OSU research collaboration looks to advance smarter multi-material 3D printing 

Thursday, September 24, 2026

Media Contact: Tanner Holubar | Communications Specialist | 405-744-2065 | tanner.holubar@okstate.edu

Few manufacturing technologies have revolutionized how quickly products can be designed and produced as much as 3D printing. By building objects layer by layer, additive manufacturing can create complex shapes and customized components that would be more difficult to produce through conventional manufacturing methods.

But researchers are looking for ways to make the process smarter.

A research collaboration between Oklahoma State University and Mississippi State University is looking to combine multi-material 3D printing with sensors and machine learning to create a more intelligent and adaptable manufacturing process.

Dr. Wenmeng Tian, associate professor in the School of Industrial Engineering and Management, is the co-principal investigator on a National Science Foundation project titled “MRI: Track 1 Development of Machine-Learning Assisted Continuous Fiber Deposition for Multi-Material Additive Manufacturing.”

Unlike many research endeavors that yield new discoveries, this project will result in the development of new technology. The OSU team will develop sensing and machine-learning modules to enable in situ analysis and optimization of the novel 3D printer.

"This project provides us with opportunities to develop a brand-new 3D printing system that is not currently available on the market,” Tian said. “What makes this project special is that this newly developed system can enable new knowledge discoveries by researchers anywhere in the U.S. The ultimate goal is to develop a new multi-material additive manufacturing device that provides unique capabilities for simultaneous multi-material deposition with sensing and machine-learning-assisted quality control and optimization capabilities.”

One key difference will be the use of continuous fiber alongside polymer materials.

Continuous fiber gives printed materials more customizable mechanical properties, thereby expanding the potential uses of 3D printing. Instead of being limited to a single material, researchers will be able to combine different materials and fibers to create composite structures with highly customizable properties.

"The new 3D printing system will enable simultaneous deposition of polymer materials and continuous fibers in multi-material composite structures, providing unique customization of material properties," Tian said.

The system will also allow a single machine to perform multiple printing processes. Conventional 3D printers generally can't integrate multiple processes and materials into a single system, which limits the potential for multi-process, multi-material manufacturing.

The new equipment will integrate multiple 3D printing heads capable of depositing different materials within the same composite build. This newfound flexibility could allow researchers to create parts that would not be possible using conventional 3D printing. This could allow the printing of components for soft robotics, flexible electronics, functional devices and smart structures.

But the printer's ability to incorporate multiple materials into the process is only one aspect of what makes this research different.

Machine learning will enable the printer to assess the quality of each component as it’s made by using data it collects during the printing process. The system will help researchers understand how the printing process affects the structure and performance of the final product. Instead of simply printing a design and evaluating it after the build finishes, the system can use process data to improve the design, optimize how it is printed and quickly identify quality issues.

IEM students will have the chance to assist with sensor selection and allocation, experimental design and machine learning-enabled data analytics to link process-structure-property relationships for the complex system being developed.

"All these training opportunities will prepare them with first-hand experience of manufacturing and data science for their future career,” Tian said.

This new printing system will be a regional and national research hub that supports a variety of science and engineering disciplines through collaborative access across industries and universities.

“The new hybrid additive manufacturing platform will also enable high-fidelity production of next-generation composites, supporting diverse applications from aerospace structures to bio-integrated devices and reinforcing the U.S. leadership in smart, sustainable manufacturing technologies,” Tian said.

This project reflects OSU’s broader commitment to translating research into practical solutions while preparing students to contribute to the technologies shaping the future of additive manufacturing.