[4D4] New frontiers of asset integrity management and predictive maintenance
A Mura
Antea Srl, Italy
In today’s asset integrity management (AIM) landscape, the abundance of data presents unprecedented opportunities to achieve unparalleled reliability levels. However, effectively organising and utilising this data remains a complex challenge requiring meticulous planning. This paper aims to explore emerging trends in AIM and maintenance management, focusing on how modern technologies can be leveraged and adapted to meet operational demands and optimise field activities.
The discussion begins with an overview of the data and modules available in state-of-the-art AIM platforms, highlighting potential enhancements enabled by advanced technologies. These innovations promise transformative improvements in management practices.
The study delves into advanced methodologies for managing classical non-destructive testing (NDT) techniques and related technical analyses, such as risk-based inspection (RBI), reliability-centred maintenance (RCM) and fitness for service (FFS). Furthermore, it examines the integration of online data management tools with monitoring systems such as integrity operating windows (IOWs), artificial intelligence applications and modern inspection technologies such as robots and drones. Additional technological advancements, including 3D modelling, laser scanning, mobile apps and cross-platform integration, are presented as key components that enhance AIM. These technologies collectively contribute to maximising safety and productivity while minimising unplanned events and downtime.
The insights presented draw from extensive experience with oil, chemical and petrochemical plants, where stringent management is essential due to high risks of major accidents. Nonetheless, the concepts discussed are broadly applicable across various industries.
This paper provides a comprehensive perspective on leveraging modern technologies to revolutionise AIM, offering practical solutions for achieving enhanced operational excellence.
The discussion begins with an overview of the data and modules available in state-of-the-art AIM platforms, highlighting potential enhancements enabled by advanced technologies. These innovations promise transformative improvements in management practices.
The study delves into advanced methodologies for managing classical non-destructive testing (NDT) techniques and related technical analyses, such as risk-based inspection (RBI), reliability-centred maintenance (RCM) and fitness for service (FFS). Furthermore, it examines the integration of online data management tools with monitoring systems such as integrity operating windows (IOWs), artificial intelligence applications and modern inspection technologies such as robots and drones. Additional technological advancements, including 3D modelling, laser scanning, mobile apps and cross-platform integration, are presented as key components that enhance AIM. These technologies collectively contribute to maximising safety and productivity while minimising unplanned events and downtime.
The insights presented draw from extensive experience with oil, chemical and petrochemical plants, where stringent management is essential due to high risks of major accidents. Nonetheless, the concepts discussed are broadly applicable across various industries.
This paper provides a comprehensive perspective on leveraging modern technologies to revolutionise AIM, offering practical solutions for achieving enhanced operational excellence.
