To solve the problems in the turbine blade investment casting mold design process such as long design time, lacking of expert experience and low level of intelligence, KBE (knowledge-based engineering) was introduced in the turbine blade investment casting mold design field, and the key technologies of the system were researched and an intelligent design system was developed. A hybrid reasoning model was prompted in which CBR (case-based reasoning) was applied to conceptual design and RBR(rule-based reasoning) was applied to parts design after research the design process and domain knowledge of aero-engine turbine blade investment casting mold design field. In the conceptual design stage, a retrieval model integrated nearest neighbor approach and knowledge-based retrieval approach was prompted which improve the retrieval efficiency, meanwhile,RBR was used to modify the retrieval result. The practical application results indicate that this system can reuse the expert experience efficiently and heighten the mold design efficiency and quality.
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