Fraunhofer-Institut für Angewandte Informationstechnik FIT

Filters

Reset filters

Settings
Now showing 1 - 10 of 3970
  • Publication
    Trusting the trust machine: Evaluating trust signals of blockchain applications
    ( 2023)
    Völter, F.
    ;
    Urbach, N.
    ;
    Padget, J.
    Information systems research emphasizes that blockchain requires trust in the technology itself. However, we lack knowledge on the applicability of established trust cues to blockchain technology. Thus, this paper's objective is to empirically evaluate the effectiveness of several established IS trust formation factors on end user trust. We do so by conducting a between-groups experiment. While we can validate the applicability of previous IS trust research for blockchain technology to some extent, we find that trust signals emphasizing the technology's underlying trust-building characteristics are most effective. Hence, we highlight the need for contextualization of trust research on blockchain technology. We provide both researchers and practitioners with insights for building trustworthy blockchain applications that enable trust-less interactions not only in theory but in practice.
  • Publication
    Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones
    ( 2022)
    Bloemen, V.
    ;
    Zelst, S. van
    ;
    Aalst, W. van der
    ;
    Dongen, B. van
    ;
    Pol, J. van de
    Given a process model and an event log, conformance checking aims to relate the two together, e.g. to detect discrepancies between them. For the synchronous product net of the process and a log trace, we can assign different costs to a synchronous move, and a move in the log or model. By computing a path through this (synchronous) product net, whilst minimizing the total cost, we create a so-called optimal alignment - which is considered to be the primary target result for conformance checking. Traditional alignment-based approaches (1) have performance problems for larger logs and models, and (2) do not provide reliable diagnostics for non-conforming behaviour (e.g. bottleneck analysis is based on events that did not happen). This is the reason to explore an alternative approach that maximizes the use of observed events. We also introduce the notion of milestone activities, i.e. unskippable activities, and show how the different approaches relate to each other. We propose a data structure, that can be computed from the process model, which can be used for (1) computing alignments of many log traces that maximize synchronous moves, and (2) as a means for analysing non-conforming behaviour. In our experiments we show the differences of various alignment cost functions. We also show how the performance of constructing alignments with our data structure relates to that of the state-of-the-art techniques.
  • Publication
    A computer science perspective on digital transformation in production
    ( 2022)
    Brauner, Philipp
    ;
    Dalibor, Manuela
    ;
    Jarke, Matthias
    ;
    Kunze, Ike
    ;
    Koren, István
    ;
    Lakemeyer, Gerhard
    ;
    Liebenberg, Martin
    ;
    Michael, Judith
    ;
    Pennekamp, Jan
    ;
    Quix, Christoph
    ;
    Rumpe, Bernhard
    ;
    Aalst, Wil van der
    ;
    Wehrle, Klaus
    ;
    Wortmann, Andreas
    ;
    Ziefle, Martina
    The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production, two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers: Smart human interfaces provide access to information that has been generated by model-integrated AI. Given the large variety of manufacturing data, new data modeling techniques should enable efficient management of Digital Shadows, which is supported by an interconnected infrastructure. Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality.
  • Publication
    The role of domain expertise in trusting and following explainable AI decision support systems
    ( 2022)
    Bayer, S.
    ;
    Gimpel, H.
    ;
    Markgraf, M.
    Although the roots of artificial intelligence (AI) stretch back some years, it currently flourishes in research and practice. However, AI deals with trust issues. One possible solution approach is making AI explain itself to its user, but it is still unclear how an AI can accomplish this in decision-making scenarios. This study focuses on how a user's expertise influences trust in explainable AI (XAI) and how this influences behaviour. To test our theoretical assumptions, we develop an AI-based decision support system (DSS), observe user behaviour in an online experiment, complemented with survey data. The results show that domain-specific expertise negatively affects trust in AI-based DSS. We conclude that the focus on explanations might be overrated for users with low domain-specific expertise, whereas it is vital for users with high expertise. Investigating the influence of expertise on explanations of an AI-based DSS, this study contributes to research on XAI and DSS.
  • Publication
    Conceptualizing and Assessing the Value of Internet of Things Solutions
    ( 2022)
    Baltuttis, D.
    ;
    Häckel, B.
    ;
    Jonas, C.M.
    ;
    Oberländer, A.M.
    ;
    Röglinger, M.
    ;
    Seyfried, J.
    The Internet of Things (IoT) is associated with enormous economic potential. To date, however, actual revenues remain below expectations. This circumstance particularly affects IoT solution providers in industrial contexts where effective value assessment is critical for market success. Since a deeper understanding of how IoT solutions create value is required to address this challenge, we develop a framework and corresponding value levers for assessing the value of IoT solutions along an archetypical yet configurable business-to-business-to-consumer (B2B2C) value chain. Taking the perspective of an IoT solution provider in the industrial context, we evaluate the framework with five such solution providers and apply the value levers for an initial value quantification. Our work extends previous research and furthers knowledge on the business value of IT and IoT. It also supports practitioners in assessing IoT value potential.
