Knowledge-driven innovation in industrial maintenance: A neural-enhanced model-based definition framework for lifecycle maintenance process information propagation

Under intensifying global competitive pressures, the digital strategic transformation of enterprises requires industrial information propagation across heterogeneous systems and lifecycle stages. These disparate transmission carriers and heterogeneous implementation mechanisms result in the inconsistent propagation of maintenance process information (MPI) in industrial information flows. These challenges render the structured data and knowledge in MPI, including maintenance activities, resource allocations, procedural instructions, and operational parameters, prone to ineffective dissemination across lifecycle phases and introduce risks of catastrophic operational failure. However, the direct application of current industrial information propagation methods, such as model-based definition (MBD) and intelligent information generation, encounters two obstacles: an incomplete standardization system for MPI definitions and construction and a mismatch between heterogeneous semistructured maintenance texts and the MPI. Therefore, a knowledge-driven neural-enhanced MBD framework for lifecycle MPI propagation is proposed. First, a lifecycle MPI propagation architecture is established to provide subsequent normative guidance. Second, an ontology-driven definition and construction method for MBD-based MPI is specified to address the obstacles posed by incomplete standardization systems. Third, an intelligent generation method for MBD-based MPI is constructed to overcome the obstacles of semantic mismatches. Finally, using aviation equipment as an example, the accuracy of the generated MPI and the feasibility of the innovative framework are verified via comparisons with current neural-enhanced models and results from multiple participants. The framework addresses lifecycle MPI propagation challenges through systematic knowledge formalization and neural-enhanced generation, advancing Industry 5.0’s vision of human-centric, resilient maintenance systems.