Since the dawn of manufacturing, designers and engineers have repeatedly run up against limitations to making things. Their ability to execute and capacity to afford bringing their ideas to market were once constrained by the manufacturing facility they had to find--either local or offshore--to build the things they wanted to build. But in a new world of enhanced robotics, factory automation, 3D printing, generative design, and design-make-use convergence, engineers' project limitations will fade away. And it's all because machine learning, computing power, and robots in the workforce are increasingly capable and intelligent. Soon, engineers will be able to design the best thing possible and then hand it to robots to dissect and turn into a series of assembled 3D-printed components.
Currently, creative engineers are forced to build geometry in CAD systems to assess the viability of design ideas. In the future, their time will be better spent analyzing and constructing the problem statement, so computers can generate new geometric options and help engineers iterate faster. As a result, the scope of problems will increase, creating new challenges and opportunities. An example is SpaceX, which successfully landed two rockets on a boat this year (after five failed attempts). What if, at the beginning of the process, the engineers had fed project parameters into a generative-design tool?
Artificial intelligence (AI) has a perception problem, as many people think of the technology primarily as a job killer. However, collaboration between humans and AI opens the opportunity of putting the design and manufacturing of goods of all kinds on a new, better foundation by curating intelligence. That's why we should rethink our expectations for machine intelligence and how it will affect our future. The role of a human as the most intelligent creature on earth may not last much longer. Technologies like artificial intelligence and machine learning are taking on operations that could previously only be conducted with human intelligence – and in some cases they're doing even better than we do.
Designing a building, developing a constructible model from a design or working out how to go about constructing a complicated model are all tasks that already contain some degree of automation. So when researchers and others in the architectural, engineering and construction world start talking about bringing artificial intelligence into the mix, many say it's already here. But recent advances in generative design, safety analysis and 5D scheduling are only the first hints of what sophisticated algorithms and deep-learning AI can bring to construction. Getting smart algorithms and other AI-derived technologies onto the project team may not be as far-fetched an idea as it once was. But rather than having a computer that takes over the existing job duties of an architect or engineer, those professions may soon have some form of AI-based assistant offering options and providing clarifications all along the way.