University at Buffalo develops AI-based cyber-manufacturing system to increase 3D printing efficiency


A University at Buffalo (UB) research team is harnessing artificial intelligence (AI), simulation and big data tools to modernize manufacturing systems and improve quality, production and efficiency in industries like 3D printing.

Funded by a $2.3 million grant from the National Science Foundation (NSF), the STREAM framework aims to create a public online repository where researchers and industry professionals can share information regarding data, models, simulators, controllers and analyses, as well as a number of other research tasks. .

“A commercial product is the end result of a long chain of intertwined steps that can span geography, industries and different manufacturing processes,” said Hongyue Sun, assistant professor of industrial systems engineering at UB. “Each step can be optimized, but that doesn’t always mean it’s for the greater good of the entire production process. What we do is create an analytical framework that connects and coordinates all of these processes.

“The end result will be a cyber-physical system that uses artificial intelligence and other tools to optimize and ultimately improve manufacturing systems.”

The footprint of a 3D printer. Image via Wenyao Xu, University at Buffalo.

UB’s 3D printing research

UB researchers have previously used AI, machine learning (ML), and other technologies to drive improvements in additive manufacturing processes.

In 2018, a team at UB developed PrinTracker, a 3D printer identification system that can track printed objects back to the machine that created them. As a result, the system could help law enforcement crack down on the potentially unethical and criminal use of 3D printers.

More recently, in 2020, a team from UB worked with MIT to develop a new ferroelectric metamaterial for light-curing 3D printing, marking a “big step” towards making synthetic materials more affordable and suitable for various applications. like electronics.

A 3D printed ferroelectric network. Photo via University at Buffalo.

Modernization of manufacturing systems

The goal of the STREAM framework is to place the complex web of steps and processes within the supply chain under the coordinated control of a sophisticated, connected computer system. The framework will use AI, simulation and other “Industry 4.0” technologies to streamline and connect the various elements of supply chains within industries such as 3D printing and semiconductors.

The supply chains of these sectors have many dependent stages, especially the semiconductor industry.

“It includes dozens of steps such as crystal growth, ingot slicing, wafer lapping and polishing, lithography, etching, chemical mechanical planarization,” Sun said. “These stages have strong dynamics and dependencies. Operations at downstream stages are affected by operations at upstream stages, in terms of quality and productivity.

“For example, multiple honing machines have to collaboratively process hundreds of wafers from ingot slicing; and the real-time process and production information of the machines are interdependent and jointly determine the performance of the system.

Throughout the project, the UB team will create software that enables efficient communication and computing within cyber-manufacturing systems. In addition, the team will produce a modeling system to achieve accurate and efficient process quality control.

The project will also see the creation of a simulation and production control system for the continuous improvement of the quality, manufacturability and productivity of future multi-stage and distributed manufacturing systems.

The ultimate goal of the project is to create an online repository for sharing information and experiences between researchers and industry professionals. The system will facilitate the sharing of knowledge regarding data, models, simulators, controllers, analyzes and empirical studies, with the aim of fostering the future development of highly intelligent and interactive manufacturing ecosystems that integrate design, product production and logistics.

Under the project, UB researchers will create new outreach and workforce development activities for K-12, undergraduate and graduate students, as well as for work with manufacturing professionals.

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Featured image shows the imprint of a 3D printer. Image via Wenyao Xu, University at Buffalo.


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