March 2019

The Safety 4.0 challenge: The Asset Integrity Management for Safety Critical Element risk management.

The business article this month propose a discussion about the importance of the AIM to manage the risk of safety critical elements based on new technologies deployed by the Industry 4.0



Since 2010, the new era of Industry 4.0 becomes to be reality for many industries across the globe. In the last five years new IOT technology development has been applied to AM based on different topics such as Big Data, Prognostic Health Maintenance and Machine Learning, being part of the so-called Maintenance 4.0.


 Despite of all development, that enable an integrated AM, too much focus has been given for maintenance and a lack of effort for safety concerning the safety critical element management. This paper aims to demonstrate the application of the AIM under AM process by applying the Industry 4.0 IOT technology. 




Key Words: Asset Integrity Management, Safety Critical Element, Risk Management, Reliability, Maintenance, Human Factor, Industry 4.0.

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Please download the full paper here.
The Safety 4.0 challenge The Asset Integ
Adobe Acrobat Document 577.3 KB

June 2019

Prognostic Health Management (PHM) based on AI solution for railway applications



The Prognostic Health Management (PHM) aims to prevent such corrective action, incident and accident by monitoring the physical asset condition and alert in case of physical asset deterioration or degradation stage. Such methodology relies on sensor information input as the basis of the prognostic. Therefore, PHM had the advantage to provide constant health conditions state about the physical asset rather than the schedule preventive maintenance or NDT that also detect the physical asset degradation, but in a specific period of time.


Based on Artificial Intelligence (AI) concept, it´s important to have a PHM that´s is adaptive to the new data collected by sensors along time and enable to update the health condition prediction based on pre-defined algorithm.


Key Words: Prognostic Health management, Remaining Life, Sensor, Artifitial Intelligence.

Paper - Adaptive Remaining Life Estimation
Adobe Acrobat Document 436.9 KB