AM Research

Smart language for additive manufacturing could increase efficiency, productivity

Researchers from the University of Huddersfield say a smart language can help designers, engineers and inspectors communicate

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A team of researchers from the University of Huddersfield in England are aiming to help advance the efficiency of additive manufacturing, but not in the way you’d expect. They’re not looking to increase the speed of 3D printers or the quality of prints, rather, they believe that establishing a smart language for additive manufacturing will increase innovation and productivity by making it easier for designers, AM engineers and inspectors to communicate.

One of the key researchers involved in the project is Dr. Qunfen Qi, an expert in the application of mathematics theory and information technology for advanced manufacturing. Dr. Qi recently spoke about her research initiative at the 15th CIRP Conference of Computer Aided Tolerancing hosted in Milan.

There, she explained to various global experts in production engineering how additive manufacturing’s potential was be further maximized through the introduction of a new smart language, largely because the technology itself has introduced wholly new design rules.

smart language

“The research can provide a smart language that enables designers, AM engineers and inspectors to truly communicate with each other in an intelligent, robust and productive way,” Dr. Qi said. “This will greatly improve the process repeatability and part-to-part reproducibility, and significantly reduce power usage and failure rate, lower the cost of production and make a more environmentally-friendly manufacturing technology.”

A research fellow at the University of Huddersield’s EPSRC Future Metrology Hub, Dr. Qi is particularly interested in applying category theory to develop this new AM language for computer-readable guidelines and AM rules. In fact, she has been exploring category theory as a means to create smart databases for over 15 years.

Among her previous achievements in the field was a custom package developed for automotive manufacturer Rolls Royce to help them design and measure surface texture. Her current endeavour is seeking to introduce a smart language which could be used across the additive manufacturing industry.

“It will have an enormous range of applications, not just limited to advanced manufacturing, but in the future—to be applied in smart cities, healthcare, social science and more,” commented Professor Paul Scott, the research director at the EPSRC Centre who supervised Dr. Qi’s PhD.

The recent CIRP conference also saw Professor Scott chair a session on Tolerance Verification and present his paper on partitioning operations for standardisation geometrical product specifications and verification. One Dr. Luca Pagani was also in attendance and presented his work on more efficient production of parts with complex surfaces.

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Tess Boissonneault

Tess Boissonneault is a Montreal-based content writer and editor with five years of experience covering the additive manufacturing world. She has a particular interest in amplifying the voices of women working within the industry and is an avid follower of the ever-evolving AM sector. Tess holds a master's degree in Media Studies from the University of Amsterdam.

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