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- Institut für Strategische Innovation und Technologiemanagement - IST (29)
- Institut für Systemdynamik - ISD (64)
- Institut für Werkstoffsystemtechnik Konstanz - WIK (5)
Ziegelsplittbetone der Nachkriegsjahre und moderne RC-Betone - Nachhaltigkeit an Objektbeispielen
(2018)
Das Bauwesen gehört zu den größten Verbrauchern an natürlichen Ressourcen und Energie in der deutschen Wirtschaft. Das ist in vielen Fällen trotzdem ökologisch und ökonomisch vertretbar, weil die Bauteile und Bauwerke verglichen mit anderen "Produkten" eine deutlich längere technische Lebensdauer haben - im Fall des Betons zwischen ca. 25 und 100 Jahren - und wenn nach dem Rückbau hohe Recyclingquoten erzielt werden. In Bezug auf Einsparmöglichkeiten spielt der Massenbaustoff Beton eine ganz zentrale Rolle. Neben der Einsparung des sehr energieintensiven Zements und der Entwicklung von Substitutionsbindemitteln, stehen auch die Gesteinskörnungen im Fokus, die den größten Anteil am Beton ausmachen. Im Artikel werden auf der Basis eigener Ergebnisse aus einem DBU?geförderten Forschungsprojekt zu RC?Betonen die Nachhaltigkeit von Beton an Objektbeispielen vorgestellt und über den Sachstand zur aktuellen Nutzung von R-Betonen in Deutschland informiert. Der Fokus liegt dabei auf der Wertigkeit mineralischer Baustoffe aus vergleichsweise wenigen, überwiegend natürlichen Komponenten wie beim Beton, dessen Instandsetzungsmöglichkeiten und bessere Voraussetzungen für späteres Recycling gegenüber vielen modernen, kunststoffhaltigen Verbundbaustoffen.
Wirkungen gestalten
(2016)
Durch den Einsatz von mobilen Endgeräten (z.B. Tablets, Smartphones) erschließen sich immer mehr Möglichkeiten, die Ausführung von Geschäftsprozessen zu unterstützen. Beispielsweise können Geschäftsprozessaktivitäten (z.B. Genehmigung eines Angebots) ortsunabhängig bearbeitet werden, wodurch die Durchlaufzeit signifikant reduziert wird. Die Nutzung von mobilen Apps beschränkt sich hierbei meist nur auf die Unterstützung von effizienter und flexibler Interaktion zwischen den verschiedenen ausführenden Rollen. Dieser Artikel beschreibt, wie mobile Apps nicht nur die Ausführung, sondern auch die Optimierung von Geschäftsprozessen unterstützen können. Hierzu werden vordefinierte Qualitätskriterien kontextabhängig während der Ausführung von Aktivitäten erfasst. Die durch traditionelle Methoden erfassten Daten (z.B. Messung von Kennzahlen) werden somit durch in Echtzeit gesammeltes User Feedback ergänzt. Der Ansatz wird am Beispiel einer eigens entwickelten mobilen App demonstriert und evaluiert.
Nowadays established companies use Corporate Entrepreneurship (CE) as a means to create discontinuous innovations. Many companies thereby even implement multiple CE units that typically involve several entrepreneurial activities. This explorative study aimed to identify the reasons why established companies implement multiple CE units concurrently. In conducting a comparative case study with eight companies from different industries, valuable insights for science and practice were gained. We provide an overview of different 11 reasons for implementing multiple CE units. This shows that the combination of CE units used by companies differs depending on the reason. It further allowed to derive general approaches of established companies to the implementation of CE units. Last, we identify the concept of co-specialization to be a central driver explaining the creation of the need to set up multiple units. We conclude by indicating implications and subjects for future research.
The cornerstone of cognitive systems is environment awareness which enables agile and adaptive use of channel resources. Whitespace prediction based on learning the statistics of the wireless traffic has proven to be a powerful tool to achieve such awareness. In this paper, we propose a novel Hidden Markov Model (HMM) based spectrum learning and prediction approach which accurately estimates the exact length of the whitespace in WiFi channels within the shared industrial scientific medical ISM) bands. We show that extending the number of hidden states and formulating the prediction problem as a maximum likelihood (ML) classification leads to a substantial increase in the prediction horizon compared to classical approaches that predict the immediate (short-term) future. We verify the proposed algorithm through simulations which utilize a model for WiFi traffic based on extensive measurement campaigns.
