Data Mapping and Management Method for Knowledge Mining in the Full Lifecycle of Equipment

The full lifecycle data of complex equipment contains a wealth of knowledge, which can effectively support equipment design, manufacturing, operation and maintenance activities through knowledge mining and services. Complex equipment is characterized by intricate physical structures, extended lifecycles, and interdependent stages. Establishing mapping relationships between multi-source and heterogeneous data throughout the entire lifecycle represent a prerequisite for knowledge mining, and they are pivotal in improving the quality of knowledge extraction. To address this problem, this study proposes a data mapping method for the full lifecycle of equipment based on meta-structure trees and encoding. First, using the equipment’s smallest design units, manufacturing units, and maintenance units as leaf nodes, an equipment metastructure tree is established and uniformly encoded. Next, a data association mapping mechanism based on the meta-structure tree is proposed for each lifecycle stage. Finally, a data management method based on fact constellation is proposed to achieve the associated mapping of complex equipment full lifecycle data and provide support for deep data mining.