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• W3005618456 abstract "The overall performance of real world production systems is heavily influenced by the applied mix of maintenance strategies. The choice is dependent on various factors which need to be understood and investigated in detail. The emerging trend towards AI-based prognostic models bring advantages in model creation but also disadvantages in prediction quality. To accomplish this, we introduce a conceptual model, which serves as a basis for a simulation model. The latter may be used as a testbed for evaluating different combinations of applied maintenance strategies with respect to throughput, availabilities and maintenance resources." @default.
• W3005618456 created "2020-02-24" @default.
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• W3005618456 date "2019-11-01" @default.
• W3005618456 modified "2023-09-25" @default.
• W3005618456 title "A Conceptual Modeling Framework for Evaluating the Performance of Predictive Maintenance for Modern, Real-World Production Systems using Potentials and Risks of Industry 4.0" @default.
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• W3005618456 doi "https://doi.org/10.1109/icsrs48664.2019.8987658" @default.
• W3005618456 hasPublicationYear "2019" @default.
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