Digital bedruckte Oberflächen müssen strengen funktionalen und ästhetischen Anforderungen genügen. Diese Eigenschaften werden im Rahmen der Qualitätsprüfung kontrolliert. Hierbei wirken sich Oberflächendefekte oftmals erst dann aus, wenn diese auch vom Menschen wahrgenommen werden. Aufgrund der hohen Produktionsgeschwindigkeit kann eine solche Bewertung der Sichtbarkeit von Defekten bisher nur außerhalb des Produktionsflusses durch manuelle - subjektiv geprägte - Inspektion erfolgen. Ziel des Projektes ist (1) die Modellierung von Texturen in einer Form, die an das menschliche visuelle System angepasst ist und (2) die automatisierte Beurteilung der Wahrnehmung von Texturfehlern. Im Rahmen des Projekts wurde ein prototypisches System zur Inline-Erfassung von texturierten Oberflächen entwickelt. Auf Basis von realen Aufnahmen industriell produzierter Holzdekore wurde eine repräsentative Texturdatenbank erstellt. Gezeigt werden erste Resultate im Bereich der Defektdetektion auf Basis von statistischen Merkmalen. Diese Ergebnisse dienen als Grundlage für die spätere wahrnehmungsorientierte Bewertung. Letztlich sollen die im Rahmen des Projekts erlangten Ergebnisse in einen prototypischen Aufbau zur Inspektion von digital bedruckten Dekoren einfließen.
Die vorausschauende Instandhaltung (engl. Predictive Maintenance) gewinnt für die produzierende Industrie weltweit an Bedeutung, da Produktionsmodernisierungen im Rahmen der Industrie 4.0 sowie die zunehmende Verwendung von heterogenen Sensoreinheiten die Instandhaltungsplanung immer komplexer gestalten. Darüber hinaus ist das Service-Kontingent, welches ein Maschinenbauer seinen Kunden im Bereich der Instandhaltung anbieten kann, durch die Ressource Mensch stark limitiert und nur ortsgebunden einsetzbar. Durch herkömmliche Instandhaltungsprozesse entstehen somit oft hohe Kosten, sowohl für den Maschinenbauer als auch für den Anwender. Dieser Beitrag gibt einen Einblick in aktuelle Forschungen der Sybit GmbH in direkter Zusammenarbeit mit der HTWG Konstanz und renommierten Maschinenbau-Unternehmen. Gemeinsames Ziel ist es, vorhandene Instandhaltungsprozesse durch die Verwendung von Augmented Reality (AR) und weiterführenden Technologien zu unterstützen. Hierbei wird ein Stufenplan erarbeitet und vorgestellt, in dem die notwendigen Erweiterungen auf dem Weg von der Implementierung eines Pilotprojekts bis hin zur vollwertigen Industrie-4.0-Anwendung diskutiert werden. Abschließend wird die plausible Erweiterbarkeit der vorgestellten Entwicklungen erörtert und die Übertragbarkeit der Ergebnisse auf andere Domänen vorgestellt.
Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition
(2018)
Deep learning is a field of machine learning that has been the focus of active research and successful applications in recent years. Offline handwriting recognition is one of the research fields and applications were deep neural networks have shown high accuracy. Deep learning models and their training pipeline show a large amount of hyper-parameters in their data selection, transformation, network topology and training process that are sometimes interdependent. This increases the overall difficulty and time necessary for building and training a model for a specific data set and task at hand. This work proposes a novel visualization-assisted workflow that guides the model developer through the hyper-parameter search in order to identify relevant parameters and modify them in a meaningful way. This decreases the overall time necessary for building and training a model. The contributions of this work are a workflow for hyper-parameter search in offline handwriting recognition and a heat map based visualization technique for deep neural networks in multi-line offline handwriting recognition. This work applies to offline handwriting recognition, but the general workflow can possibly be adapted to other tasks as well.
