AI in Predictive Asset Maintenance

Artificial intelligence has a growing role in the manufacturing sector regarding the predictive maintenance of machines and their parts. As opposed to traditional maintenance of machines, predictive maintenance utilizes historical and real-time data to detect and repair issues before they become critical. We will learn more about this growing use case of AI during this session. Among the learning outcomes of this session are:

– What assets require Predictive Asset Maintenance (PAM) in the Oil & Gas Industry?
– Impact of PAM 
– RUL (Remaining Useful Life) & TTF (Time To Failure)
– Explaining the workflow with hands-on Python code
– Example Projects (If time permits)

About the Speaker

Divyanshu is a Machine Learning & Data Analytics Consultant and a Community mentor for AI enthusiasts in the Oil and Gas Industry. Currently, he works for Shell as a Data Science Researcher. Before this, he worked on data science and analytics at Accenture AI, Dicelytics, and L&T Infotech. He is also the founder of Petroleum from Scratch: a venture focused on mentoring the community with core Petroleum Concepts and Data Analytics Skills that help students and professionals acquire the skills needed for Industry 4.0.