Dr.-Ing.

Kuhn, Thomas

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  • Publication
    Reference Architectures for Industry 4.0
    ( 2023)
    Schnicke, Frank
    ;
    Kuhn, Thomas
    The adoption of Industry 4.0 requires reconsideration of plant software architecture due to the strict layers of the automation pyramid hindering the implementation of central Industry 4.0 use cases like the changeable plant. Thus, plant software architecture has to change and, for example, adopt concepts such as the digital twin. In this chapter, we provide an overview of current challenges of the status quo of software architecture in Industry 4.0 and describe how they are solved by reference architectures. Furthermore, we provide guidance on how to classify use cases and reference architectures of Industry 4.0 according to various reference architecture models.
  • Publication
    Verwaltungsschalenbasierte Datenräume. Möglichkeiten, Herausforderungen und Lösungsansätze auf dem Weg zu datengetrieben resilienten Wertschöpfungsnetzwerken
    ( 2023)
    Adler, Rasmus
    ;
    Kuhn, Thomas
    ;
    Schnicke, Frank
    Der Austausch von Unternehmensdaten ist eine wichtige Grundlage, um fragile Lieferketten in resiliente und nachhaltige Wertschöpfungsnetzwerke zu transformieren. Im Rahmen dieser Transformation werden die Verfügbarkeit von Daten und die Fähigkeit, diese zu nutzen, die lukrativsten Geschäftsmodelle der Zukunft prägen. Intelligente Systeme können die Daten nutzen, um autonome Entscheidungen bezüglich der Wandlung von Produktionssystemen zu treffen oder Empfehlungen zu geben. Damit diese Transformation gelingt, werden für die notwendigen Entwicklungen verwaltungsschalenbasierte Datenräume benötigt.
  • Publication
    Manufacturing-X: Die Branche der Fabrikausrüster
    ( 2023)
    Sauer, Olaf
    ;
    Haller, Marc Leon
    ;
    Wagner-Sardesai, Saskia
    ;
    Henke, Jürgen
    ;
    Schmelting, Jürgen
    ;
    Meyer, Tom
    ;
    Kujath, Marc
    ;
    Seidel, Holger
    ;
    Kuhn, Thomas
    ;
    Schnicke, Frank
    ;
    Harst, Simon
    ;
    Wenzel, Ken
    ;
    ten Hompel, Michael
    ;
    Henke, Michael
    ;
    Clausen, Uwe
    ;
    Ihlenfeldt, Steffen
    Die deutsche Ausrüsterindustrie beliefert weltweit Fabriken mit Produktionslinien, Maschinen, Komponenten, Automatisierungstechnik und produktionsnaher Software. Über viele Jahre waren die Auftragsbücher voll und die Entwicklungs- und Produktionskapazitäten ausgelastet. Die Frage ist: wird das auch in der Zukunft so sein und: wie können die deutschen Ausrüster ihre Wettbewerbsfähigkeit erhalten oder sogar noch verbessern? Welche Rolle spielt dabei die Digitalisierung? Viele Ausrüster haben in den Jahren seit dem Start von „Industrie 4.0“ zaghafte Schritte in die Digitalisierung gemacht, mehr oder weniger erfolgreich; viele proprietäre Lösungen blieben weit hinter den Erwartungen zurück. Entsprechend zurückhaltend sind die Unternehmen nun bei den nächsten Schritten. Damit bleiben sie aber in Bezug auf die Digitalisierung und den mit ihr verbundenen Möglichkeiten für zusätzliche datenbasierte Dienstleistungen rund um Maschinen und Komponenten zurück und verpassen möglicherweise wichtige Innovationschancen. Qualitativ hochwertige Maschinen, Anlagen und Komponenten zu entwickeln, herzustellen und zu liefern wird in Zukunft für den Geschäftserfolg der deutschen Ausrüster nicht mehr ausreichen – sie müssen dringend in datenbasierte Dienste investieren, denn die Kunden von morgen werden diese erwarten. Um die Kräfte bei der Software- und Diensteentwicklung zu bündeln, schlagen die Autoren mehrerer Fraunhofer-Institute die Beteiligung der Ausrüster an industriellen Datenräumen vor: dabei teilen sich die beteiligten Unternehmen die Aufwände zur Entwicklung der ‚Basisdienste‘ und konzentrieren sich vielmehr