Motion estimation is an essential element for autonomous vessels. It is used e.g. for lidar motion compensation as well as mapping and detection tasks in a maritime environment. Because the use of gyroscopes is not reliable and a high performance inertial measurement unit is quite expensive, we present an approach for visual pitch and roll estimation that utilizes a convolutional neural network for water segmentation, a stereo system for reconstruction and simple geometry to estimate pitch and roll. The algorithm is validated on a novel, publicly available dataset recorded at Lake Constance. Our experiments show that the pitch and roll estimator provides accurate results in comparison to an Xsens IMU sensor. We can further improve the pitch and roll estimation by sensor fusion with a gyroscope. The algorithm is available in its implementation as a ROS node.
When mobile devices at the network edge want to communicate with each other, they too often depend on the availability of faraway resources. For direct communication, feasible user-friendly service discovery is essential. DNS Service Discovery over Multicast DNS (DNS-SD/mDNS) is widely used for configurationless service discovery in local networks, due inno small part to the fact that it is based on the well establishedDNS, and efficient in small networks. In our research, we enhance DNS-SD/mDNS providing versatility, user control, efficiency, and privacy, while maintaining the deployment simplicity and backward compatibility. These enhancements are necessary to make it a solid, flexible foundationfor device communication in the edge of the Internet. In this paper, we focus on providing multi-link capabilities and scalable scopes for DNS-SD while being mindful of both user-friendliness and efficiency. We propose DNS-SD over StatelessDNS (DNS-SD/sDNS), a solution that allows configurationless service discovery in arbitrary self-named scopes - largely independentof the physical network layout - by leveraging ourStateless DNS technique and the Raft consensus algorithm.
Konventionelle, von Dieselmotoren angetriebene Radlader beeinträchtigen die Lebensqualität der Menschen in ihrer unmittelbaren Umgebung mit Lärm- und Schadstoffemissionen. Das vom BMBF geförderte Forschungsvorhaben "Emissionsarmer Elektroradlader" verfolgt das Ziel, die lokalen Emissionen von Radladern deutlich herabzusetzen und die Effizienz des Fahrzeugs zu steigern. Im Rahmen des Vorhabens wurde ein konventioneller Radlader auf elektrische Antriebe umgerüstet. Als Energiespeicher dient eine LiFeYPO4-Batterie, die für eine Betriebsdauer von vier Stunden ausgelegt ist. In ersten praktischen Untersuchungen wurde die Energiebilanz des Emissionsarmen Elektro-Radladers mit der des konventionellen Serienfahrzeugs verglichen. Dazu wurde ein modifizierter Y-Arbeitszyklus entworfen, der sich an den üblichen Arbeitsaufgaben des Radladers orientiert und sich durch eine hohe Reproduzierbarkeit auszeichnet. Für die vollständige Bewertung wird die komplette Kette der Energieumwandlung betrachtet, beginnend mit der Energie im Kraftstoff bzw. der dem Stromnetz entnommenen Energie, bis zur mechanischen Arbeit, die das Gerät verrichtet. Daraus lassen sich Rückschlüsse auf die unterschiedlichen CO2-Emissionen beider Fahrzeuge ableiten.
Ballistocardiography (BCG) can be used to monitor heart rate activity. Besides, the accelerometer should have high sensitivity and minimal internal noise; a low-cost approach was taken into consideration. Several measurements have been executed to determine the optimal positioning of a sensor under the mattress to obtain a signal strong enough for further analysis. A prototype for an unobtrusive accelerometer-based measurement system has been developed and tested in a conventional bed without any specific extras. The influence of the human sleep position for the output accelerometer data was tested. The obtained results indicate the potential to capture BCG signals using accelerometers. The measurement system can detect heart rate in an unobtrusive form in the home environment.
