FCU Wins National AI Automation Competition Championship for Second Consecutive Year

Feng Chia University achieved an outstanding result at the 15th National Collegiate AI Automation Equipment Innovation Competition, organized by Gallant Precision Machining Co., Ltd., earning one championship and two honorable mention awards. With three winning projects in a single year, Feng Chia University received more awards than any other institution in this year’s competition, demonstrating its strong research and development capabilities in AI-driven smart manufacturing.

Following the championship-winning project RoadScan Pro in 2025, FCU has now claimed the competition’s top prize for two consecutive years. Among the highlights of this year’s event was Chun-Yu Hung, a student from the Department of Information Engineering and Computer Science, who contributed to both championship teams—RoadScan Pro in 2025 and InsightWafer in 2026.

Championship Project: InsightWafer

The winning project, InsightWafer: Wafer Defect Identification and Feedback System, was jointly advised by Feng-Jeng Lin of the Department of Information Engineering and Computer Science and Tzu-Wang Shen of the Department of Automatic Control Engineering.

The interdisciplinary team consisted of Chun-Yu Hung, Hsing-Hao Yeh, and Chih-Chia Fan from the Department of Information Engineering and Computer Science, together with Yun-Ching Pu from the Department of Automatic Control Engineering.

InsightWafer addresses a critical challenge in semiconductor manufacturing. Existing automated optical inspection systems can identify defect locations but often cannot determine the underlying causes of defects. Traditional contact-based inspection methods may also damage increasingly thin wafers during the inspection process.

To overcome these limitations, the team developed a fully optical, non-contact inspection solution that integrates automated machinery with AI-driven analysis into a closed-loop system. The platform enables manufacturers to transition from reactive defect management to proactive detection and compensation.

An interdisciplinary team consisting of Chun-Yu Hung, Hsing-Hao Yeh, and Chih-Chia Fan from the Department of Information Engineering and Computer Science, together with Yun-Ching Pu from the Department of Automatic Control Engineering, won the championship at the 15th National Collegiate AI Automation Equipment Innovation Competition.

The system was specifically designed with small and medium-sized semiconductor manufacturers in mind. By simply adding a 3D-printed mounting structure to existing manual microscopes, companies can upgrade to a semi-automated inspection platform without purchasing entirely new equipment. The AI engine automatically identifies defects, traces potential process-related causes, and generates analytical reports. Before wafers proceed to the next production stage, the system can recommend appropriate compensation measures.

All computations are performed locally to ensure process data security, and engineers must approve every compensation action before implementation, balancing operational efficiency with safety and quality control.

Honorable Mention: AI-Powered Robotic Dog Inspection Platform

One of the honorable mention projects, Smart Inspection and Cyber-Physical Integration Platform Driven by a Biomimetic Robotic Dog, focused on sewer infrastructure inspection.

Sewer environments are often narrow, dark, humid, and potentially hazardous, making manual inspections both risky and dependent on individual expertise. The system uses a robotic dog equipped with sensors to identify cracks and structural damage in real time. It also incorporates NVIDIA Omniverse digital twin technology to simulate and validate inspection workflows before field deployment, reducing testing costs and operational risks.

The project was developed by Ching-Tai Chang, Yen-Cheng Peng, Hung-Yu Chou, and Cheng-Tai Chiang from the Department of Information Engineering and Computer Science.

Students Ching-Tai Chang, Yen-Cheng Peng, Hung-Yu Chou, and Cheng-Tai Chiang from the Department of Information Engineering and Computer Science received an Honorable Mention for their project, Smart Inspection and Cyber-Physical Integration Platform Driven by a Biomimetic Robotic Dog.

Honorable Mention: AIoT Water Quality Prediction and Automated Control

Another honorable mention project, Machine Learning-Based AIoT Water Quality Prediction and Intelligent Automated Control, addressed water quality management for eel aquaculture.

Traditional aquaculture operations often rely on manual inspections and reactive interventions after water quality has already deteriorated. To improve risk management, the system continuously monitors factors such as water temperature, dissolved oxygen, and pH levels through multiple sensing nodes.

Using machine learning algorithms, the platform predicts water quality conditions up to six hours in advance, issues graded alerts, and automatically activates aerators, pumps, and other equipment when necessary. This predictive approach transforms aquaculture management from crisis response to proactive prevention, helping reduce production losses.

Students Yung-Tu Huang, Che-Kai Chiang, and Yu-Cheng Hsiao from the Department of Information Engineering and Computer Science, along with Yen-Ching Lai and Yu-Chun Chou from the Department of Automatic Control Engineering, received an Honorable Mention for their project, Machine Learning-Based AIoT Water Quality Prediction and Intelligent Automated Control.

The team consisted of Yung-Tu Huang, Che-Kai Chiang, and Yu-Cheng Hsiao from the Department of Information Engineering and Computer Science, together with Yen-Ching Lai and Yu-Chun Chou from the Department of Automatic Control Engineering.

Advancing AI Talent Through Practice-Oriented Education

Professor Feng-Jeng Lin noted that both teams under his supervision focused on solving real industrial challenges. From hardware redesign and algorithm development to complete system deployment, the projects demonstrated comprehensive engineering thinking and strong execution capabilities.

He emphasized that winning the championship for two consecutive years not only validates students’ research achievements but also highlights Feng Chia University’s strengths in interdisciplinary integration and practice-oriented education.

Feng Chia University has long promoted the CDIO (Conceive–Design–Implement–Operate) engineering education model, encouraging students to apply AI, automation, and mechatronics technologies to real-world projects while strengthening collaboration with industry partners. The accomplishment of earning three awards and securing back-to-back championships once again illustrates FCU’s success in cultivating practical talent for the rapidly evolving AI smart manufacturing sector.

List of winners of the 15th National College AI Intelligent Automation Device Creation Award from Feng Chia University

第一名｜InsightWafer：晶圓異常辨識與回饋系統

指導教師：資訊系林峰正、自控系沈祖望
參賽學生：資訊系洪群彧、葉星豪、范秩嘉；自控系卜云晴

佳作｜仿生機器狗驅動之智慧巡檢與虛實整合平台系統
指導教師：資訊系林峰正、張弘豫
參賽學生：資訊系張景泰、彭彥程、周竑宇、江承泰

佳作｜基於機器學習之AIoT水質預測與智動化控制
指導教師：資訊系林哲維、自控系黃清輝
參賽學生：資訊系黃永都、江喆楷、蕭育承；自控系賴彥璟、周于鈞