Ageing Assessment and Management at Major-Hazard Industries

As a consequence of the obligations of the Directive Seveso III, there is a need of methods and tools that support industrial managers and the auditors, respectively, to manage and to verify the ageing status of critical equipment. Risk-Based Inspection methods (RBI) are usually used, as well as som...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Chemical engineering transactions 2018-09, Vol.67
Hauptverfasser: Francesca Milazzo Maria, Paolo Bragatto, Giuseppa Ancione, Giuseppe Scionti
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:As a consequence of the obligations of the Directive Seveso III, there is a need of methods and tools that support industrial managers and the auditors, respectively, to manage and to verify the ageing status of critical equipment. Risk-Based Inspection methods (RBI) are usually used, as well as some other recommended practices (ASME, API or RIMAP). Criticalities are associated with RBI methods as these were born to optimise inspections’ costs by comparing them with safety levels, thus an effort is always necessary to adapt the method in order to manage ageing. This work describes an under-development system that supports industrial managers and auditors in controlling and managing ageing. It can be considered as a virtual sensor, made up by hardware and software. It collects information about process variables (recorded by control systems), external variables, inspection information and other data, then it processes collected information and predicts the numeric value of a performance indicator based on the approach for the ageing assessment, which was developed by an Italian working group on ageing. Based on such an indicator the prediction of the ageing state of the equipment is possible as well as its management based on the levels of industrial risk acceptance. The software is a dynamic model indicating factors that accelerate and those that slow down the degradation processes. The model is expected to build a “digital twin” of a complex plant by using a huge amount of data, which is valuable to understand how the plant will age in the next future.
ISSN:2283-9216
DOI:10.3303/CET1867013