Sasol Leverages Cloud-Powered Predictive Analytics for Enhanced Decision-Making

This presentation by Joseph (Joe) Barber, a mechanical engineer with extensive experience in reliability engineering at Sasol, focuses on the transition of Asset Performance Management (APM) from on-premise to cloud-based solutions. It outlines the motivation, benefits, and challenges of migrating to cloud technology for predictive analytics in industrial settings. The shift aims to enhance accessibility, cost savings, and global standardization, addressing data privacy and cybersecurity concerns effectively.

Joe shares insights from his professional journey, emphasizing the importance of predictive maintenance and reliability engineering in large-scale projects. He highlights the architecture of the new cloud-based APM system, which integrates various data sources, including SAP and vibration analysis software, to optimize equipment performance and risk management.

The presentation includes case studies demonstrating significant cost savings and operational improvements achieved through predictive analytics. One example involves addressing compressor fouling issues through targeted chemical treatment, preventing costly shutdowns. Another case highlights improved communication and performance monitoring within teams using customized dashboards.

Key challenges faced during the transition include ensuring robust cybersecurity measures and reliable data flow through OPC interfaces. Despite these hurdles, the cloud migration resulted in substantial benefits, such as reduced maintenance costs, easier global implementation, and enhanced flexibility for policy modifications.

In conclusion, Joe emphasizes the critical role of tracking and documenting findings to justify the investment in cloud-based APM solutions, underscoring the long-term value and efficiency gains achieved through this technological advancement.