Faizan Patankar, CEO of Amygda, was invited to Vertical MRO Podcast, hosted by Val Medved, to discuss the current role of AI, the future of human-AI collaboration, and the benefits of AI for Helicopter Maintenance.
Amygda is building artificial intelligence assistance for MaintOps teams to improve reliability and boost efficiency for helicopters and other assets in the transport industry.
The discussion covered the practical applications of AI across the helicopter industry. From predictive maintenance to supply chain and procurement strategies.
Key highlights in the podcast include:
- the critical balance between AI systems and human expertise,
- emphasising the importance of building trust through accurate data implementation.
The conversation also looked toward future innovations. Including the potential of robotics for inspection and the integration of natural language processing in maintenance and operations.
Part of the podcast focused on current industry challenges. It is worth noting that less than 10% of helicopters worldwide currently utilise health and usage monitoring systems (HUMS).
Key takeaways from the podcast:
1. Decision support
Modern helicopters can generate over 4,000 data points per second – far too much for human processing. Amygda’s AI solution can process this data and equip maintenance technicians with the information necessary to make informed decisions.
2. Enhancing Human Capabilities
AI offers advanced analytics and predictive capabilities. It is not a replacement for human expertise, particularly in areas requiring nuanced judgment.
Look at AI as augmenting the human expertise. AI is meant to provide assistance to maintenance and operations teams. Until we reach an agreed level of artificial general intelligence (AGI) that is acceptable to the regulatory bodies, we will always have a human in the loop for maintenance decision making.
3. OEM Independence in AI Solutions
AI systems need to be OEM (Original Equipment Manufacturer) independent. This approach allows operators with mixed fleets to unify data and insights across different platforms and component suppliers, enabling seamless maintenance operations.
4. Knowledge Preservation
A major challenge in the industry is the loss of technical knowledge as experienced engineers retire. AI systems that capture and codify this expertise, will ensure that critical knowledge is retained and accessible for future technicians.
Every interaction improves the system’s understanding. When your experienced staff provide feedback or take action, the system learns – building a growing knowledge base that benefits all users. This means newer team members can benefit from years of operational experience.
Listen to the full podcast to find out how many dimensions the human brain can process and what’s the “iPhone Moment” for AI and Maintenance.
