Read the complete Boeing case study, here.
Boeing manufactures the 787 Dreamliner, an aircraft made using advanced materials known as ply composites. Ply composites are lightweight, safe, and strong, enabling these jets to fly further and consume less fuel. But designing aircraft components using ply composites is a complex problem.
Each component is composed of thousands of individual plies — long strands of strong material, layered across one another like fabric. Each strand is strong in one direction. Building a strong component with the right properties out of plies requires careful arrangement, placing each strand at just the right angle relative to the ones next to it.
For a large aircraft component, all of those decisions about the angles of ply strands can add up to 100,000 variables. There are no known methods for solving such complex problems all at once on classical computers, so engineers break the problems up into digestible pieces. Then they bring all the pieces together, following strict safety and design rules, at the end of the process. This approach is effective and safe, but takes extra time and money.
The Boeing and IBM teams ran what was at the time the largest binary optimization problem ever handled by a quantum computer.
IBM is building quantum computers to solve complex problems with lots of variables. While quantum computers haven’t yet reached the scale necessary to support the design of an entire aircraft component, IBM Quantum and Boeing scientists showed how quantum computers might support this kind of aerospace engineering in the future.
Together, the Boeing and IBM teams ran what was at the time the largest binary optimization problem ever handled by a quantum computer: a small version of Boeing’s ply composite problem. Through the collaboration, Boeing’s team developed quantum skills and capabilities. As quantum computers scale, Boeing will be ready to take advantage of the opportunities they offer.
To learn more, watch the case study video and read the full story.