This article describes a research project that aims at investigating individual entrepreneurial founders concerning their shift tendencies of decision-making logics - especially during the respective phases of the venture creating process. Prior studies found that team founders show a hybrid perspective on strategic decision-making. They not only combine causation (planning-based) and effectuation (flexible) logics but also show logic shifts and also re-shifts over time. Due to the fact, that founders' social identity shapes early structuring processes, this article describes the necessity of elimination of in-group influences of multi-founding ventures and focus on individuals in order to make specific assessments on logic shifts and re-shifts. Based on an extensive literature review, a pre-selection-test and a qualitative case study design from the empirical body of the paper. Insofar, this study applies a qualitative design of a process research approach to investigate shifts of decision-making logics of individual founders in new venture creation over time.
Corporate Entrepreneurship (CE) has now evolved into an imperative innovation practice of established companies. Despite organizational design models for CE activities and companies' frequent initiation of new activities, effectively managing them remains a challenging endeavor which results in disappointment about the outcomes of CE and its early termination. We assume specific types of goals for CE as one element of this unresolved management issue. While both practice and literature address goals in different contexts, no uniform picture has emerged so far. Although goals are commonly used to categorize CE activities, they seldomly seem to be the core subject of investigation. Based on this preliminary analysis and consolidation, we put the goals of CE in focus. In a systematic literature review, we reveal aspects of goals to unmask the different types of goals and their underlying dimensions and characteristics. Our review contributes to a better understanding of goals by (1) organizing relevant literature on goals of CE in a specific classification process, (2) describing dimensions and attributes for a systematic classification of CE goals; and (3) providing a framework showing differences of goals for the CE context. We conclude with a discussion and hints for future research paths.
Ulrich Finsterwalder
(2016)
Putze und Fugenmoertel, insbesondere in Sichtmauerwerken uebernehmen wesentliche technische, bauphysikalische und aesthetische Aufgaben fuer die Fassade und tragen massgeblich zum Erhalt der historischen Bausubstanz bei. Dabei sind an Denkmalen haeufig Befunde historischer Putze und Fugenmoertel sowie Verarbeitungsweisen und Handwerkstechniken vorhanden, die heute nicht mehr gebraeuchlich sind und beherrscht werden. Deshalb kommt ihrer Erhaltung besondere Bedeutung zu. Als aeusserster 'Angriffspunkt' der Gebaeudehuelle sind die Putze und Fugenmoertel der Witterung und zum Teil chemischen, biologischen und mechanischen Belastungen frei ausgesetzt und werden in Spritzwasserbereichen auch durch Tausalze beansprucht. Die dadurch sowie durch Alterung und Ermuedung entstehenden Schaeden werden beschrieben und Moeglichkeiten fuer die Erhaltung und Instandsetzung der Putze aufgezeigt.
Low-Code Development Platforms (LCDPs) enable non-information technology (IT) personnel to develop applications and workflows independently of the IT department. Consequently, these digital platforms help to overcome the growing need for software development. However, science and practice warn of several barriers that slow down or hinder the usage of LCDPs. This publication scientifically identifies, analyzes, and discusses challenges during implementation and application of LCDPs from both perspectives in a holistic manner. Therefore, we conduct an exploratory study (data from scientific literature, expert interviews, and practical studies) and assign the challenges to the socio-technical system model. The results show that the scientific and practical communities recognize common challenges (especially knowledge transfer) but also perceive differences related to technological (science) and social (practice) aspects. This paper proposes future research directions for academia, such as governance, culture change, and value evaluation of LCDPs. Additionally, practitioners can prepare for possible challenges when using LCPDs.
TU Darmstadt HUMVIB-Bridge
(2016)
The simulation of the human-induced vibrations of lightweight footbridges is in general a complex problem where the dynamics of the pedestrian system meets the structural dynamics of the bridge. However, standard methods for numerical analysis of pedestrian bridges deal with this issue by using simplified approaches. The structure is mostly represented either by discretised multi mass systems or through a formulation in modal coordinates, while the excitation is typically described by a moving load.
Positive effects of the interaction between the two systems (pedestrian and structure) are usually completely neglected. This paper, which is partially
extracted from an actual research report of the Institute of Structural Mechanics and Design (TU Darmstadt), presents an experimental set-up developed for investigations of the human-structure interaction (HSI), as well as results of the preliminary investigations carried out in the same context.
