GE Vernova Streamlines Inspections, Monitoring with AI-Based Software

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Autonomous Inspection is a software program using artificial intelligence (AI) and machine learning (ML) to automate manual processes, manual inspection, and asset monitoring.

GE Vernova released a cloud-based computer vision software called Autonomous Inspection. The program is designed to automate the monitoring of industrial assets and manual inspection processes through image capture devices and AI/ML algorithms. It integrates visual data and additional insights for select programs within GE Vernova’s Asset Performance Management (APM) software suite—APM helps asset performance and operations and maintenance efficiency for equipment, plants, and entire fleets.

"In the energy industry, computer vision is not just about seeing, it’s about foresight. Autonomous Inspection is the eyes of our APM suite and is powered by AI technology that turns images into rich data that can help power insights to transform how we safeguard, optimize, and propel the future of energy," said Linda Rae, General Manager of GE Vernova’s Power & Energy Resources Software business. “Digitalizing operations has helped customers in quality, safety, and performance improvements, as well as emission management.”

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Autonomous Inspection can help a variety of industries by advancing operational excellence, helping with safety and compliance, and providing a visual aspect for performance goals.

  • Operational Quality: An oil and gas firm recently used the Autonomous Inspection software during a pilot. It removed bottlenecks such as manual-intensive and siloed inspection workflows via automation, allowing the firm to reduce inspection review time for corrosion images from two weeks to 30 minutes.

  • Safety & Compliance: Cameras and AI/ML algorithms can reduce the safety risks associated with workers performing inspections at elevation or near heated equipment. This technology can also decrease the need for inspection-related travel with remote access to data and insights over the cloud. A European utility is using the program to monitor electrical equipment, such as transformers and switchyards, and transitioning toward a remote-enabled, efficient asset inspection model.

  • Performance Goals: The automation of manual workflows can save the time and effort of previously relied-upon workers. Autonomous Inspection allows workers to quickly identify defects and sends alerts to enable preventative actions for improved asset uptime.

Within the overall inspection and monitoring workflows, Autonomous Inspection’s capabilities include automated image data collection, processing, integration, analysis, and management. It can be applied to use cases such as automated gauge reading, corrosion detection, severity classification, and thermal profiling of equipment.

At the beginning of April 2024, GE Vernova installed its SmartSignal predictive analytics software into the APM program used by Saudi Arabia’s National Industrialization Company (TASNEE). SmartSignal can help industrial companies prevent equipment downtime by detecting, diagnosing, and forecasting emerging failures. TASNEE will use this software, and the rest of its APM program, to increase operational efficiency, reliability, and sustainability across its industrial operations in the country.

"Embracing digital transformation is imperative for our industry's evolution, and our collaboration with GE Vernova signifies a commitment to staying at the forefront of innovation," said Sultan Al Hazmi, Reliability Superintendent at TASNEE. "GE Vernova's predictive analytics software will play a pivotal role in our holistic APM strategy, providing us with actionable insights to enhance asset performance, reduce operational risks, and drive sustainable growth.”

The company’s advanced analytics platform merges data-supported insights and machine learning algorithms to allow companies, such as TASNEE, to replace reactive maintenance operations with a proactive and predictive approach. SmartSignal has the capability to maximize asset lifespan and, as a result, may contribute to increased overall productivity for TASNEE’s petrochemical operations.