  • Publication
    Prioritising smart factory investments - A project portfolio selection approach
    ( 2022)
    Dreyer, S.
    ;
    Egger, A.
    ;
    Püschel, L.
    ;
    Röglinger, M.
    Industry 4.0, which describes the transformation of existing production environments toward smart factories, is implemented in ever more manufacturing companies. Smart factories offer diverse advantages such as high flexibility, dynamic scheduling, as well as accurate fault diagnosis and prediction. Hence, manufacturing companies need support for assessing which projects they should implement to transform their production environment. As no such guidance exists in the literature, we propose a multi-dimensional decision model that accounts for interdependencies among production components, for projects with different performance effects, and for digital capabilities constitutive of smart factories (i.e., real-time ability, interoperability, virtualisation and decentralisation). The decision model schedules smart factory projects over multiple planning periods and assesses project roadmaps in line with objectives that comply with established performance measures and the digital capabilities of smart factories. We evaluate and discuss the decision model in interviews with two factory managers and three researchers with great experience in the smart factory domain. Based on a software prototype, we also successfully applied the decision model at a manufacturing company based on real-world data.
  • Publication
    Deep learning-based automated characterization of crosscut tests for coatings via image segmentation
    ( 2022)
    Zhang, G.
    ;
    Schmitz, C.
    ;
    Fimmers, M.
    ;
    Quix, Christoph
    ;
    Hoseini, S.
    A manual scratch test to measure the scratch resistance of coatings applied to a certain substrate is usually used to test the adhesion of a coating. Despite its significant amount of subjectivity, the crosscut test is widely considered to be the most practical measuring method for adhesion strength with a good reliability. Intelligent software tools help to improve and optimize systems combining chemistry, engineering based on high-throughput formulation screening (HTFS) technologies and machine learning algorithms to open up novel solutions in material sciences. Nevertheless, automated testing often misses the link to quality control by the human eye that is sensitive in spotting and evaluating defects as it is the case in the crosscut test. In this paper, we present a method for the automated and objective characterization of coatings to drive and support Chemistry 4.0 solutions via semantic image segmentation using deep convolutional networks. The algorithm evaluated the adhesion strength based on the images of the crosscuts recognizing the delaminated area and the results were compared with the traditional classification rated by the human expert.
  • Publication
    Non-Intrusive Delay-Based Model Partitioning for Distributed Real-Time Simulation
    ( 2022)
    Bogdanovic, M.
    ;
    Stevic, M.
    ;
    Monti, A.
    The work in this article analyses the impact of time-delays on distributed real-time simulation stability and accuracy with respect to different decoupling points as well as the impact of decoupling point selection on system modes. We perform analysis of the system modes and participation matrix of the system and determine suitable points that negligibly modify the system modes to decouple the original system. From this analysis, a non-intrusive delay-based model partitioning method for distributing real-time simulations that exploits the flexibility in the context of selecting decoupling points is developed.
  • Publication
    Electricity Markets in a Time of Change: A Call to Arms for Business Research
    ( 2022)
    Bichler, M.
    ;
    Buhl, H.U.
    ;
    Knörr, J.
    ;
    Maldonado, F.
    ;
    Schott, P.
    ;
    Waldherr, S.
    ;
    Weibelzahl, M.
    Europe's clean energy transition is imperative to combat climate change and represents an economic opportunity to become independent of fossil fuels. As such, the energy transition has become one of the most important, but also one of the most challenging economic and societal projects today. Electricity systems of the past were characterized by price-inelastic demand and only a small number of large electricity generators. The transition towards intermittent renewable energy sources changes this very paradigm. Future electricity systems will consist of many thousands of electricity generators and consumers that actively participate in markets, offering flexibility to balance variable electricity supply in markets with a high spatial and temporal resolution. These structural changes have ample consequences for market operators, generators, industrial consumers as well as prosumers. While a large body of the literature is devoted to the energy transition in engineering and the natural sciences, it has received relatively little attention in the recent business research literature, even though many of the central challenges for a successful energy transition are at the core of business research. Therefore, we provide an up-to-date overview of key questions in electricity market design and discuss how changes in electricity markets lead to new research challenges in business research disciplines such as accounting, business & information systems engineering, finance, marketing, operations management, operations research, and risk management.
  • Publication
    Welcome
    ( 2022)
    Cauchard, Jessica R.
    ;
    Jarke, Matthias
    ;
    Oliver, Nuria