With the current digital transformation and the development of complex manufacturing systems, advanced maintenance is proposed to improve the competitiveness of complex products, generating a large amount of heterogeneous maintenance data and information. There is a lack of standardized representations of motion-centred maintenance knowledge which leads to semantic ambiguity and poor intertranslatability. In addition, it causes subjective deviations and human resource investments in related time prediction applications. Therefore, a knowledge reuse method for ontology modelling and the application of maintenance motion state sequences is proposed. First, a framework for reusing maintenance motion state sequence (MMSS) knowledge is established, which is defined as the state sets of time-sequence maintenance motion. Second, maintenance motion state sequence ontology (MMSSO) is constructed to standardize the definition of MMSS, as a supplement to the current maintenance ontologies. Third, an MMSSO application for automatic maintenance time prediction is proposed by incorporating the standardized specifications of MMSSO and improving the MODAPTS method. Finally, using aviation equipment as an example, the rationality and superiority of MMSSO in real applications are verified. MMSSO is a new practice of integrating multi-source information in advanced maintenance. It can also provide predicted time as an iterative reference for industrial practitioners in the digital design stage.

中文翻译：

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本体建模知识重用及维护运动状态序列应用


当前数字化转型和复杂制造系统的发展，为提高复杂产品的竞争力提出了高级维护，产生了大量异构的维护数据和信息。缺乏以运动为中心的维护知识的标准化表示，导致语义模糊和互译性差。此外，还造成相关时间预测应用的主观偏差和人力资源投入。因此，提出了一种用于本体建模和维护运动状态序列应用的知识重用方法。首先，建立了维护运动状态序列（MMSS）知识重用框架，将其定义为时序维护运动的状态集。其次，构建维护运动状态序列本体（MMSSO）来标准化MMSS的定义，作为现有维护本体的补充。第三，通过结合MMSSO的标准化规范并改进MODAPTS方法，提出了一种用于自动维护时间预测的MMSSO应用。最后以航空设备为例，验证了MMSSO在实际应用中的合理性和优越性。 MMSSO是高级维护中集成多源信息的新实践。它还可以提供预测时间，作为工业从业者在数字设计阶段的迭代参考。