2013 - EMEA Industry Session - Oil and Gas
The Implementation of the PI System to Support Predictive Maintenance Diagnostics Across Oil & Gas Plants in Italy
The presentation describes ENI’s experience in implementing the PI System, focusing on providing a real-time data integration and applications infrastructure for the Predictive Maintenance Diagnostics application for major rotating equipment (gas turbines, reciprocating and centrifugal compressors) across ENI’s oil and gas plants in Italy.
The PI System architecture will be described, including the centralized PI Server at headquarters and the PI Interfaces for a variety of DCS and SCADA systems across two major oil and gas facilities and three gas plants in Italy.
The PI system plays two roles within the Predictive Maintenance Diagnostics application by providing:
- The source of real time data to feed a specialized predictive analytics package (Smart Signal). This software supports the early detection of malfunctions and/or the degradation of the performance of the equipment by identifying any minor modifications between the expected behavior (based on the observations of historical data) and the actual behavior of the equipment.
- Direct diagnosis tools (PI ProcessBook and PI DataLink) when dealing with failures that are rapidly developing on the equipment which cannot be detected by the predictive analytics package.
After two years of applications, use of the PI System’s real time data has demonstrated its value with more than thirty early diagnoses covering leaking valves, leakage from packing, dirty fuel injectors, bad sensors, lubrication problems, and motor windings problems which triggered maintenance actions in the plants, thereby avoiding equipment damage.
The analytical capability of the PI System allowed the investigation and determination of the cause of failure for several major issues which developed so quickly that they could not be prevented. The correct identification of the cause of failure enabled engineering and modifications to prevent similar problems in the future.
ENI will discuss its vision of the PI System in addressing other business needs.
Cristina Bottani is a technical leader within the Business Application Development group of ENI E&P in Milan, Italy. Bottani holds a Mathematical degree with Universita di Pavia. She joined ENI E&P in 1987, and worked for several years on projects related to technical applications and databases for Oil & Gas.
Since 2009, she has been working as architecture designer for real time applications. She is involved in R&D projects across several disciplines, including HSE, Engineering, Reservoir and G&G. Bottani has authored several technical papers presented at Oil & Gas conferences.
Marco Piantanida is a knowledge owner and technical leader within the Business Application Development group of Eni E&P in Milan, Italy. He holds an Electronic Engineering degree with Politecnico di Milano and a Master's degree in Information Technology. Piantanida gained the PMP (Project Management Professional) certification in 2005. He joined Eni E&P in 1992, and had been working for ten years on projects related to Expert Systems, Neural Networks and advanced algorithms for the E&P world.
Since 2002, Piantanida has been working as project manager and architecture designer for technical web portals and collaboration tools. He has been in charge of the development of the IT framework supporting the processes of E&P Field Development, Exploration, Operation & Production, and Innovation Projects. Piantanida is also involved in many R&D projects across several disciplines, including HSE, Engineering, Reservoir and G&G. He has authored many technical papers in Oil & Gas conferences, as well as being a session chairman.