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Auflistung nach Schlagwort "predictive maintenance"

1 - 3 von 3
  • Konferenzbeitrag
    Mining Industrial Logs for System Level Insights
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Czora, Sebastian; Dix, Marcel; Fromm, Hansjörg; Klöpper, Benjamin; Schmitz, Björn
    Industrial systems are becoming more and more complex and expensive to operate. Companies are making considerable efforts to increase operational efficiency and eliminate unplanned downtime of their equipment. Condition monitoring has been applied to improve equipment availability and reliability. Most of the condition monitoring applications, however, focus on single components, not on entire systems. The objective of this research was to demonstrate that a combination of visual analytics and association rule mining can be successfully used in a condition monitoring context on system level.
  • Textdokument
    Towards Designing a User-centric Decision Support System for Predictive Maintenance in SMEs
    (INFORMATIK 2021, 2021) Kellner, Domenic; Lowin, Maximilian; von Zahn, Moritz; Chen, Johannes
    In manufacturing, small and medium-sized enterprises (SMEs) face global competition. In the field of predictive maintenance (PdM), artificial intelligence (AI) helps to prevent machine failures and has the potential to significantly reduce costs and increase process efficiency. Even though PdM has several benefits, it also entails considerable challenges for SMEs, especially when it comes to user interactions. In this short paper, we harness the design science methodology and discuss several problems regarding user interactions with predictive maintenance applications. We incorporate two different literature streams, namely, predictive maintenance and decision support systems. Finally, we present necessary design requirements, principles, features, and propose a research design to further develop and evaluate a user-centric PdM decision support system. Thereby, we contribute to making AI tangible in SMEs.
  • Textdokument
    Towards Predictive Maintenance as a Service in the Smart Housing Industry
    (INFORMATIK 2021, 2021) Lowin, Maximilian; Mihale-Wilson, Cristina
    Maintenance is a significant cost driver in many industries with tangible assets. Aiming to predict damages before they occur, this paper focuses on predictive maintenance (PdM) for smart buildings and apartments – a multi-billion-dollar market with substantial cost savings potential. Based on stakeholder groups’ heterogeneity within the smart housing industry, PdM cannot be a one-fits-all solution. To be effective, practitioners can enrich PdM with Artificial Intelligence (AI). However, to match very heterogeneous environments and the various needs of the stakeholders, PdM must be modular and flexible. Motivated by the challenges and peculiarities for implementing Predictive Maintenance as a Service (PdMaaS) in the smart housing industry, we provide a concept to support managers to overview and optimize complex PdM needs in complex and heterogeneous environments.