MIT researchers have automated the process to determine ideal parameters that consistently print a new material effectively using artificial intelligence. They created a machine-learning system that watches the manufacturing process using computer vision and corrects handling faults in real-time. They put the controller on a real 3D printer after using simulations to teach a neural network how to change the printing parameters to reduce error. Compared to other 3D printing controllers, their technology produced items more correctly. [1]

Figure 1. Using artificial intelligence to control digital manufacturing

Figure 1 shows they used simulations to teach a neural network how to adjust printing parameters to minimize error, and then applied that controller to a real 3D printer. Their system printed objects more accurately than all the other 3D printing controllers they compared it to.

The work avoids the prohibitively expensive process of printing thousands or millions of real objects to train the neural network. And it could enable engineers to more easily incorporate novel materials into their prints, which could help them develop objects with special electrical or chemical properties. It could also help technicians make adjustments to the printing process on-the-fly if material or environmental conditions change unexpectedly. [2]

AI in Digital Manufacturing:

Artificial Intelligence is not a silver bullet; no solution will solve all, or most, of your problems. As a rule of thumb, AI works best when it is applied to solving a specific problem, or a very closely-related set of problems. “General AI” is something to be wary of: if a vendor claims to do everything, then they probably do nothing particularly well.

Which brings us back to the topic of AI in manufacturing. There are numerous potential applications for AI and Machine Learning in manufacturing, and each use case requires a unique type of Artificial Intelligence.

In the guide below, we present a simple, effective formula to selecting the right Industrial AI solution to address your specific manufacturing challenges and goals — focusing specifically on Machine Learning AI, since that is where the most exciting and impactful innovations are occurring. [3]

When they tested the controller, it printed objects more accurately than any other control method they evaluated. It performed especially well at infill printing, which is printing the interior of an object. Some other controllers deposited so much material that the printed object bulged up, but the researchers’ controller adjusted the printing path so the object stayed level. [4]

References:

1. https://www.electronicsforu.com/news/whats-new/digital-manufacturing-management-using-artificial-intelligence
2. https://www.sciencedaily.com/releases/2022/08/220802175834.htm
3. https://www.seebo.com/machine-learning-ai-manufacturing/
4. https://indiaeducationdiary.in/massachusetts-institute-of-technology-using-artificial-intelligence-to-control-digital-manufacturing/

Cite this article:

Thanusri swetha J (2022), Using artificial intelligence to control digital manufacturing, Anatechmaz, pp.153