Next-Gen Smart 3D Printer Automatically Adapts to New Materials

A next-generation smart 3D printer has emerged from MIT, aiming to streamline the adoption of new materials by autonomously adjusting its settings to accommodate varying compositions.

MIT Presents a Smart 3D Printer

Researchers note that the prevalent challenge in contemporary 3D printing lies in the limited recyclability of plastic materials used in fabrication, prompting the exploration of sustainable alternatives.

However, integrating these novel materials into the printing process entails meticulous manual adjustment of up to 100 parameters, posing a significant barrier to their widespread use.

In response to this challenge, a collaborative effort involving researchers from MIT's Center for Bits and Atoms (CBA), the U.S. National Institute of Standards and Technology (NIST), and the National Center for Scientific Research in Greece (Demokritos) has yielded a solution.

They have devised a modification to the extruder, the core component of a 3D printer, enabling it to gauge materials' forces and flow characteristics.

This allows the printer to conduct a 20-minute test during which it gathers data on material properties. Subsequently, a mathematical function processes this data to automatically generate printing parameters, eliminating the need for manual intervention.

These parameters, which encompass crucial factors like flow rate and temperature, can seamlessly integrate with off-the-shelf 3D printing software, enabling the printer to accommodate a diverse array of materials effortlessly.

The researchers claim that this new technology has the potential to alleviate the environmental impact associated with additive manufacturing. By facilitating the use of renewable and recyclable materials, the technology aims to foster sustainability within the 3D printing ecosystem.

Tackling the Complexity of 3D Printing Parameters

The research team, spearheaded by first author Jake Read, a graduate student at CBA, leveraged a multidisciplinary approach to tackle the complexity of 3D printing parameters.

Through the integration of measurement, modeling, and manufacturing, they devised a systematic methodology to address the intricacies of material properties.

Key to this methodology is the incorporation of instrumentation within the printer's extruder, enabling real-time measurement of pressure and flow rate. These measurements serve as inputs for a computational model that derives printing parameters, substantially reducing the manual effort required for parameter tuning.

Despite the complexity inherent in 3D printing processes, the team reports that the method demonstrated remarkable efficacy across various materials, including bio-based polymers and recycled substrates.

Looking ahead, the research team envisions further refinements to their workflow, including seamless integration with existing 3D printing software and incorporation of thermodynamic modeling.

"By developing a new method for the automatic generation of process parameters for fused filament fabrication, this study opens the door to the use of recycled and bio-based filaments that have variable and unknown behaviors," said Alysia Garmulewicz, an associate professor in the Faculty of Administration and Economics at the University of Santiago in Chile who was not involved with this work.

"Importantly, this enhances the potential for digital manufacturing technology to utilize locally sourced sustainable materials."

The findings of the team were published in the journal Integrating Materials and Manufacturing Innovation.