A hybrid approach of case- and rule-based reasoning to assembly sequence planning

This paper presents a case-based reasoning (CBR) method in combination with ontology theory to carry out decision making for assembly sequence planning (ASP). Due to the ontology unifying various kinds of assembly sequence-related knowledge from different sources, the CBR approach enables a unified structured representation of previous cases and target cases to achieve integration and sharing of knowledge. Based on the similarity measure of classes and properties in ontology theory, the similarity calculation between target ASP case and previous ASP cases is carried out by considering the connection type, motion-transmission type, and location-support type, and a similarity-based previous cases retrieval algorithm is proposed. The combination of ontology and CBR enables flexible and high-quality assembly sequence decisions under various conditions; the ontology-based rule-based reasoning (RBR) method is also adopted as a supplement to CBR in the assembly sequence construction process. Additionally, a reducer case is used to validate the effectiveness of the proposed method.