This paper discusses the objectives and early results of the project PROAGE, funded by INAIL under the Saf€ra framework. The aim is to better control of the ageing of equipment, to quantify the impact of operating modes on system reliability, to estimate their residual life and to adapt the maintenance strategy, while respecting safety, regulation and operational performance. Monitored systems in modern process plants can be seen as “intelligent prognostics” system to measure, control, and alert the operating personnel, detecting degradation mechanisms (such as fatigue or corrosion before mechanical integrity is compromised and, in the end, prevent potentially dangerous outcomes. Case studies of industrial interest whose results will disclose the data, the methodologies and the procedures to enhance the capabilities of the organizations of dealing with ageing assets. Data mining techniques applied to the data gained through the automated monitoring and control systems, and the inspections, will allow to extract meaningful indications to support risk- based decision making (Comberti et al., 2018) and the risk management of ageing equipment (Baldissone et al., 2019). Development of professional competencies related to ageing management: specific training for an environment where the volume of data and flexibility of the human machine interface (HMI) systems has increased and is continuously increasing together with the ICT capabilities will be also considered and will be included in a dedicated training case-study, taking advantage of the more recent Serious Game approaches. Within the expected results & outcomes, the Development of a complete theoretical and operational approach to the problem of the ageing equipment, complemented with the methodological and technical tools, resulting in a quantifiable improvement of the safety management in industry is foreseen.
Demichela M., Cozzani V., Marzani A., Baldissone G., Messina M. (2019). Aging facilities prognostic & health management: Data collection, analysis and use. CHEMICAL ENGINEERING TRANSACTIONS, 77, 925-930 [10.3303/CET1977155].
Aging facilities prognostic & health management: Data collection, analysis and use
Cozzani V.Validation
;Marzani A.Supervision
;Messina M.Investigation
2019
Abstract
This paper discusses the objectives and early results of the project PROAGE, funded by INAIL under the Saf€ra framework. The aim is to better control of the ageing of equipment, to quantify the impact of operating modes on system reliability, to estimate their residual life and to adapt the maintenance strategy, while respecting safety, regulation and operational performance. Monitored systems in modern process plants can be seen as “intelligent prognostics” system to measure, control, and alert the operating personnel, detecting degradation mechanisms (such as fatigue or corrosion before mechanical integrity is compromised and, in the end, prevent potentially dangerous outcomes. Case studies of industrial interest whose results will disclose the data, the methodologies and the procedures to enhance the capabilities of the organizations of dealing with ageing assets. Data mining techniques applied to the data gained through the automated monitoring and control systems, and the inspections, will allow to extract meaningful indications to support risk- based decision making (Comberti et al., 2018) and the risk management of ageing equipment (Baldissone et al., 2019). Development of professional competencies related to ageing management: specific training for an environment where the volume of data and flexibility of the human machine interface (HMI) systems has increased and is continuously increasing together with the ICT capabilities will be also considered and will be included in a dedicated training case-study, taking advantage of the more recent Serious Game approaches. Within the expected results & outcomes, the Development of a complete theoretical and operational approach to the problem of the ageing equipment, complemented with the methodological and technical tools, resulting in a quantifiable improvement of the safety management in industry is foreseen.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.