> Many of the problems such as parts that don't fit and supply chain problems could be solved by current machine learning techniques.
How? I know a bit of ML but don't understand what you're saying.
How? I know a bit of ML but don't understand what you're saying.
But in general, the problem involves doing pattern detection between possible designs and their quality metrics. When the whole thing is in software the designs can be verified ahead of time. For instance, you can create a language for designing airplane wings, and then the optimizer can generate potentially good designs, they can be verified to be manufacturable, and then they can be fed into a virtual wind tunnel to figure out if the design performs well. They can also be scored by things like weight and cost to manufacture. Let the optimizer iterate a few thousand times and you're really doing a machine learning problem where the blueprints and the quality metrics are the data set.
If aircraft were machined out of a single block of material into an ideal structure and didn't have a million systems on board, designed by thousands of people trying to cooperate together best they can, you might have a chance.
GAs etc, are useful for small tasks here and there, but at the end of the day how the aircraft gets made and what goes wrong comes down to politics, people, communication, arcane processes and documents, money, time, regulations, rules of thumb etc etc etc
But the problem also could have been solved with good management and communication. Give employees the power to communicate and raise issues/questions.