Boeing: Increasing Quality & Efficiency Through AI

Boeing's development of a photo-driven AI validation tool demonstrates how optical character recognition technology can transform industrial quality assurance processes.

The solution, which enables inspectors to photograph part information rather than manually entering long serial numbers, represents a significant application of AI in aerospace quality control.

The technology extracts and logs data directly into Boeing's aircraft readiness log (ARL) using embedded optical character recognition.

According to a McKinsey report, AI could reduce expenses by up to half a trillion dollars in manufacturing and supply chain operations alone, suggesting substantial potential for automation solutions across industrial sectors.

OCR technology

The AI tool uses optical character recognition to read text from photographs captured on handheld devices.

Once the system extracts the information, it validates the data against a part information dictionary before populating the part serial number into the aircraft readiness log directly.

This approach eliminates the need for manual data entry of serial numbers during aircraft inspection processes.

The tool currently supports inspection of more than 1,400 aircraft parts across Boeing's production facilities.

Wanbin Song, Boeing AI Team Lead at Boeing Korea Engineering & Technology Centre (BKETC), says: "Quality inspectors identified the challenges in their current process and guided our design.

"Their insights guided us through the development journey and helped minimise disruption to existing workflows."

Rapid deployment across international teams

The development effort involved collaboration between engineering teams from BKETC and Boeing Artificial Intelligence, working with colleagues in the US.

The cross-functional approach brought together ARL, Boeing AI, Information Digital Technology & Security and BKETC teams.

Jay Oh, Boeing AI Senior Manager at BKETC, says: "With rapid field deployment in mind, ARL, Boeing AI, Information Digital Technology & Security, and BKETC worked closely together.

"By taking charge of their areas, the teams delivered a prototype ready for on-site testing in just eight months, showcasing their dedication to field innovation."

The team's methodology involved spending weeks on the factory floor, meeting with quality inspectors daily and running workshops to iterate on the tool's design.

This collaborative approach ensured the solution addressed real-world challenges rather than theoretical improvements, increasing the likelihood of successful adoption.

Measurable impact on inspection processes

Before the AI tool's deployment, more than 70% of Boeing 737 part serials required manual entry.

The implementation improves inspection time by more than 17 hours per aircraft, representing a substantial efficiency gain in production workflows.

The tool launched on production lines at Boeing's Renton Factory and Everett Factory in 2024, with plans to implement it at Boeing South Carolina.

Hector Silva, Vice President of Regulatory Compliance and Core Quality at Boeing, says: "The engineers spent weeks on the factory floor, meeting with Quality inspectors daily, running workshops and iterating on the tool to minimise disruption to long‑standing processes.

"The team focused on listening to users, making incremental changes inspectors could adopt quickly and integrating OCR into legacy workflows to reduce the number of devices inspectors must carry."

According to McKinsey research, rising passenger demand for air travel is meeting with constrained supply of new aircraft, with delivery times and maintenance turnaround times experiencing delays.

The integration of AI-driven processes across manufacturing and research and development contributes to addressing these supply chain challenges.

Boeing reported delivery of 348 commercial aircraft in 2024 and 600 in 2025, demonstrating the ongoing demand for production efficiency improvements.