At last week’s Predictive Aircraft Maintenance (PAM) Conference in Dublin, Matias Bjerregaard, predictive maintenance specialist at SAS – Scandinavian Airlines, shared valuable insights on how the airline has been leveraging predictive maintenance to improve operational efficiency.
For over 75 years, SAS has been connecting Scandinavia to the world, and Bjerregaard explained that the airline’s investment in aircraft health monitoring (AHM) aims to enhance passenger satisfaction and reduce maintenance costs.
“Predictive maintenance is pivotal in reducing Aircraft on Ground (AOG) events, improving passenger satisfaction, and lowering maintenance costs,” Bjerregaard explained. “Our teams work tirelessly to achieve our goals of improving defect management, troubleshooting efficiency, and minimising unscheduled maintenance.”
SAS’s transition to predictive maintenance began through its partnership with Airbus and the adoption of the Skywise Predictive Maintenance+ system. “A dedicated team and new roles – such as predictive maintenance specialists – were established to oversee the system’s development,” Bjerregaard said. He also highlighted key milestones, such as retrofitting the fleet for real-time data transmission and integrating predictive tools into the airline’s maintenance workflow.
“Predictive maintenance has proven highly effective in addressing a range of operational challenges,” Bjerregaard noted, citing examples like abnormal engine operations, hydraulic fluid leaks, and landing gear uplock degradation, all of which have been successfully managed using predictive systems. “These interventions have significantly reduced delays and cancellations, ensuring smoother flight operations and improved customer satisfaction.”
In addition to boosting operational efficiency, Bjerregaard explained that predictive maintenance has delivered notable financial and environmental benefits. By minimising delays, cancellations, and reducing excessive fuel consumption, the airline has achieved significant cost savings. For instance, detecting a faulty trim tank isolation valve helped prevent a 1% increase in fuel consumption, demonstrating how predictive maintenance can avoid inefficiencies and mitigate penalties.
Furthermore, the integration of predictive systems has led to improved reliability metrics. “Aircraft equipped with these systems have experienced a 37% reduction in unscheduled downtime, so we’ve seen the benefits of predictive maintenance in enhancing fleet performance and operational consistency,” Bjerregaard said.
In conclusion, Bjerregaard emphasised that SAS’s predictive maintenance strategy is centered on continuous feedback, fine-tuning models, and learning from operational data to further enhance maintenance efficiency and fleet reliability.
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