Holistic view of asset predictive analytics

Noman Rasool, the Lead Business Process Automation at Shell, a seasoned expert in Electrical Engineering, Agile Project Management, and with an MBA from the University of Alberta. With over 18 years of experience, he’s a leader in cloud migration, Predictive Analytics, and Asset Modernization. Stay tuned as we delve into his innovative strategies in asset predictive analytics.

In the world of modern industry, making things work smoothly and preventing problems before they happen is crucial. Here’s a simple four-step plan to do just that: First, gather information from your machines and equipment. Second, send that information to a computer either on the cloud or at your workplace. Third, let smart computer programs use this data to predict when something might go wrong with your machines. And finally, don’t stop at one machine – apply this process to all your machines and systems to keep everything running smoothly and prevent issues across the board. That’s how you use the power of data to make your business better!

Data collection from assets
Transportation of data to cloud or on-prem
Apply ML/AI on this data using data-driven models and validate value proposition
Scale it to all asset class, equipment class and system class and that’s how you can modernize and optimize your pipeline or any other system

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