Post-prognostics decision in Cyber-Physical Systems
This work addresses predictive maintenance for distributed industrial systems, but it appears incremental as it adapts existing PHM concepts to CPS and cloud technologies without claiming major breakthroughs.
The paper tackles the challenge of implementing Prognostics and Health Management (PHM) for predictive maintenance in distributed industrial assets by proposing a PHM solution based on Cyber-Physical Systems (CPS) that connects physical components to cloud-based analysis processes, aiming to leverage cloud characteristics for shared and optimized maintenance operations.
Prognostics and Health Management (PHM) offers several benefits for predictive maintenance. It predicts the future behavior of a system as well as its Remaining Useful Life (RUL). This RUL is used to planned the maintenance operation to avoid the failure, the stop time and optimize the cost of the maintenance and failure. However, with the development of the industry the assets are nowadays distributed this is why the PHM needs to be developed using the new IT. In our work we propose a PHM solution based on Cyber physical system where the physical side is connected to the analyze process of the PHM which are developed in the cloud to be shared and to benefit of the cloud characteristics