darauf, Business-Applikationen mit tatsächlichem Kundennutzen zu schaffen. Gleichzeitig gewährleisten Datenräume die Datensouveränität, d.h. die Kontrolle der jeweiligen Dateneigentümer über Daten und deren Nutzung, die sie im Datenraum zur Verfügung stellen, bleibt erhalten. In der hier vorgelegten Studie beschreiben die Autoren zunächst die Branche der Fabrikausrüster und deren Teilbranchen. Basierend auf einer Auswertung aktueller Studien zu Innovationskraft und Digitalisierung der Ausrüsterbranche arbeiten sie heraus, dass es für die Fabrikausrüster höchste Zeit ist, ihr Produktportfolio um digitale Lösungen zu erweitern. Nur so können die Unternehmen den zukünftigen Herausforderungen Stand halten, z.B. Reduzierung der Abhängigkeiten von wenigen Vorleistungslieferanten, verbesserte Resilienz von Lieferketten, Anforderungen an Nachhaltigkeit und Kreislaufwirtschaft oder dem heute schon spürbaren Fachkräftemangel. Aufbauend auf der Faktenlage und den daraus resultierenden Trends formulieren die Autoren dann thesenartig relevante Entwicklungspfade für die Ausrüsterbranche mit konkreten Vorschlägen bis hin zu neuen Möglichkeiten, Ergebnisse aus F&E-Projekten durch gezielten Einsatz digitalen Wissenstransfers für ausrüstende Unternehmen zu nutzen. Mit der hier vorgelegten Studie stellt der Leitmarkt ‚Anlagenund Maschinenbau‘ der Fraunhofer-Gesellschaft unter Beweis, dass die Fraunhofer Institute über ein umfangreiches Angebot für Fabrikausrüster verfügen, um den Weg in die digitale Zukunft der Branche zielgerichtet, innovativ und investitionssicher zu beschreiten.
  • Publication
    A Quality 4.0 Model for architecting industry 4.0 systems
    ( 2022)
    Oliveira Antonino, Pablo
    ;
    Capilla, Rafael
    ;
    Pelliccione, Patrizio
    ;
    Schnicke, Frank
    ;
    Espen, Daniel
    ;
    Kuhn, Thomas
    ;
    Schmid, Klaus
    The increasing importance of automation and smart capabilities for factories and other industrial systems has led to the concept of Industry 4.0 (I4.0). This concept aims at creating systems that improve the vertical and horizontal integration of production through (i) comprehensive and intelligent automation of industrial processes, (ii) informed and decentralized real-time decision making, and (iii) stringent quality requirements that can be monitored at any time. The I4.0 infrastructure, supported in many cases by robots, sensors, and algorithms, demands highly skilled workers able to continuously monitor the quality of both the items to be produced and the underlying production processes. While the first attempts to develop smart factories and enhance the digital transformation of companies are under way, we need adequate methods to support the identification and specification of quality attributes that are relevant to I4.0 systems. Our main contribution is to provide a refined version of the ISO 25010 quality model specifically tailored to those qualities demanded by I4.0 needs. This model aims to provide actionable support for I4.0 software engineers that are concerned with quality issues. We developed our model based on an exhaustive analysis of similar proposals using the design science method as well as expertise from seasoned engineers in the domain. We further evaluate our model by applying it to two important I4.0 reference architectures further clarifying its application.
  • Publication
    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.
  • Publication
    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.
  • Publication
    Continuous engineering for Industry 4.0 architectures and systems
    ( 2022)
    Oliveira Antonino, Pablo
    ;
    Capilla, Rafael
    ;
    Kazman, R.
    ;
    Kuhn, Thomas
    ;
    Schnicke, Frank
    ;
    Treichel, Tagline
    ;
    Bachorek, Adam
    ;
    Müller-Zhang, Zai
    ;
    Salamanca, V.
