IoT Systems for Predictive Maintenance in Industry 4.0

peopleKelly GarcésNicolas Cardozo
access_time2019

In the Industry 4.0 vision, Prognostics and Health Management (PHM) is expected to assist domain experts in the generation of maintenance decisions. PHM relies on the processing of data sensed from the manufacturing plant for inferring the future performance of production systems. The acquisition and management of data brings different challenges such as data integration, heterogeneity, search usability and volume. To be best of authors' knowledge, an information system for sharing maintenance data able to fulfill the aforementioned challenges is not available yet. XRepo is proposed within this paper and faces three of the identified challenges through selected functionality: i) Heterogeneity: stored data is complaint with a standard format that includes the information necessary for performing PHM analysis; ii) Integration: data is uploaded to the repository through files or web services; iii) Search usability: stored data can be filtered by criteria and downloaded. This work is meant to be an effort towards the generation of a common information system for PHM analysis.

Results
library_booksArdila A, Martinez F, Garces K, Barbieri G, Sanchez D, Caielli A, Cattaneo L, Fumagalli L. (2019) Xrepo - Towards an information system for prognostics and health management analysis. International conference on industry 4.0 and smart manufacturing (ISM) Cosenza, Italia