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An ontological modelling of multi-attribute criticality analysis to guide Prognostics and Health Management program development

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Autonomous Intelligent Systems 2022年第1期2卷 16-31页

作者： Adalberto Polenghi Irene Roda Marco Macchi alessandro pozzetti Department of Management Economics and Industrial EngineeringPolitecnico di MilanoP.zza Leonardo da Vinci 3320133 MilanItaly

Digital technologies are becoming more pervasive and industrial companies are exploiting them to enhance the potentialities related to Prognostics and Health Management(PHM).Indeed,PHM allows to evaluate the health state of the physical assets as well as to predict their future *** be effective in developing PHM programs,the most critical assets should be identified so to direct modelling *** techniques could be adopted to evaluate asset criticality;in industrial practice,criticality analysis is amongst the most *** the advancement of artificial intelligence for data analysis and predictions,the criticality analysis,which is built upon both quantitative and qualitative data,has not been improved *** is the goal of this work to propose an ontological formalisation of a multi-attribute criticality analysis in order to i)fix the semantics behind the terms involved in the analysis,ii)standardize and uniform the way criticality analysis is performed,and iii)take advantage of the reasoning capabilities to automatically evaluate asset criticality and associate a suitable maintenance *** developed ontology,called MOCA,is tested in a food company featuring a global *** application shows that MOCA can accomplish the prefixed goals;specifically,high priority assets towards which direct PHM programs are *** the long run,ontologies could serve as a unique knowledge base that integrate multiple data and information across facilities in a consistent *** such,they will enable advanced analytics to take place,allowing to move towards cognitive Cyber Physical Systems that enhance business performance for companies spread worldwide.

关键词： Criticality analysis Ontology Artificial intelligence Prognostics and Health Management PHM Maintenance

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