Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability of energy grids and requires accurate forecasts of electricity consumption and production at any point in time. Today's Energy Data Management (EDM) systems already provide accurate predictions, but typically employ a very time-consuming and inflexible forecasting process. However, emerging trends such as intra-day trading and an increasing share of renewable energy sources need a higher forecasting efficiency. Additionally, the wide variety of applications in the energy domain pose different requirements with respect to runtime and accuracy and thus, require flexible control of the forecasting process. To solve this issue, we introduce our novel online forecasting process as part of our EDM system called pEDM. The online forecasting process rapidly provides forecasting results and iteratively refines them over time. Thus, we avoid long calculation times and allow applications to adapt the process to their needs. Our evaluation shows that our online forecasting process offers a very efficient and flexible way of providing forecasts to the requesting applications.

Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability and efficiency of energy grids. This balancing task requires accurate forecasts of future electricity consumption and production at any point in time. For this purpose, database systems need to be able to rapidly process forecasting queries and to provide accurate results in short time frames. However, time series from the electricity domain pose the challenge that measurements are constantly appended to the time series. Using a naive maintenance approach for such evolving time series would mean a re-estimation of the employed mathematical forecast model from scratch for each new measurement, which is very time consuming. We speed-up the forecast model maintenance by exploiting the particularities of electricity time series to reuse previously employed forecast models and their parameter combinations. These parameter combinations and information about the context in which they were valid are stored in a repository. We compare the current context with contexts from the repository to retrieve parameter combinations that were valid in similar contexts as starting points for further optimization. An evaluation shows that our approach improves the maintenance process especially for complex models by providing more accurate forecasts in less time than comparable estimation methods.

In standard pneumatics, the available signals for data analytics are very limited. As a rule, no continuous status information is available. Usually only the reaching of the end position is indicated - by means of a digital signal of a proximity sensor. This paper examines whether these limited data can be used to derive usable and useful information for predictive maintenance. Pneumatic clamps in bodyin- white construction were chosen as application example. The paper describes a continuous run to investigate the basic feasibility of predictibility. In the following chapters, possibilities for error classification are discussed. Finally, the implementation of the findings in a field test is described.

Die zunehmende Gewöhnung von Benutzern an neue Interaktionskonzepte und Endgeräte ermöglicht deren Einführung in industriellen Umgebungen. Daraus folgen Anwendungsszena-rien, in denen es, selbst während der Bearbeitung einer einzelnen Arbeitsaufgabe, zu häufigen Änderungen in der Zusammensetzung der verwendeten Geräte kommt. Dies motiviert die Entwicklung migrierbarer Benutzungsschnittstellen (MUI). In diesem Beitrag stellen wir zu-nächst die anerkannte Theorie der MUIs vor, inklusive verschiedener Klassifikationsmerkma-le und spiegeln diese an den Anforderungen der Automatisierungstechnik. Anhand dessen diskutieren wir anschließend zwei Anwendungsszenarien. Die Analyse verwandter Arbeiten zeigt auf, dass existierende Ansätze nur eingeschränkt in diesen Szenarien eingesetzt werden können. Am Ende stellen wir eine Fallstudie vor, die die Anwendbarkeit von MUIs in industriel-len Prozessvisualisierungen demonstriert.:1. Einleitung 2. Migratorische Benutzungsschnittstellen 2.1 Einführung 2.2 Klassifikationsmerkmale 3. Anforderungen industrieller Visualisierungen an ein migratorisches UI 3.1 Anforderungen an Software und Engineering 3.2 Struktur und Funktionalität 3.3 Diskussion 4. Beispielhafte Anwendungsszenarien 5. Fallstudie 5.1 Existierende Prototypen 5.2 Konzeption einer Migrationslösung 6. Zusammenfassung und Ausblick / Due to familiarization of users with modern interaction concepts and devices, they become interesting for industrial environments as well. These devices enable use cases where users change the set of applied devices, even during handling one single task. This fosters the de-sign of migratory user interfaces (MUI) which can be transferred freely between devices, in order to follow according to a user’s device changes. Hence, in this paper the generally ac-cepted theory, including a set of identified classifiers for MUIs, is being analyzed with respect to the demands of the domain of industrial process visualizations. Moreover, we discuss two use cases. Our review of the related work revealed only a limited applicability in those use cases. In order to demonstrate an MUI’s usefulness in industrial process visualizations, we finally present our own case study.:1. Einleitung 2. Migratorische Benutzungsschnittstellen 2.1 Einführung 2.2 Klassifikationsmerkmale 3. Anforderungen industrieller Visualisierungen an ein migratorisches UI 3.1 Anforderungen an Software und Engineering 3.2 Struktur und Funktionalität 3.3 Diskussion 4. Beispielhafte Anwendungsszenarien 5. Fallstudie 5.1 Existierende Prototypen 5.2 Konzeption einer Migrationslösung 6. Zusammenfassung und Ausblick

