indicator of the efficiency of a re-dispatching on the power flowing in the overloaded line. This approach leads to reduced re-dispatching costs and increased network reliability. Actual and proposed methods are compared in the paper using Matlab/Simulink simulations of a realistic test grid. It is shown that the real-time supervisor allows maximization of renewable production during congestions while ensuring network reliability.Congestion management; Wind farm; Power Transfer Distribution Factors (PTDF); Power system control; Active power dispatch; Variable speed wind turbines.

Data-driven approach for diagnostic analysis of dynamic bottlenecks in serial manufacturing systems

A variety of established approaches exist for the detection of dynamic bottlenecks. Furthermore, the prediction of bottlenecks is experiencing a growing scientific interest, quantifiable by the increasing number of publications in recent years. Neglected, on the other hand, is the diagnosis of occurring bottlenecks. Detection methods may determine the current location of a bottleneck, while predictive approaches may indicate the location of an upcoming bottleneck. However, mere knowledge of current and future bottlenecks does not enable concrete actions to be taken to avoid the bottlenecks, nor does it open up any immediate advantage for manufacturing companies. Since small and medium-sized companies in particular have limited resources, they cannot implement improvement measures for every bottleneck that occurs. Due to the shifts of dynamic bottlenecks, the selection of the mostsuitable stations in the value stream becomes more difficult. This paper therefore contributes to the neglected field of bottleneck diagnosis. First, we propose two data-driven metrics, relative bottleneck frequency and relative bottleneck severity, which allow a quantitative assessment of the respective bottleneck situations. For validation purposes, we apply these metrics in nine selected scenarios generated using discrete event simulation in a value stream with a serial manufacturing line. Finally, we evaluate and discuss the results.Comment: 11 pages, 9 figures, 1 tabl

Ganzheitliche Produktionssysteme für Logistikdienstleister

Aufgrund hoher Marktdynamik und Wettbewerbsintensität steht die Logistikdienstleistungswirtschaft vor neuartigen Herausforderungen. Kunden fordern verstärkt komplexe Systemleistungen aus einer Hand und eine tiefe, reibungslose Integration der Dienstleistungserstellung in die eigenen Leistungsprozesse. Die Probleme, die von industriellen Auftraggebern beim Outsourcing logistischer Leistungsumfänge beklagt werden, deuten an, dass die Herausforderungen nicht zufriedenstellend bewältigt werden und machen eine Veränderung des bisher angewendeten Systems zur Leistungserstellung notwendig. Logistikunternehmen muss es künftig gelingen, die eigenen Prozesse konsequent an den Anforderungen des Kunden auszurichten. Expertise in der systematischen Unterstützung der Wertschöpfung des Kunden und ein vertieftes Verständnis für die Produktionskultur der Auftraggeber ist dafür eine Voraussetzung. Diese Kultur wird in zahlreichen produzierenden Unternehmen durch die auf das Toyota- Produktionssystem zurückzuführenden Ansätze des Schlanken Denkens geprägt. Dabei bündeln, standardisieren und integrieren Ganzheitliche Produktionssysteme die mit diesen Ansätzen verbundenen Inhalte zu einem aus den Unternehmenszielen abgeleiteten und unternehmensspezifisch zugeschnittenen methodischen Ordnungsrahmen. Aufgrund ihrer Schnittstellenposition kommen Logistikunternehmen zwangsläufig mit den durch die Verschlankungsbemühungen induzierten organisatorischen Veränderungen in Kontakt, vor allem auch deshalb, weil einige dieser Veränderungen starken Einfluss auf den Aktionsraum der Dienstleister – die Logistik – haben. Das Forschungsvorhaben leistet daher einen Beitrag, um die im schlanken Transformationsprozess erreichten Erfolge zahlreicher Unternehmen in der Sachgüterproduktion auch der Logistikdienstleistungswirtschaft zugänglich zu machen. Die Auswirkungen der Verbreitung von schlanken Produktionssystemen in produzierenden Unternehmen auf die Logistikdienstleistungserstellung wurden dazu systematisch analysiert und transparent gemacht. Zudem wurden die Anwendungspotenziale des Ansatzes der Ganzheitlichen Produktionssysteme zur Verankerung standardisierter, schlanker und stabiler Prozesse in Logistikunternehmen untersucht. Die Ergebnisse der Untersuchungen wurden in einen spezifischen Gestaltungsrahmen zur Schaffung derartiger Systeme in der Logistikbranche überführt. Dieser Gestaltungsrahmen ist ein methodischer Ansatz, der interessierte Dienstleister bei der unternehmensspezifischen Konfiguration und Implementierung eines eigenen Ganzheitlichen Produktionssystems oder aber auch lediglich Teilen davon unterstützt. Darüber hinaus liefert er Hinweise zur Erfolgskontrolle des initiierten Veränderungsprozesses. Durch eine zielgruppenorientierte Aufbereitung aller Teilergebnisse des Forschungsvorhabens und deren Integration in einen internetbasierten Anwenderkatalog steht interessierten Logistikunternehmen nunmehr eine Plattform zur Verfügung, die sie zur Auseinandersetzung mit innovativen Trends in der Produktionsorganisation einlädt. Diese Einschätzung wurde auch von beteiligten Kooperationspartnern aus der Logistikdienstleistungswirtschaft geteilt

Cyber Physical Systems for Life Cycle Continuous Technical Documentation of Manufacturing Facilities

AbstractContinuous rising of requirements to create technical documentation results in high effort in terms of time and costs to create a complete and up to date documentation for manufacturers. In case of any technical modifications of machines the technical documentation also has to be updated. In fact these updates are lacking in most cases.In this paper, the authors propose a methodology for a self-organized creation of technical documentation to enable an up to date state throughout the Product Life Cycle. A complete and up to date technical documentation provides benefits to customers as well as suppliers of manufacturing facilities. The new approach is based on integration and communication of all components and modules such as machine tool, transportation and handling technology etc. via “Cyber Physical Systems”