Dr.-Ing.

Kuhn, Thomas

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Towards the Concept of Trust Assurance Case

2023 , Cioroaica, Emilia , Buhnova, Barbora , Schneider, Daniel , Tomur, Emrah , Sorokos, Ioannis , Kuhn, Thomas

Trust is a fundamental aspect in enabling a smooth adoption of robotic technical innovations in our societies. While Artificial Intelligence (AI) is capable to uplift digital contributions to our societies while protecting environmental resources, its ethical and technical trust dimensions bring significant challenges for a sustainable evolution of robotic systems. Inspired by the safety assurance case, in this paper we introduce the concept of trust assurance case together with the implementation of its ethical and technical principles directed towards assuring a trustworthy sustainable evolution of AI-enabled robotic systems.

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Predictive Simulation within the Process of Building Trust

2022 , Cioroaica, Emilia , Buhnova, B. , Kuhn, Thomas

The emerging dynamic architectures of autonomous digital ecosystems raise new challenges in the process of assuring trust and safety. In particular, the admission of software smart agents into autonomous dynamic ecosystems will become a significant future topic. In this work we propose the concept of predictive simulation, which elevates from the concept of virtual Hardware-in-the-Loop (vHiL) testbed, to support rapid runtime evaluation of software smart agents in autonomous digital ecosystems. Based on this testbed, we introduce a novel strategy for building trust in software components that enter an ecosystem as black boxes without executing their behavior which can be potentially malicious, but by executing corresponding digital twins which are abstract models fed with real-time data.

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Architecture Blueprints to Enable Scalable Vertical Integration of Assets with Digital Twins

2022 , Schnicke, Frank , Haque, Ashfaqul , Kuhn, Thomas , Espen, Daniel , Oliveira Antonino, Pablo

Many Industry 4.0 use cases require the integration of live data, e.g., from sensors and devices. However, the large number of legacy fieldbus protocols and proprietary data formats turns this integration into an effort-consuming task. As the number of digital twins in a factory increases rapidly, data source integration has to scale well. Until now, little guidance is available on how to implement this integration in a scalable and reusable manner for Industry 4.0. To close this gap, we define five architecture blueprints based on our experience in various Industry 4.0 projects. These blueprints detail various integration scenarios differentiated by key attributes like frequency of data consumption and data production. In these architecture blueprints, two core components, the Updater and the Delegator, are identified. By providing and evaluating our open-source implementation of these two components, we show the feasibility of the defined blueprints. Utilizing the provided open-source components and the defined architecture blueprints will benefit practitioners as well as researchers when it comes to data integration with digital twins.

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Datenablage als Grundlage für den digitalen Zwilling eines Bauwerks - Verwaltungsschale BBox

2021 , Braml, Thomas , Wimmer, Johannes , Maack, Stefan , Küttenbaum, Stefan , Kuhn, Thomas , Reingruber, Maximilian , Gordt, Alexander , Hamm, Jürgen

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SEC-Learn: Sensor Edge Cloud for Federated Learning

2022-04-27 , Aichroth, Patrick , Antes, Christoph , Gembaczka, Pierre , Graf, Holger , Johnson, David S. , Jung, Matthias , Kämpfe, Thomas , Kleinberger, Thomas , Köllmer, Thomas , Kuhn, Thomas , Kutter, Christoph , Krüger, Jens , Loroch, Dominik M. , Lukashevich, Hanna , Laleni, Nelli , Zhang, Lei , Leugering, Johannes , Martín Fernández, Rodrigo , Mateu, Loreto , Mojumder, Shaown , Prautsch, Benjamin , Pscheidl, Ferdinand , Roscher, Karsten , Schneickert, Sören , Vanselow, Frank , Wallbott, Paul , Walter, Oliver , Weber, Nico

Due to the slow-down of Moore’s Law and Dennard Scaling, new disruptive computer architectures are mandatory. One such new approach is Neuromorphic Computing, which is inspired by the functionality of the human brain. In this position paper, we present the projected SEC-Learn ecosystem, which combines neuromorphic embedded architectures with Federated Learning in the cloud, and performance with data protection and energy efficiency.

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Towards the Concept of Trust Assurance Case

2022 , Cioroaica, Emilia , Buhnova, Barbora , Schneider, Daniel , Sorokos, Ioannis , Kuhn, Thomas , Tomur, Emrah

Trust is a fundamental aspect in enabling self-adaptation of intelligent systems and in paving the way towards a smooth adoption of technological innovations in our societies. While Artificial Intelligence (AI) is capable to uplift the human contribution to our societies while protecting environmental resources, its ethical and technical trust dimensions bring significant challenges for a sustainable self-adaptive evolution in the domain of safety-critical systems. Inspired from the safety assurance case, in this paper we introduce the concept of trust assurance case together with the implementation of its ethical and technical principles directed towards assuring a trustworthy sustainable evolution of safety-critical AI-controlled systems.