Anwendungen unter Einsatz von Augmented Reality (AR)-Technologien gewinnen zuneh-mend an Relevanz in diversen industriellen Anwendungen, zum Beispiel für Produktpräsenta-tionen, Ausbildung und Lehre, Engineering, etc. Bei der Entwicklung solcher Anwendungen – im Speziellen von Bedien- und Beobachtungslösungen – müssen verschiedene Normen und Richtlinien beachtet werden, um zu gewährleisten, dass Anforderungen an die Betriebssi-cherheit in der jeweiligen Anlage eingehalten werden. In diesem Beitrag sollen einige Aspekte bezüglich der Anwendbarkeit solcher Richtlinien auf AR Anwendungen untersucht werden. Darüber hinaus werden weitere Aspekte betrachtet, die bei der Einführung von AR Anwen-dungen im großen Maßstab relevant sind, wie etwa die durchgängige Nutzbarkeit von CAD-Anlagenmodellen zur automatischen Erzeugung von AR-Lösungen. Schließlich stellen wir eine Fallstudie einer AR-Anwendung für eine prozesstechnische Kleinversuchsanlage vor.:1. Einleitung 2. Entwicklungsphasen von AR-Anwendungen 3. Betrachtung der UI-Gestaltungsrichtlinien 4. Fallstudie 4.1. Implementierung 4.2. Ergebnisse 5. Evaluation eines durchgängigen Entwurfsprozesses 6. Zusammenfassung und Ausblick 7. Danksagung / Augmented Reality (AR) applications gain more and more relevance in various industrial ap-plications lately, e. g. for product presentations, education, engineering, etc. In the industrial domain, especially in process supervision applications, a number of standards and guidelines have been established to ensure that the design of user interfaces meets the safety require-ments of plants or factories. Hence, we seek an evaluation if these guidelines can be applied to AR applications. Moreover, there are other aspects to consider in case AR solutions shall be applied on a larger scale in industrial applications. Thus, it is being discussed whether CAD plant models can be used to generate AR applications automatically. Finally, in this contribu-tion, we present the first preliminary results of a case study on the application of those stand-ards to a visual AR application for in-field inspection and servicing scenarios.:1. Einleitung 2. Entwicklungsphasen von AR-Anwendungen 3. Betrachtung der UI-Gestaltungsrichtlinien 4. Fallstudie 4.1. Implementierung 4.2. Ergebnisse 5. Evaluation eines durchgängigen Entwurfsprozesses 6. Zusammenfassung und Ausblick 7. Danksagung

Perhaps the most flexible synopsis of a database is a uniform random sample of the data; such samples are widely used to speed up processing of analytic queries and data-mining tasks, enhance query optimization, and facilitate information integration. The ability to bound the maximum size of a sample can be very convenient from a system-design point of view, because the task of memory management is simplified, especially when many samples are maintained simultaneously. In this paper, we study methods for incrementally maintaining a bounded-size uniform random sample of the items in a dataset in the presence of an arbitrary sequence of insertions and deletions. For “stable” datasets whose size remains roughly constant over time, we provide a novel sampling scheme, called “random pairing” (RP), that maintains a bounded-size uniform sample by using newly inserted data items to compensate for previous deletions. The RP algorithm is the first extension of the 45-year-old reservoir sampling algorithm to handle deletions; RP reduces to the “passive” algorithm of Babcock et al. when the insertions and deletions correspond to a moving window over a data stream. Experiments show that, when dataset-size fluctuations over time are not too extreme, RP is the algorithm of choice with respect to speed and sample-size stability. For “growing” datasets, we consider algorithms for periodically resizing a bounded-size random sample upwards. We prove that any such algorithm cannot avoid accessing the base data, and provide a novel resizing algorithm that minimizes the time needed to increase the sample size. We also show how to merge uniform samples from disjoint datasets to obtain a uniform sample of the union of the datasets; the merged sample can be incrementally maintained. Our new RPMerge algorithm extends the HRMerge algorithm of Brown and Haas to effectively deal with deletions, thereby facilitating efficient parallel sampling.

