To kick off the project, teams from two advanced innovation centers came together. ACIC’s industry specialists were familiar with the data, the data collection process during manufacturing, the problems encountered and the desired solutions. Meanwhile, Accenture Labs researchers utilized their expertise in AI and computer vision to develop a new AI as well as a special data annotation tool—that is custom fit for that data to expedite the annotation of over a million video segments.
The teams maintained an agile development process to efficiently develop the AI, train and test the model, identify the weaknesses and iterated until they achieved the performance level needed to do the job correctly and consistently.
The solution uses video feeds to automatically detect manufacturing issues in the plane’s final assembly. As the plane moves through its inspection, the deep-learning AI recognizes when tasks have been completed through motion. For instance, once the wing is attached, it’s noted and timestamped. This is not only a quicker, but also a more efficient way to conduct the final inspection. What’s more, the AI solution gathers and annotates images and video to inspect the proper installation and positioning of the aircraft’s large parts more accurately. All this ladders up to an automated process that frees up time for Airbus’s employees to focus on more meaningful tasks, while the AI solution takes care of the rest.
