Artificial Intelligence and the coming of the self-designing machine
Manufacturing is in the early stages of a state of disruption brought on by technologies such as artificial intelligence (AI) and 3D printing. “Additive manufacturing” has already worked itself into companies such as Porsche and Bugatti, and aircraft builder Airbus is experimenting with UAV THOR, a drone made entirely of 3D-printed parts. At the same time, AI is coming into play in a number of ways, in everything from analytics to manufacturing robotics. So the “factory of the future,” as envisioned by projects such as the Defense Advanced Research Projects Agency’s Adaptive Vehicle Make program, is one in which software drives the manufacturing process and the factory can be rapidly reconfigured to change what it makes.
AI has increasingly played a role in designing products in the form of generative design software. AI-driven generative design software makes it possible for humans and AI to work together to rapidly consider every conceivable design option and to test them all before choosing one for production.
“In an AI-driven generative design paradigm, humans input design goals and material parameters,” explains Avi Reichental, the CEO and founder of XponentialWorks (a venture investment, corporate advisory, and product development company specializing in artificial intelligence, 3D printing, robotics, and digital transformation). “The software does the rest—exploring nearly infinite design permutations based on existing design concepts. This includes designs that are stronger, lighter and use less material than would be used otherwise to save money, increase scalability, and raise efficiency while enhancing form and function.”
In this increasingly connected manufacturing chain, a product’s form and features don’t even need to be finished when it ships. With just a little Internet access, products themselves are beginning to participate in improving their overall design long after they’ve left the factory. They can, in effect, “phone home” changes to their own design to improve efficiencies or to overcome new or unforeseen obstacles.
Thus, human designers have started seeing their role change: they’re increasingly becoming co-designers for a product’s entire lifespan.
Manufacturing outside factory walls
The freedom for Internet of Things (IoT) devices to co-design, and eventually self-design, on the fly came about because no one told AI that its work had to be confined to an industrial setting. Without such a rule, taking manufacturing on the road became an enticing option in design evolution.
Modern generative design works to continuously improve efficiency, sustainability, and resilience at ever faster speeds. It can use any mix of AI/machine learning, edge computing, the cloud, and additive manufacturing (3D-printing) to quickly develop myriad manufacturing design alternatives. These technologies can also be used to help enable things to execute changes to their own design even when they are far outside their creator’s facilities.
“For example, a robot on Mars might detect very loose sand and determine it cannot move about efficiently to complete its mission,” explains Ben Schrauwen, co-founder and CTO of Oqton, an autonomous manufacturing platform. “The robot could learn to suggest different modalities on how to move in that environment, and, with 3D printing technology and some local robotics, it’s very conceivable that the robot could reconfigure itself at a distance to continue its mission unimpeded.”
Interplanetary travel and space missions aside, there is plenty of motivation to enable things to co-design or self-design here on Earth, too.
“The most exciting change is the embedding of sensors within manufactured items to create a design system that is a self-improving circuit, where the sensors provide feedback to the design to cause it to respond and improve,” said Tod Northman, partner at Tucker Ellis, a law firm with a specialized practice in intellectual property and liability issues concerning autonomous vehicles and other artificially intelligent devices. “Such a system will become a self-improving loop, with better products resulting without human intervention.”
Sometimes that self-improving loop will be adding to the thing’s design to upgrade its functionality and features. But sometimes, it will suggest a design change meant to affect a real-time repair. For example, if a robot were to break a leg or a vehicle to blow a tire or break an axle, a truly AI-driven thing could adjust its design to create a different form of mobility and continue on its way.
Simply put, the day is coming when manufacturing becomes autonomous—a time when anyone can manufacture anything on a home or regional 3D printer by selecting base models from a store and adding customizations as desired. Or, soon customers may simply give the AI a general description of a design or a product’s function they want made. The AI will then take care of everything else from material selection and supply chain activation to design optimization and manufacturing processes.
“You won’t have to tell it that your design needs to be this material or that material or it needs to be printed or machined. You’re only interested in the end performance of the part, the function it needs to do in the world, and that’s what you tell the system,” says Schrauwen. “The system then figures out whatever material and tools are available locally and how it can deliver on that requirement.”
While machines will do this work, don’t expect conformity in their outputs. “You might order the same part from five different small factories and you might get five different parts, but they still have the same function in the world,” Schrauwen added.
When presented with a variety of things that all meet your requirement or desire, you’re bound to have preferences among them. And with preference comes branding so that you can easily find that preferred make again. In that way, an AI-future for manufacturing may not look so different: “AIs could develop their own brands and fan bases,” as Schrauwen puts it.
