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Managing Integrity And Corrosion Through Real-Time Prediction Modeling Approach – “Software Sensor” Concept

Managing Integrity and Corrosion Through Real-Time Prediction Modeling Approach – “Software Sensor” Concept
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Safe and stable operation of the process plant through its life cycle is an ultimate target of any integrity management system. Over the last decades, a number of possible ways and systems for managing plant integrity were described and implemented.1-4 A common path for all those efforts was to control and manage corrosion processes in a more-or-less systematic way by applying certain measures (monitoring techniques, material selection guidelines, operating procedures etc.) and performance indicators (remaining time-to-failure, inhibitor usage etc.). An effective corrosion and integrity management system, in theory, should be capable to “uncover” excessive corrosion incidents before serious damage occurs. Unfortunately, unexpected corrosion-related failures are still occurring in the petroleum industry.5 This situation stems predominantly from relatively poor data organization and management, leaving corrosion and key process information spread and hidden across different refinery functions and systems.  

Product Number: 51322-18126-SG
Author: Slawomir Kus, Kwei Meng Yap, Pierre Constantineau
Publication Date: 2022
Industries: Corrosion Monitoring and Control , Coatings
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$20.00

Corrosion and Integrity Management (CIM) covers several elements such as policy, strategy, resources etc. For effective implementation and supervision, these should be also supported by an integrated IT platform for analysis and communication. There’s a lot of hype about the Digital Transformation or the Industrial Internet of Things and their roles in supporting corrosion and integrity management. Digital Transformation at its core, is a simple concept – to harness the immense power of plant and process data in a seamless, cloud enabled digital environment to achieve superior process efficiencies, productivity, and reliability. This has important implications from connectivity of real time operating data, automated predictive analytics, increased collaboration – and finally, the quantitative impact on the process of managing corrosion. Over the last 20+ years, a number of research initiatives to effectively manage corrosion assessment, damage mitigation and asset integrity management in refinery unit operations were conducted by Honeywell International Inc. sponsored by global, industry-leading refining and engineering companies. Results of these research efforts formed the foundation for corrosion prediction models for multiple corrosion damage mechanisms including naphthenic and sulfidic corrosion, ammonium bisulfide corrosion and ammonium chloride corrosion. The by-product of these comprehensive efforts is a real time corrosion software sensor framework built around industry leading corrosion prediction models.

Corrosion and Integrity Management (CIM) covers several elements such as policy, strategy, resources etc. For effective implementation and supervision, these should be also supported by an integrated IT platform for analysis and communication. There’s a lot of hype about the Digital Transformation or the Industrial Internet of Things and their roles in supporting corrosion and integrity management. Digital Transformation at its core, is a simple concept – to harness the immense power of plant and process data in a seamless, cloud enabled digital environment to achieve superior process efficiencies, productivity, and reliability. This has important implications from connectivity of real time operating data, automated predictive analytics, increased collaboration – and finally, the quantitative impact on the process of managing corrosion. Over the last 20+ years, a number of research initiatives to effectively manage corrosion assessment, damage mitigation and asset integrity management in refinery unit operations were conducted by Honeywell International Inc. sponsored by global, industry-leading refining and engineering companies. Results of these research efforts formed the foundation for corrosion prediction models for multiple corrosion damage mechanisms including naphthenic and sulfidic corrosion, ammonium bisulfide corrosion and ammonium chloride corrosion. The by-product of these comprehensive efforts is a real time corrosion software sensor framework built around industry leading corrosion prediction models.

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