Big Data Technology for Resilient Failure Management in Production Systems

Volker Stich (1) , Felix Jordan (1) , Martin Birkmeier (1) , Kerem Oflazgil (1) , Jan Reschke (1) , Anna Diews (1)

1 RWTH - Rheinisch-Westfälische Technische Hochschule Aachen University

Due to a growing complexity within value chains the susceptibility to failures in production processes increases. The research project BigPro explores the applicability of Big Data to realize a pro-active failure management in production systems. The BigPro-platform complements structured production data and unstructured human data to improve failure management. In a novel approach, the aggregated data is analyzed for reoccurring patterns that indicate possible failures of the production system, known from historic failure events. These patterns are linked to failures and respective countermeasures and documented in a catalog. The project results are validated in three industrial use cases.

Mots clés: Failure management; Big data; Complex event processing; Production control; Pattern management

Domaines: Informatique [cs]

Volker Stich, Felix Jordan, Martin Birkmeier, Kerem Oflazgil, Jan Reschke, et al.. Big Data Technology for Resilient Failure Management in Production Systems. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2015, Tokyo, Japan. pp.447-454, ⟨10.1007/978-3-319-22756-6_55⟩. ⟨hal-01417530⟩