This paper summarizes the trends in metallization and interconnection technology in the eyes of the participants of the 8th Metallization and Interconnection Workshop. Participants were asked in a questionnaire to share their view on the future development of metallization technology, the kind of metal used for front side metallization and the future development of interconnection technology. The continuous improvement of the screen-printing technology is reflected in the high expected percentage share decreasing from 88% in three years to still 70% in ten years. The dominating front side metal in the view of the participants will be silver with an expected percentage share of nearly 70% in 2029. Regarding interconnection technologies, the experts of the workshop expect new technologies to gain significant technology shares faster. Whereas in three years soldering on busbars is expected to dominate with a percentage share of 71% it will drop in ten years to 35% in the eyes of the participants. Multiwire and shingling technologies are seen to have the highest potential with expected percentage shares of 33% (multiwire) and 16% (shingling) in ten years.
The trajectory tracking problem for a real-scaled fully-actuated surface vessel is addressed in this paper. A nonlinear model predictive control (NMPC) scheme was designed to track a reference trajectory, considering state and input constraints, and environmental disturbances, which were assumed to be constant over the prediction horizon. The controller was tested by performing docking maneuvers using the real-scaled research vessel from the University of Applied Sciences Konstanz at the Rhine river in Germany. A comparison between the experimental results and the simulated ones was analyzed to validate the NMPC controller.
Trajectory Tracking of a Fully-actuated Surface Vessel using Nonlinear Model Predictive Control
(2021)
The trajectory tracking problem for a fully-actuated real-scaled surface vessel is addressed in this paper. The unknown hydrodynamic and propulsion parameters of the vessel’s dynamic model were identified using an experimental maneuver-based identification process. Then, a nonlinear model predictive control (NMPC) scheme is designed and the controller’s performance is assessed through the variation of NMPC parameters and constraints tightening for tracking a curved trajectory.
This paper presents the integration of a spline based extension model into a probability hypothesis density (PHD) filter for extended targets. Using this filter the position and extension of each object as well as the number of present objects can jointly be estimated. Therefore, the spline extension model and the PHD filter are addressed and merged in a Gaussian mixture (GM) implementation. Simulation results using artificial laser measurements are used to evaluate the performance of the presented filter. Finally, the results are illustrated and discussed.
Virtual measurement models (VMM) can be used to generate artificial measurements and emulate complex sensor models such as Lidar. The input of the VMM is an estimation and the output is the set of measurements this estimation would cause. A Kalman filter with extension estimation based on random matrices is used to filter mean and covariance of the real measurements. If these match the mean and covariance of the artificial measurements, then the given estimation is appropriate. The optimal input of the VMM is found using an adaptation algorithm. In this paper, the VMM approach is expanded for multi-extended object tracking where objects can be occluded and are only partially visible. The occlusion can be compensated if the extension estimation is performed for all objects together. The VMM now receives as input an estimation for the multi-object state and the output are the measurements that this multi-object state would cause.
Corporate entrepreneurship (CE) is experiencing continuously increasing interest from scholars and practitioners. One reason for this seems to be rooted in the organizational structures of established companies, which are cumbersome for implementing organizational agility and for developing radical innovations. In view of the advancing digitalization, however, exactly this is required in order to be successful in the long-term. CE is a promising managerial tool that offers a wide range of options to pursue the creation of new businesses and to support the companies' transformation in order to adapt to changes in the environment. Even though CE offers a broad range of opportunities, the effective management is a challenge. One reason for this is the ambiguity when it comes to the differences between the various CE forms and the objectives that can be achieved by those. This study, which is based on 13 in-depth interviews from eight high-tech companies, contributes to a better understanding of CE by offering a first harmonized set of CE objectives that is suitable to compare and differentiate across the different forms. In addition to that, three CE types, offering a new perspective on how to differentiate CE forms, are identified and give implications for a more effective management.
