Knowledge-based disturbance propagation in manufacturing systems: A case study

Production systems are subject to various kinds of disturbances, which may alter pre-set organization and generate significant risks. Disturbances and risks need to be controlled in order not to degrade expected performance. Controlling disturbances and risks requires and generates a huge quantity of knowledge. In literature, only a few approaches focus on structuring disturbance related knowledge in order to facilitate their use and reuse. In this paper, we first classify disturbance related knowledge. Then, we detail the design of an ontology able to structure this knowledge. Finally, we conceive a set of rules in order to use structured knowledge to propagate disruptions and determine their direct (certain) consequences and indirect (probable) risks.