Latest Article
How to Achieve Predictive Corrosion Management: The Role of Technology and IIoT for Predictive Analytics
by Mustapha Mazouzi, President Antea Americas
and Floyd Baker, VP Antea Americas
One of the largest threats to operations in asset and process-intensive industries (such as oil and gas, petrochemical, and power generation) is corrosion. If insufficiently monitored, corrosion damage will lead to the degradation of assets, at various rates – creating cause for leaks, cracks, reduced reliability, and even complete equipment failure or other catastrophic events. The safety, environmental, equipment repair and replacement and production loss costs of such events are documented in industry.
An effective corrosion management system (CMS) is a critical component of any asset integrity management (AIM) strategy to mitigate the consequences of corrosion – and, ideally, to predict or prevent them.
The Industrial Internet of Things (IIoT) has brought the advent of advanced technologies that, when leveraged properly, can heighten the efficacy of CMS. When bridged in a centralized database – for example, an AIM software – these technologies provide continuous remote monitoring and heightened levels of asset intelligence.
Over time, they enable predictive analytics, making it possible for operators of process-intensive industries to elevate their CMS practices from simple mitigation to true predictive corrosion management (PCM). This article examines how you can improve your corrosion management strategies and achieve PCM — anticipating and preventing corrosion incidents before they have a chance to occur.
In this article, which was featured in Inspectioneering Journal, you will learn:
- Corrosion Management System Requirements according to NACE
- Corrosion Types and Technologies
- The Role of IIoT for Predictive Analytics
- Benefits and Implementation Strategies
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