This interview is part of our new AI in Energy series, where we interview the world's top thought leaders on the front lines of the intersections between AI and energy.
In this interview, we speak with Greg Slater, General Manager and Head of Sales at Flutura Decision Sciences and Analytics, to understand how his company is using AI to transform energy, and what the future of the energy industry holds.
1. What's the story behind Flutura? Why and how did you begin?
GS: With companies reaching a plateau of efficiency by deploying repeatable processes and automation, the question emerged: where would the next possible efficiency levers come from to improve the bottom line? If you look at the list of the top ten companies on the S&P index over the last ten years, you will see the 100-year-old companies that once enjoyed high market cap have been toppled. This is evidence that our world is changing and changing fast.
Many of these companies have large scale operations, equipment, and a wide customer base. But very few companies have real-time insights into last mile operations across various business processes. This is where Flutura sees the next level of efficiency improvements.
The Flutura founders chose themes/problems to be addressed and one of them was how to help companies increase visibility into last mile operations in real time. The second theme was building a product to help address this at scale. From thereon it has been a “Serendipitous Journey of Experiments” identifying the solution to solve at the last mile. Flutura zeroed on unplanned downtime of heavy machinery and machine influenced process deviations as areas which were vastly underserved.
2. Please describe your use case and how Flutura uses artificial intelligence:
GS: The Artificial Intelligence space will continue to evolve, and we believe every step from now on will be towards large-scale autonomous operations which will become commonplace.
Cerebra is the AI platform tuned for Industrial IoT, focused on improving the two core business objectives of “Equipment Uptime” and “Operational Efficiency.”
AI is used for:
- Automating root cause analysis for the petrochemical industry.
- Enabling dynamic operating environments for the operators.
- Predicting output quality, potential equipment downtime, and performance degradations.
- Predicting potential safety threats with the goal of avoiding events risking human, aquatic life, and the environment (oil leakage, blow out, etc.).
- Reducing resource waste.
3. Could you share a specific customer/user that benefits from what you offer? What has Flutura done for them?
GS: One global technological leader in the energy industry engaged in the design and manufacture of equipment, and required real-time diagnosis of the health of its early production system for two reasons:
- Too many signals to process. Human eyes were missing anomalies leading to performance degradation.
- Decreased productivity and project profitability as there were no detailed sensor intelligence or equipment diagnostics.
Cerebra reduced latency associated with detecting performance deviations by identifying micro-signals. With the additional time to react/plan for the deviations, operators were able to increase uptime for the equipment, including:
- Deployment of a digital twinmodule for easy configuration of multiple subsystems of EPS on Cerebra.
- Deployment of advanced diagnostics module for real-time detection of performance deviations which decreased the unplanned downtime.
- Deployment of Cerebra’s prognostic module for detecting early warning signals using vessel pressure, flow rate, and enabling field engineers to take proactive actions.
Ultimately, the utilization of Cerebra enabled the customer to introduce an Asset-as-a-Service offering for customers resulting in:
- A 90 percent reduction in latency for detecting performance deviations.
- A 23 percent reduction in non-productive time over the course of a year.
- Cerebra was configured and went live in two weeks.