In this chapter we present the realization of a prototype infrastructure aiming at providing a useful framework to collect and elaborate information in a big-data and IoT environment. The work presents a novel approach related to predictive maintenance for automatic packaging machines, dealing with condition monitoring of mechanical components. The knowledge of the state of machinery parts is crucial to trigger dynamic scheduling of their servicing before they are worn out or get corrupted, saving time and money. In this fashion, condition monitoring, also known as incipient fault diagnosis, has a key role in the estimation of components’ condition and their remaining working time.

An Onboard Model-of-signals Approach for Condition Monitoring in Automatic Machines

BARBIERI, MATTEO;Bosso, Alessandro;Conficoni, Christian;Diversi, Roberto;Tilli, Andrea
2018

Abstract

In this chapter we present the realization of a prototype infrastructure aiming at providing a useful framework to collect and elaborate information in a big-data and IoT environment. The work presents a novel approach related to predictive maintenance for automatic packaging machines, dealing with condition monitoring of mechanical components. The knowledge of the state of machinery parts is crucial to trigger dynamic scheduling of their servicing before they are worn out or get corrupted, saving time and money. In this fashion, condition monitoring, also known as incipient fault diagnosis, has a key role in the estimation of components’ condition and their remaining working time.
Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability
263
269
Barbieri, Matteo; Bosso, Alessandro; Conficoni, Christian; Diversi, Roberto; Sartini, Matteo; Tilli, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/670649
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