Abstract: In order to respond quickly to disturbance events and restore production stability, the intelligent matching technology of multi-type perturbation event ontology and workshop production scheduling case ontology were proposed. Firstly, the successful cases of dynamic scheduling in the past were standardized through the introduction of ontology technology, and the successful ontological case libraries and the self-improvement learning mechanism of the case libraries constructed. Then, the problem of the new perturbed production shop scheduling with the success stories of the case database were matched by Case-Based Reasoning (CBR) technology and similarity theory, and perturbation workshop intelligent auxiliary decision actualized based on the similarity degree of the threshold interval, which achieved the purpose of improving the decision-making process timeliness and shortening the decision-making time. Finally, the simulation results show that, compared with the traditional CBR and hybrid-driven scheduling strategy, the case retrieval accuracy of the ontology-CBR method is about 6% higher than that of the traditional CBR, and the decision time is 25 mins faster than that of the hybrid-driven scheduling strategy, so the case retrieval accuracy and response time are effectively improved.

Key words: ontology, case-based reasoning (CBR), production disturbance, dynamic scheduling, intelligent decision