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ERP-Systeme
(2021)
As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization.
Since more and more production tasks are enabled by Industry 4.0 techniques, the number of knowledge-intensive production tasks increases as trivial tasks can be automated and only non-trivial tasks demand human-machine interactions. With this, challenges regarding the competence of production workers, the complexity of tasks and stickiness of required knowledge occur [1]. Furthermore, workers experience time pressure which can lead to a decrease in output quality. Cyber-Physical Systems (CPS) have the potential to assist workers in knowledge-intensive work grounded on quantitative insights about knowledge transfer activities [2]. By providing contextual and situational awareness as well as complex classification and selection algorithms, CPS are able to ease knowledge transfer in a way that production time and quality is improved significantly. CPS have only been used for direct production and process optimization, knowledge transfers have only been regarded in assistance systems with little contextual awareness. Embedding production and knowledge transfer optimization thus show potential for further improvements. This contribution outlines the requirements and a framework to design these systems. It accounts for the relevant factors.
Wiederanlauf nach der Krise
(2020)
Jetzt intelligent aus der Krise heraus starten! Der Anlauf von Neuprodukten und der jetzt notwendige Wiederanlauf nach der Corona-Krise haben einige Gemeinsamkeiten: In beiden Fällen muss vorsichtig vorgegangen werden, es muss eine hohe Wandlungsfähigkeit und Anpassungsfähigkeit aufrechterhalten werden, um schnell auf eine Veränderung der Situation reagieren zu können und es werden geeignete Werkzeuge und Prognoseverfahren benötigt, um sich die Auswirkungen von geplanten Schritten vorher verdeutlichen zu können. Das vorliegende Herausgeberwerk wurde zusammengestellt, um Expertenwissen für die Praxis nutzbar zu machen. Die über 30 Aufsätze in diesem Werk dienen dem Ziel, das Thema „Wiederanlauf nach der Krise“ aus allen wichtigen Blickwinkeln zu beleuchten und alle relevanten Branchen zu berücksichtigen. Nach der Darstellung allgemeiner Prinzipien des Wiederanlaufs werden Methoden und Werkzeuge vorgestellt, bevor dann Spezika einzelner Branchen diskutiert werden. Im Vordergrund steht dabei die international vernetzte Automobilindustrie sowie die globalen Lieferketten. Weitere Branchen wie die Elektronikfertigung und die Herstellung von Konsumgütern werden ebenfalls besprochen. Zielgruppe dieses Werkes sind vor allem diejenigen, die jetzt den Wiederanlauf von Produktionssystemen nach der drastischen Reduzierung durch das neuartige Corona-Virus planen, vorbereiten und umsetzen.
A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the transfer of knowledge between any kind of knowledge carriers in business processes with AR techniques can lead to a huge competitive advantage, for instance in manufacturing. This includes the transfer of person-bound knowledge as well as externalized knowledge of physical and virtual objects. The contribution builds on a time-dependent knowledge transfer model and conceptualizes an adaptable, AR-based application. Having the intention to accelerate the speed of knowledge transfers between a manufacturer and an information system, empirical results of an experimentation show the validity of this approach. For the first time, it will be possible to discover how to improve the transfer among knowledge carriers of an organization with knowledge-driven information systems (KDIS). Within an experiment setting, the paper shows how to improve the quantitative effects regarding the quality and amount of time needed for an example manufacturing process realization by an adaptable KDIS.
Fabriksoftware
(2020)
Immer mehr Konzepte versprechen die Digitale Fabrik, die Industrie 4.0-Fabrik, die Smart Factory usw. Allen ist gemeinsam, dass dahinter der erheblich ausgeweitete Einsatz von vernetzter Software steht. Allein der Begriff Fabriksoftware selbst ist noch nicht definiert bzw. gegenüber nahestehenden Begriffen abgegrenzt. Der vorliegende Beitrag stellt dazu einen für Forschung und Praxis tauglichen Ansatz zur Einordnung von Software in Fertigung und Logistik vor.
Accelerating knowledge
(2019)
As knowledge-intensive processes are often carried out in teams and demand for knowledge transfers among various knowledge carriers, any optimization in regard to the acceleration of knowledge transfers obtains a great economic potential. Exemplified with product development projects, knowledge transfers focus on knowledge acquired in former situations and product generations. An adjustment in the manifestation of knowledge transfers in its concrete situation, here called intervention, therefore can directly be connected to the adequate speed optimization of knowledge-intensive process steps. This contribution presents the specification of seven concrete interventions following an intervention template. Further, it describes the design and results of a workshop with experts as a descriptive study. The workshop was used to assess the practical relevance of interventions designed as well as the identification of practical success factors and barriers of their implementation.