MEMBER SPOTLIGHT
HONGYUE SUN
ASME member’s smart manufacturing research is transforming how manufacturers approach efficiency and precision.
Written by Cathy Cecere
From left to right, Minsung Kang, Chenyu Xu, Wuyang Chen, Hongyue Sun, and Nitesh Silwal investigating the autonomous tool path planning and uncertainty quantification for 3D scanning with robotic arm. Photo: University of Georgia
IN THE RAPIDLY ADVANCING AREAS of smart manufacturing and data analytics, Hongyue Sun, an associate professor of mechanical engineering at the University of Georgia in Athens, leads groundbreaking research. His work is transforming how manufacturers approach efficiency, precision, and overall productivity.
Manufacturers today face the dual challenge of maximizing productivity while maintaining consistent product quality. “The increasing reliance on automation and advanced manufacturing processes comes with its own set of challenges, primarily in integrating and analyzing data from multiple sources,” Sun explained. Without seamless data integration, manufacturers struggle to fully optimize their operations.
Sun’s work concentrates on streamlining data-driven decision-making. “By integrating IoT and smart manufacturing technologies, I envision production floors where machines and operators are interconnected,” he said. This real-time data flow enables quick process adaptations, more precise quality control, and significant reductions in downtime. The results for manufacturers are faster production cycles, minimized waste, and substantial cost savings.
INNOVATIVE SOLUTIONS
Sun’s most recent contribution was to the article, “Multiclass Reinforced Active Learning for Droplet Pinch-Off Behaviors Identification in Inkjet Printing,” published in ASME's Journal of Manufacturing Science and Engineering. This work showcases a major leap forward in the additive manufacturing sector, particularly in inkjet printing, which has shown its cost-effectiveness and versatility in diverse applications such as printing electronic and biomedical components.
“Ensuring consistent droplet formation is a significant challenge for reliable product manufacturing,” Sun explained. His research addresses this by proposing a multiclass reinforced active learning (MCRAL) framework, combined with graph convolutional networks (GCNs). This innovative approach allows for automatic and efficient feature extraction from droplet images and minimizes the need for manual image annotation by sequential and iterative model updating and decision-making.
By significantly reducing human annotation efforts, the MCRAL framework ensures high accuracy in classifying various droplet pinch-off behaviors. While it is designed for inkjet printing, the principles behind MCRAL can be adapted to other manufacturing processes with a high annotation cost, which opens doors to process monitoring, optimization, and control.
From left to right, Chenyu Xu, Nitesh Silwal, Hongyue Sun, Minsung Kang, and Wuyang Chen standing next to a summary of their project: Cyber-Coordinated Analytical Framework for Multi-stage Distributed Future Manufacturing Systems. Photo: University of Georgia
THE FUTURE
Looking ahead, Sun foresees a future where manufacturing systems will be increasingly autonomous, with more sophisticated human-machine collaboration. “Manufacturing decision-making will become smarter, integrated, robust, and more secure, pushing the boundaries of what current manufacturing technologies can achieve,” he concluded.
To get there, Sun emphasizes the importance of the role of young mechanical engineers. “Their eagerness to merge traditional engineering knowledge with cutting-edge technologies signals a promising future for manufacturing,” he explained.
Sun’s dedication to blending machine learning with engineering underscores the essential role of interdisciplinary approaches in modern manufacturing research. His contributions not only address pressing manufacturing challenges but also set a benchmark for future innovations in process modeling, monitoring, and control. This approach to engineering will help ensure that manufacturers are well equipped to face the challenges of today and tomorrow.
Cathy Cecere is membership content program manager.
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