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arXiv · 1905.06413

Knowledge-based multi-level aggregation for decision aid in the machining industry

Mathieu Ritou·Farouk Belkadi·Zakaria Yahouni·Catherine Da Cunha·Florent Laroche·Benoit Furet
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Abstract

In the context of Industry 4.0, data management is a key point for decision aid approaches. Large amounts of manufacturing digital data are collected on the shop floor. Their analysis can then require a large amount of computing power. The Big Data issue can be solved by aggregation, generating smart and meaningful data. This paper presents a new knowledge-based multi-level aggregation strategy to support decision making. Manufacturing knowledge is used at each level to design the monitoring criteria or aggregation operators. The proposed approach has been implemented as a demonstrator and successfully applied to a real machining database from the aeronautic industry. Decision Making; Machining; Knowledge based system

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Mathieu Ritou, Farouk Belkadi, Zakaria Yahouni, Catherine Da Cunha, Florent Laroche, Benoit Furet. 2019-05-14. Knowledge-based multi-level aggregation for decision aid in the machining industry. https://doi.org/10.1016/j.cirp.2019.03.009

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