A Big Data implementation of the MANTIS reference architecture for predictive maintenance

Author:

Larrinaga Felix1,Fernandez-Anakabe Javier1ORCID,Zugasti Ekhi1,Garitano Iñaki1,Zurutuza Urko1,Olaizola Jon1,Anasagasti Mikel2,Mondragon Mikel2

Affiliation:

1. Electronics and Computer Engineering Department, Mondragon University, Mondragon, Spain

2. Goizper S. Coop, Antzuola, Spain

Abstract

This article presents the implementation of a reference architecture for cyber-physical systems to support condition-based maintenance of industrial assets. It also focuses on describing the data analysis approach to manage predictive maintenance of clutch-brake assets fleet over the previously defined MANTIS reference architecture. Proposals for both the architecture and data analysis implementation support working on Big Data scenarios, due to the usage of related technologies, such as Hadoop Distributed File System, Kafka or Apache Spark. The techniques are (1) root cause analysis powered by attribute-oriented induction clustering and (2) remaining useful life powered by time series forecasting. The work has been conducted in a real use case within the H2020 European project MANTIS.

Funder

ministerio de industria, energía y turismo

electronic components and systems for european leadership

eusko jaurlaritza

MANTIS

European Union’s Horizon 2020

Publisher

SAGE Publications

Subject

Mechanical Engineering,Control and Systems Engineering

Reference18 articles.

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