    Traditionally, the quality of a software or system architecture has been evaluated in the early stages of the development process using architecture quality evaluation methods. Emergent approaches like Industry 4.0 require continuous monitoring of both run-time and development-time quality properties, in contrast to traditional systems where quality is evaluated at specific milestones using techniques such as project reviews. Considering the dynamics and minimum down-time imposed by the industrial production domain, it must also be ensured that Industry 4.0 system evaluations are continuously performed with high confidence and with as much automation as possible, using simulations, for instance. In this regard, there is a need to develop new methods for continuously monitoring and evaluating the quality properties of software-based systems for Industry 4.0, which must be supported by automated quality evaluation techniques. In this research we analyze traditional architecture evaluation methods and Industry 4.0 scenarios, and propose an approach based on Digital Twins and simulations to continuously evaluate runtime quality aspects of the architecture and systems of industrial production plants. The evaluation is based on the instantiation of our approach for a concrete demand of an automation plant in the automotive domain.
  • Publication
    Industry 4.0 reference architectures: State of the art and future trends
    ( 2021)
    Nakagawa, Elisa Yumi
    ;
    Antonino, Pablo Oliveira
    ;
    Schnicke, Frank
    ;
    Capilla, Rafael
    ;
    Kuhn, Thomas
    ;
    Liggesmeyer, Peter
    Industry 4.0 has led to a dramatic shift in manufacturing processes, which must be accomplished by interacting end-to-end industrial systems. While Industry 4.0 is still a big challenge for many manufacturing companies, reference architectures have been increasingly adopted in different domains to guide engineers on how their systems should interoperate and be structured. Companies have made different experiences with reference architectures for Industry 4.0. However, depending on the use cases addressed, a reference architecture may be more or less suited to support the transformation of a particular company. Besides, a complete understanding of existing representative architectures does not exist. The main goal of this work is to review existing reference architectures for Industry 4.0 and analyze them concerning their suitability for supporting Industry 4.0 processes and solutions. For this, we systematically researched these architectures and thoroughly analyzed and characterized them. We also address their use and technologies/tools that could support their implementation. As a result, we found that existing architectures still have a long way to go; hence, we present the most urgent steps for the near future. We conclude that the Industry 4.0 community is right in investing in reference architectures considering the future of Industry 4.0.
  • Publication
    Continuous Systems and Software Engineering for Industry 4.0: A disruptive view
    ( 2021)
    Nakagawa, Elisa Yumi
    ;
    Antonino, Pablo Oliveira
    ;
    Schnicke, Frank
    ;
    Kuhn, Thomas
    ;
    Liggesmeyer, Peter
    Context: Industry 4.0 has substantially changed the manufacturing processes, leading to smart factories with full digitalization, intelligence, and dynamic production. The need for rigorous and continuous development of highly networked software-intensive Industry 4.0 systems entails great challenges. Hence, Industry 4.0 requires new ways to develop, operate, and evolve these systems accordingly. Objective: We introduce the view of Continuous Systems and Software Engineering for Industry 4.0 (CSSE I4.0). Method: Based on our research and industrial projects, we propose this novel view and its core elements, including continuous twinning, which is also introduced first in this paper. We also discuss the existing industrial engagement and research that could leverage this view for practical application. Results: There are still several open issues, so we highlight the most urgent perspectives for future work. Conclusions: A disruptive view on how to engineer Industry 4.0 systems must be established to pave the way for the realization of the fourth industrial revolution.
  • Publication
    Architecture Blueprint Enabling Distributed Digital Twins
    ( 2021)
    Schnicke, Frank
    ;
    Espen, Daniel
    ;
    Antonino, Pablo Oliveira
    ;
    Kuhn, Thomas
    Mass production today is optimized for large lot sizes, and changes to industrial production lines are effort-intense, time-consuming, and costly. The fourth industrial revolution, Industry 4.0 (I4.0), aims at reducing the effort needed for changes in industrial production lines. The key benefits of next-generation manufacturing systems are less downtimes and the production of small lot sizes down to lot size 1. I4.0 does not introduce a silver bullet technology, but requires a transformation of the system architecture of production systems. In the literature, however, there systematic guidance for designing manufacturing systems that address central I4.0 use cases like plug'n'produce and end-to-end communication is still missing, as are details on the infrastructure needed to enable I4.0 technologies such as Digital Twins. To contribute to filling this gap, this paper presents (i) a Digital Twin architecture blueprint driven by central I4.0 use cases and (ii) a prototypical open-source implementation of the architecture using the concept of the Asset Administration Shell.