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Bridging Trust in Runtime Open Evaluation Scenarios

2021 , Cioroaica, Emilia , Buhnova, Barbora , Marchetti, Eda , Schneider, Daniel , Kuhn, Thomas

Solutions to specific challenges within software engineering activities can greatly benefit from human creativity. For example, evidence of trust derived from creative virtual evaluation scenarios can support the trust assurance of fast-paced runtime adaptation of intelligent behavior. Following this vision, in this paper, we introduce a methodological and architectural concept that interplays creative and social aspects of gaming into software engineering activities, more precisely into a virtual evaluation of system behavior. A particular trait of the introduced concept is that it reinforces cooperation between technological and social intelligence.

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A Digital Twin-based Approach Performing Integrated Process Planning and Scheduling for Service-based Production

2022 , Müller-Zhang, Zai , Kuhn, Thomas

Nowadays, the automation industry is undergoing many changes, manufactures must react to fast changing market demands and more individual customer requirements. Recept-based, Service-Oriented Architectures enable the efficient adaption of production processes to new operating conditions. However, to ensure production performance, service-oriented production should also be complemented by adequate scheduling approaches to guarantee critical performance factors. We present a Digital Twin-based approach that performs integrated process planning and scheduling for service-based production. For our approach, we have identified a common set of input data required for integrated process planning and scheduling. We use Deep-Q-Network, which is a deep Reinforcement Learning method, to derive near optimal schedules for production conditions described in Digital Twins. If an unforseen event happens during the production, our approach is able to adapt current schedules to the changed operating conditions. The case study shows that our approach is able to derive near optimal schedules for customized products and adapt its currents schedules for new orders with different production goals.

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Architecture Blueprints for the Application of the Industry 4.0 Asset Administration Shell

2022 , Schnicke, Frank , Kuhn, Thomas , Klausmann, Tobias , Grüner, Sten , Porta, Daniel

The digitization of value chains is an ongoing challenge in production. The Asset Administration Shell (AAS) aims to address this issue. Besides standardization activities, there is however little architectural guidance on how to bridge the gap between potential AAS use-cases and realization.In this paper, we describe four AAS related use-cases that we derived from 15 application projects which adopted the AAS into industrial contexts. For each of the four use-cases, we devise an architecture blueprint that documents our experiences when applying the AAS. By utilizing these blueprints, practitioners can benefit from our experiences when implementing the AAS and bridge the gap between use-cases and implementation more easily.

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Enabling SMEs to Industry 4.0 Using the BaSyx Middleware: A Case Study

2021 , Kannoth, Subash , Hermann, Jesko , Damm, Markus , Rübel, Pascal , Rusin, Dimitri , Jacobi, Malte , Mittelsdorf, Björn , Kuhn, Thomas , Antonino, Pablo Oliveira

Industry 4.0 (I4.0) concepts evolve the current industrial processes towards directly connecting shopfloor machines to systems from different layers of the Automation Pyramid, such as Enterprise Resource Planning (ERP) or Manufacturing Execution Systems (MES). Companies introducing I4.0 concepts aim at (i) facilitating changeable production systems in order to quickly react to customer inquiries such that even lot-size one becomes feasible and (ii) having a holistic view of the different parameters of a production process. Enabling these calls for accessing the different systems of the Automation Pyramid, which is hard to achieve in traditional production systems without technical changes consuming time, effort and budget, mainly due to the lack of standardization, heterogeneous protocols, and the lack of proper interfaces among the systems of the Automation Pyramid. This challenge is greater in small and medium-size enterprises (SMEs) due to economic reasons or lack access to personnel with a skill set encompassing all the levels of the Automation Pyramid. I4.0-based concepts are built according to the Service-Oriented Architecture principle to enable peer-to-peer communication of systems from each layer of the Automation Pyramid. The service-oriented middleware architecture Eclipse BaSyx 4.0 implements SOA and other I4.0 concepts such as Digital Twins, and has been instantiated in German companies of different sizes. In this paper, we present two use cases focusing on of adoption of Eclipse BaSyx in two German SMEs and show how this enables the adoption of I4.0 concepts with improved time, effort and budget.

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