Session: CIE-31-02 VARE User Experience (UX) and Human-Machine Interaction

Paper Number: 194100

194100 - Augmented Reality-Assisted Cyber-Physical System for Manual Spray Painting of Complex Geometries 

Spray painting is a manufacturing process commonly used for surface coating in aerospace, automotive, and consumer-product industries. Driven by mass customization, this process requires balancing automation efficiency with human adaptability to achieve high operational flexibility, particularly when handling complex parts. This paper proposes a human-centric cyber-physical system (CPS) framework that leverages augmented reality (AR) to enhance manual spray painting. A prototyping tool is implemented by integrating a spray gun instrumented with IoT sensors and 6-DoF tracking, paint deposition simulation, and an AR headset. The tool increases operator awareness and facilitates timely adjustments to spraying control through real-time visual cues representing the workpiece processing state and operational guidance. To validate the framework, a comparative experiment is conducted involving unassisted, AR-assisted manual spraying, and an autonomous robotic benchmark. Experimental results indicate that while the AR approach requires longer execution times, it enhances coating quality, improving peak tolerance compliance from approximately 70% to over 90%. This study demonstrates that human dexterity supported by real-time AR cues may outperform fully automated solutions in complex manufacturing tasks. Spray painting is a manufacturing process commonly used for surface coating in aerospace, automotive, and consumer-product industries. Driven by mass customization, this process requires balancing automation efficiency with human adaptability to achieve high operational flexibility, particularly when handling complex parts. This paper proposes a human-centric cyber-physical system (CPS) framework that leverages augmented reality (AR) to enhance manual spray painting. A prototyping tool is implemented by integrating a spray gun instrumented with IoT sensors and 6-DoF tracking, paint deposition simulation, and an AR headset. The tool increases operator awareness and facilitates timely adjustments to spraying control through real-time visual cues representing the workpiece processing state and operational guidance. To validate the framework, a comparative experiment is conducted involving unassisted, AR-assisted manual spraying, and an autonomous robotic benchmark. Experimental results indicate that while the AR approach requires longer execution times, it enhances coating quality, improving peak tolerance compliance from approximately 70% to over 90%. This study demonstrates that human dexterity supported by real-time AR cues may outperform fully automated solutions in complex manufacturing tasks

Presenting Author: Jie-Ke Pan National Tsing Hua University

Presenting Author Biography: Jie-Ke Pan is a Ph.D. candidate at National Tsing Hua University. His research focuses on the application of Augmented and Virtual Reality within industrial settings and human-robot collaboration. Leveraging his core expertise in industrial design, system implementation, hardware/software prototyping, and 3-D graphics rendering, he investigates how Mixed Reality can optimize manufacturing and production workflows through the lens of human factors engineering. His broader research interests include experimental design, system integration, robotic path planning, HMI design, innovative product development, and digital fabrication.