Case Study: Santos achieves millions in annual savings with IBM Analytics predictive asset monitoring

Saving millions with a predictive asset monitoring and alert system

Santos Ltd., a leading oil and gas producer, faced the challenge of preventing critical asset failures across its vast, remote operations to avoid costly downtime and safety risks for engineers. To address this, they partnered with vendor IBM to leverage predictive analytics using IBM SPSS Modeler and IBM SPSS Lab Services to identify early warning signs from their existing IoT sensor data.

The IBM solution created predictive models that analyze multiple data streams to forecast equipment failure with high accuracy. This has enabled Santos to shift to proactive, predictive maintenance, resulting in over AUD 10 million in annual savings from increased uptime, optimized power systems, and more efficient scheduling. IBM's technology has significantly reduced engineer travel time and improved safety while providing scalable models for future applications.

Santos

Steven Benn

Manager