Science Talk: Quality control key to solving 3D printing pain points

In fields as demanding as aerospace and medical devices, the production of complex components often presents significant challenges. 3D printing, or additive manufacturing, has emerged as an effective solution, offering greater freedom in design, superior capability for intricate shapes and improved material efficiency compared with traditional subtractive methods.

According to a recent report by market researcher VoxelMatters, the technology produced nearly 37 million consumer product parts in 2023, representing a 23 percent increase over the previous year.

Despite these advances, mass production faces critical obstacles such as quality instability and the inability to detect defects in real time, resulting in costly scrapped parts.

An undetected gas pocket in a complex engine component can invalidate an entire build, leading to losses that may amount to millions of yuan and waste months of effort.

To address these challenges, research teams at Xi'an Jiaotong University have developed a laser-based monitoring system supported by national key research and development projects.

This system captures acoustic, optical, thermal, magnetic and electrical signals during the printing process, and uses artificial intelligence-driven image recognition to detect defects with up to 95 percent accuracy. Real-time monitoring enables immediate intervention to correct errors, minimize material waste and ensure consistent quality.

Already adopted across the aerospace industry and exported to markets such as Austria, this AI-enhanced monitoring technology is recognized by institutions like the National Institute of Standards and Technology in the United States as essential for scaling additive manufacturing. As companies increasingly pair their printers with monitoring systems, this breakthrough is poised to transform 3D printing from a prototyping tool into a reliable solution for large-scale production.

Liu Tingyu contributed to this story.