Boeing Deploys Photo-Driven AI to Streamline Aircraft Part Validation

Boeing has introduced a new artificial intelligence tool designed to automate the inspection and logging of aircraft parts, a move the manufacturer states has significantly reduced production time and improved data accuracy. Developed by engineers at the Boeing Korea Engineering & Technology Center (BKETC), the system utilizes Optical Character Recognition (OCR) to replace manual data entry during the assembly process.

According to the company, the new technology allows quality inspectors to validate components simply by photographing them. This innovation addresses a longstanding bottleneck in the manufacturing workflow, reportedly saving more than 17 hours of inspection time per airplane.

Eliminating the “Fat-Finger” Factor

Prior to the implementation of this AI solution, quality inspectors were required to manually input complex serial numbers into the Aircraft Readiness Log (ARL). This process was not only time-consuming but also susceptible to human error, often referred to in the industry as “fat-finger” typos.

Boeing data indicates that before the tool’s deployment, approximately 70% of part serial numbers on the 737 program had to be entered manually. The repetitive nature of typing long strings of alphanumeric characters created a high potential for inaccuracies, which could disrupt the “digital thread”, the continuous digital record of an aircraft’s components and history.

How the Technology Works

The new handheld tool leverages computer vision to streamline the validation process. The workflow, as described in Boeing’s report, involves three primary steps:

• Capture: An inspector takes a photograph of the part’s identification tag.
• Processing: The AI analyzes the image, reading the text and validating it against a “part information dictionary” to ensure the component matches engineering requirements.
• Logging: Once validated, the system automatically populates the serial number and relevant data into the ARL, removing the need for manual typing.

To ensure the system could handle the variety of fonts, formats, and lighting conditions found on a factory floor, the development team undertook an extensive training process. Engineers captured over 2,250 images of various parts and manually labeled nearly 38,100 text boxes to train the machine learning model. Currently, the tool is capable of inspecting more than 1,400 different parts.

Development and Deployment

The project was a collaborative effort led by the Boeing Korea Engineering & Technology Center (BKETC) in partnership with the company’s central Artificial Intelligence team. The involvement of the Korea-based team highlights Boeing’s strategy of leveraging global engineering talent to solve specific production challenges.

“Quality inspectors identified the challenges in their current process and guided our design. Their insights guided us through the development journey and helped minimize disruption to existing workflows.”

, Wanbin Song, Boeing AI Team Lead at BKETC

The tool was first deployed in January 2024 at Boeing’s primary manufacturing sites in Renton and Everett, Washington, which produce the 737 and widebody jets respectively. Following its success in these facilities, Boeing plans to expand the technology to its South Carolina facility for 787 Dreamliner production. The team is also evaluating other areas of the production system where this OCR capability could further streamline documentation.

AirPro News Analysis

The deployment of this OCR tool represents a practical application of “Smart Factory” principles, moving beyond buzzwords to address tangible production inefficiencies. In aerospace manufacturing, the integrity of the “digital thread” is paramount; the physical aircraft must perfectly match its digital records for safety, maintenance, and regulatory compliance.

By automating the entry of serial numbers, Boeing is reducing the cognitive load on inspectors and closing a gap where human error frequently occurs. While a saving of 17 hours per aircraft may seem minor in the context of a multi-month build cycle, these incremental efficiency gains are critical as the manufacturer seeks to stabilize production rates and ensure rigorous quality control across its assembly lines.

Frequently Asked Questions

What is the primary benefit of the new AI tool?
The tool eliminates manual data entry errors and reduces inspection time by over 17 hours per aircraft.

Who developed the technology?
The tool was developed by the Boeing Korea Engineering & Technology Center (BKETC) and the Boeing AI team.

Where is the tool currently used?
It was deployed in Renton and Everett, Washington, in January 2024, with plans to expand to Boeing South Carolina.

Sources

• This article is based on an official report from Boeing.