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