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group 1 | 2: Digital systems Group 3: Novel displacement machines Group 4: Industrial applications Group 5: Components Group 6: Predictive maintenance Group 7: Electro-hydraulic actuators / Der Download des Gesamtbandes wird erst nach der Konferenz ab 15. Oktober 2020 möglich sein.:Group 1 | 2: Digital systems Group 3: Novel displacement machines Group 4: Industrial applications Group 5: Components Group 6: Predictive maintenance Group 7: Electro-hydraulic actuators

In dieser Masterarbeit wird ein digitalisiertes Assistenzsystem, welches weniger erfahrenen Mitarbeitern hilft, Instandhaltungsaufgaben zu verrichten, in einer Laborumgebung implementiert. Aus theoretischen Vorbetrachtungen über den digitalen Wandel, welcher im Bereich der Instandhaltung feststellbar ist, wird die Untersuchungsfrage abgeleitet. Diese Masterarbeit setzt sich das Ziel, herauszufinden, wie Problemlösungprozesse von Instandhaltern mittels industrieller Assistenzsysteme unterstützt werden können. Dabei werden eine App (im Folgenden: Wartungsapp), eine Testumgebung sowie ein Kategoriensystem aufgebaut, um der Untersuchungsfrage nachgehen zu können. Ergebnisse aus einer Arbeitsbeobachtung von Testpersonen in Interaktion mit der Wartungsapp werden in Form von Transkripten und Prozessdarstellungen festgehalten. Die Interpretation der Ergebnisse zeigt auf, dass verschiedene Stellschrauben anzunehmen sind, die über Erfolg oder Misserfolg der kosten- und ressourcensparenden Implementierung eines industriellen Assistenzsystems für die Instandhaltung entscheiden können. Zusammenhänge über Schutzfunktionen, Menüführung und Gestaltung der Benutzeroberfläche werden anschließend erläutert und für eventuelle Folgeprojekte vorbereitet. / In this master thesis a digitalized assistance system, which helps less experienced employees to perform maintenance tasks, is implemented in a test environment. The research question is derived from theoretical considerations about a certain digital change that can be observed in the field of maintenance. This master thesis aims to find out how problem solving processes of maintenance personnel can be supported by industrial assistance systems. An app (in the following: maintenance app), a test environment and a category system are developed to answer the research question. Results from a work observation of test persons in interaction with the maintenance app are recorded in the form of transcripts and process representations. The interpretation of the results shows that there are several factors that can determine the success or failure of an industrial maintenance assistance system. Furthermore protective functions, menu navigation and design of the user interfaces are explained and prepared for possible follow-up projects.

Concrete is the most widely used material in construction and infrastructure, and is often reinforced by steel to improve tensile strength. Despite its enduring popularity, the material’s inherent weaknesses – namely corrosion damage and material fatigue – combined with ageing infrastructure, poses a challenge to both decision-makers and civil engineers to optimise sustainable infrastructure services. This article explores and synthesises the sustainable potential of maintenance and repair methods using concrete and cement-based composite materials. We draw on published case studies where sustainability assessments have been applied within this field. We also included cases that describe themselves as a type of sustainability assessment, but lack the assessment of all dimensions. Our research aims, firstly, to identify what maintenance interventions were assessed by means of sustainability criteria. Second, it explores the basic conceptual understanding which underlies each sustainability assessment. Third, it analyses the many methodological choices made for system boundaries, selection of indicators, or forms of aggregation. We have applied a systematic literature review to develop evidence-based management knowledge; this shows that current sustainability assessments are diverse regarding system boundaries, their scope, levels of detail, and overall quality. Although there is a trend towards more holistic types of assessment, environmental and economic sustainability dominated our sample, with global warming and energy consumed being most often reported. External costs, if included in the assessment, drive the overall economic score, while life cycle sustainability assessment is applied to only three cases. The most critical and challenging issues were shown to be the long-term orientation of maintenance measures and the complexity of undertaking a truly holistic sustainability assessment. To that end, we have stimulated scholarly discussion on further methodological progress to align with the good practices identified in our review, and call for greater application of these methods in the construction industry.

Reducing unscheduled maintenance is important for aircraft operators. There are significant costs if flights must be delayed or cancelled, for example, if spares are not available and have to be shipped across the world. This thesis describes three methods of aircraft health condition monitoring and prediction; one for system monitoring, one for forecasting and one combining the two other methods for a complete monitoring and prediction process. Together, the three methods allow organizations to forecast possible failures. The first two use decision trees for decision-making and genetic optimization to improve the performance of the decision trees and to reduce the need for human interaction. Decision trees have several advantages: the generated code is quickly and easily processed, it can be altered by human experts without much work, it is readable by humans, and it requires few resources for learning and evaluation. The readability and the ability to modify the results are especially important; special knowledge can be gained and errors produced by the automated code generation can be removed. A large number of data sets is needed for meaningful predictions. This thesis uses two data sources: first, data from existing aircraft sensors, and second, sound and vibration data from additionally installed sensors. It draws on methods from the field of big data and machine learning to analyse and prepare the data sets for the prediction process.