Realistic traffic modeling plays a key role in efficient Dynamic Spectrum Access (DSA) which is considered as enabler for the employment of wireless technologies in critical industrial automation applications (IAA). The majority of models of spectrum usage are not suitable for this specific use case as they are based on measurement campaigns conducted in urban or controlled laboratory environments. In this work we present a time-domain traffic model for industrial communication in the 2.4 GHz industrial, scientific, medical (ISM) band based on measurements in an industrial automotive production site. As DSA is usually implemented on Software Defined Radios (SDR), our measurement campaign is based on SDR platforms rather than sophisticated spectrum analyzers. We show through the estimation of the Hurst parameter that industrial wireless traffic possesses inherent self-similarity that could be exploited for efficient DSA. We also show that wireless traffic could be modeled as a semi-Markov model with channel on and off durations Log-normally and Pareto distributed, respectively. We finally estimate the parameters of the derived models using Maximum Likelihood estimation.
Nowadays, information technology (IT) is a strategic asset for organizations. As a result, the IT costs are rising and there is a need for transparency about their root causes. Cost drivers as an instrument in IT cost management enable a better transparency and understanding of costs. However, there is a lack of IT cost driver research with a focus on the strategic position of IT within organizations. The goal of this paper is to develop a comprehensive overview of strategic drivers of IT costs. The Delphi study leads to the identification and validation of 17 strategic drivers. Hence, this paper builds a base for cost driver analysis and contributes to a better understanding of the causes of costs. It facilitates future research regarding cost behavior and the business value of IT. Additionally, practitioners gain awareness of levers to influence IT costs and consequences of managerial decisions on their IT spend.
Business units are increasingly able to fuel the transformation that digitalization demands of organizations. Thereby, they implement Shadow IT (SIT) to create flexible and innovative solutions. However, the individual implementation of SIT leads to high complexities and redundancies. Integration suggests itself to meet these challenges but can also eliminate the described benefits. In this emergent research, we develop propositions for a conceptual decision framework, that balances the benefits and drawbacks of an integration of SIT using a literature review as well as a multiple-case study. We thereby integrate the perspective of the overall organization as well as the specific business unit. We then pose six propositions regarding SIT integration that will serve to evaluate our conceptual framework in future research.
Tourist tracking
(2015)
Adjusting the friction response of the wheel-rail interface is a key factor in the mitigation of wear and rollingcontact fatigue (RCF) in rails. The use of top-of-rail (TOR) friction conditioners has the potential to reduce maintenance costs significantly. Unfortunately, conflicting results on the use of commercial TOR conditioners have been presented in the literature. In this work, the performance of commercial TOR conditioners and a laboratory-made formulation were tested, both on the lab scale and in field measurements. Friction results are discussed together with the structural and chemical analysis of the tested materials.
Think BIQ: Gender Differences, Entrepreneurship Support and the Quality of Business Idea Description
(2023)
Entrepreneurship support, its influencing factors and female entrepreneurship are recently discussed topics with great relevance for society and politics. However, research on the subject has been divergent in its results and lacks a focus on the impact of support programs’ characteristics concerning different types of entrepreneurs. Thus, we conduct a fuzzy-set Qualitative Comparative Analysis on entrepreneurship support characteristics aiming to shed light on possible gender differences occurring in respective programs. We investigate the quality of business idea descriptions, as a predecessor for a high-potential business model, operationalized using inter alia causation and effectuation theory and social role theory as possible explanations. In our fuzzy-set Qualitative Comparative Analysis on a sample of 911 Norwegian ventures, we find a variety of differences related to the entrepreneurs’ gender. For instance, that financial support combined with a well described key contribution or careful planning seem to be more important antecedents for female entrepreneurs’ business idea quality than for males. Moreover, it seems a well-described key contribution has a positive effect on the outcome variable in most cases. Another interesting finding concerns the entrepreneurs’ network partners, where we found evident gender differences in our combinations. Female entrepreneurs seemingly benefitted from rather small networks, and males from big networks, although the former possess larger networks in the sample. In conclusion, we find that gender differences in combinations of entrepreneurship support for high business idea quality still occur even in a country like Norway, calling for an adaption of the provided support and environment.