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

2019-05-14
Mathieu Ritou (RoMas, IUT NANTES), Farouk Belkadi (IS3P, ECN), Zakaria Yahouni (LS2N, IUT NANTES), Catherine Da Cunha (IS3P, ECN), Florent Laroche (IS3P, ECN), Benoit Furet (RoMas, IUT NANTES)

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

Abstract (translated by Google)
URL

http://arxiv.org/abs/1905.06413

PDF

http://arxiv.org/pdf/1905.06413


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