A computer-Aided Evaluation Method of Maintenance Operation Space Based on Knowledge Reuse

Industry 5.0 requires the manufacturing industry to realize the human-centric maintenance task for complex industrial tasks. It forces designers to reserve sufficient maintenance operation space during the early digital prototype design phase of the lifecycle, which is difficult to balance digital design for complex system with small space and compact layout. At present, designers conduct virtual simulation and analysis for maintenance operation space based on subjective experience. This digital method relies heavily on subjective expertise and manual iterations, leading to inefficiencies and inconsistent outcomes, which caused by the lack of visual model representation of subjective experiences and the absence of intelligent computer-aided technologies. Hence, a study on computer-aided evaluation of maintenance operation space based on knowledge reuse is proposed. First, an Applied Ontology for Maintenance Operation Space Evaluation (AOMOSE) for common structural components and activities are constructed. Second, an AOMOSE application which combines computer-aided and natural semantic processing technology is proposed to achieve four-step rapid analysis, including value matching, position obtaining, model import and positioning, and model interference detection. A case study on an aircraft APU starter-generator demonstrates this knowledge reuse method's effectiveness and feasibility. This method is a fusion of knowledge engineering, maintenance design, natural semantic processing, and computer-aided technologies. It explores the feasibility to achieve advanced maintenance in industry 5.0.

Keywords: Knowledge reuse, Maintenance operation space, Computer-aided technology, Maintenance design.