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- W4320924169 abstract "Total Productive Maintenance (TPM) is one of the methodologies widely used to increase the availability of existing facilities reducing downtimes, stops, and defects, by improving manufacturing methods, usage, and maintenance equipment. Considering the large amount of data currently available thanks to the Industry 4.0 (I4.0) digitization processes, extending the analysis performed in TPM with the support of new techniques and tools is interesting. More in detail, in this work, Association Rule Mining (ARM) is used to identify the hidden relationships between different failure events, allowing their monitoring and prediction and improving the continuity and resilience of the production flow. The final aim pursued by the proposed approach is the development of a maintenance strategy in order to improve the Overall Equipment Effectiveness (OEE) of the selected process. An example case based on real data from an automotive company is used to present the approach and extract proper knowledge from its implementation." @default.
- W4320924169 created "2023-02-16" @default.
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- W4320924169 date "2023-01-01" @default.
- W4320924169 modified "2023-09-26" @default.
- W4320924169 title "A Preliminary Implementation of Data-Driven TPM: A Real Case Study" @default.
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- W4320924169 doi "https://doi.org/10.1007/978-3-031-25448-2_2" @default.
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