Department of Industrial Engineering and Management Receives Second Place and Honorable Mention at the 2026 National Business Management and Interdisciplinary Innovation Project Competition, Demonstrating Excellence in Interdisciplinary Research
Department of Industrial Engineering and Management Receives Second Place and Honorable Mention at the 2026 National Business Management and Interdisciplinary Innovation Project Competition, Demonstrating Excellence in Interdisciplinary Research
Competition Overview
To encourage university students to strengthen their project development, problem-solving, and innovative implementation capabilities, Takming University of Science and Technology organized the 2026 National Business Management and Interdisciplinary Innovation Project Competition. Through a preliminary document review and a final oral presentation, the competition provides a platform for students nationwide to present their research achievements and receive professional feedback from experts. The competition includes three divisions: Quantitative Research Division, Business Planning Division, and Interdisciplinary Project Division, encouraging students to integrate knowledge from business management, information technology, artificial intelligence, design, sustainability, and other disciplines to develop innovative projects with practical application value.
The competition aims to enhance students' abilities in project development, problem analysis, and problem-solving while showcasing their diverse learning outcomes and innovative thinking. Through interaction among participating teams from different universities and guidance from professional judges, the competition promotes practical research, academic exchange, and the integration of theoretical knowledge with real-world applications. It also inspires students and faculty members to engage in research and innovation while cultivating talented professionals with creativity, practical skills, and future competitiveness.
The competition consists of two stages: a preliminary document review and a final oral presentation. The overall results are determined by combining the preliminary review score (30%) and the final presentation score (70%). In particular, the Interdisciplinary Project Division encourages students to integrate expertise from business management, information technology, artificial intelligence, design, and sustainability to develop innovative projects with practical value while responding to emerging industrial trends.
Award Achievement
Students from the Department of Industrial Engineering and Management achieved outstanding results in this year's competition, receiving Second Place in the Quantitative Research Division and an Honorable Mention in the Interdisciplinary Project Division, demonstrating excellence in research, interdisciplinary integration, and project implementation.
Under the supervision of Professor Chien-Chih Wang, Yi-Ling Chen participated in the 2026 National Business Management and Interdisciplinary Innovation Project Competition organized by Takming University of Science and Technology with the research project "Quality Risk Early Warning Model for Low-Carbon Manufacturing: Practical Application of Integrating Carbon Inventory Data with Machine Learning." The project was awarded Second Place in the Quantitative Research Division. By integrating low-carbon manufacturing, carbon inventory data analysis, and machine learning techniques, the study developed a quality risk early warning model, demonstrating the student's research capability in data analytics, sustainable manufacturing, and practical application. This achievement not only recognizes the quality of the research but also reflects the University's commitment to cultivating interdisciplinary talents and promoting industry-oriented research.
Under the supervision of Professor Chien-Chih Wang, Kuan-Yu Chen, Tzu-Tang Tseng, Hsin-Fu Chen, and Ming-Yao Hsu, students from Ming Chi University of Technology, participated in the same competition with the project "An Automated Cafeteria Checkout System Integrating Computer Vision and Semi-Supervised Learning: Toward Fair Pricing and Consistent Service Processes." The project received an Honorable Mention in the Interdisciplinary Project Division.
Award Recipients
Second Place – Quantitative Research Division
- Yi-Ling Chen
- Advisor: Chien-Chih Wang, Ph.D.
Research Highlights
The award-winning project, "Quality Risk Early Warning Model for Low-Carbon Manufacturing: Practical Application of Integrating Carbon Inventory Data with Machine Learning," combines low-carbon manufacturing, carbon inventory data analysis, and machine learning techniques to establish a quality risk early warning model. The research demonstrates the student's capabilities in data analytics, sustainable manufacturing, and the integration of practical applications. This achievement recognizes not only the quality of the research but also the University's efforts in cultivating interdisciplinary talents and promoting industry-oriented applied research.
Honorable Mention – Interdisciplinary Project Division
- Kuan-Yu Chen, Tzu-Tang Tseng, Hsin-Fu Chen, and Ming-Yao Hsu
- Advisor: Chien-Chih Wang, Ph.D.
Research Highlights
The project "An Automated Cafeteria Checkout System Integrating Computer Vision and Semi-Supervised Learning: Toward Fair Pricing and Consistent Service Processes" received an Honorable Mention in the Interdisciplinary Project Division. By integrating computer vision, semi-supervised learning, and food service applications, the research proposes an innovative automated checkout system that addresses inconsistent pricing standards, human judgment variations, and service efficiency issues commonly encountered in cafeteria operations.
The project demonstrates students' capabilities in artificial intelligence applications, information technology integration, service process optimization, and interdisciplinary project development. It also highlights the potential to support digital transformation and intelligent service development across related industries. The award recognizes the team's dedication to research and practical implementation while reflecting the University's success in cultivating students' interdisciplinary integration, innovative thinking, and problem-solving abilities.
Significance of the Award
These achievements demonstrate the Department's commitment to integrating theory with practice while showcasing the dedication of both faculty members and students in project research, data analytics, and interdisciplinary innovation. The Department of Industrial Engineering and Management extends its sincere congratulations to all award recipients and their advisor and looks forward to their continued research excellence and future accomplishments.
Student Remarks
Quantitative Research Division
It is a great honor to participate in the 2026 National Business Management and Interdisciplinary Innovation Project Competition organized by Takming University of Science and Technology and to receive Second Place in the Quantitative Research Division with the project "Quality Risk Early Warning Model for Low-Carbon Manufacturing: Practical Application of Integrating Carbon Inventory Data with Machine Learning."
This competition provided me with an invaluable opportunity to apply classroom knowledge to practical research while exploring the integration of low-carbon manufacturing, carbon inventory data, and machine learning. From data collection and model development to the final presentation, every stage of the project greatly enriched my learning experience.
I would like to express my sincere gratitude to Professor Chien-Chih Wang for his patient guidance and professional advice throughout the research process. His support enabled me to continuously refine the research direction and improve the quality of the project. I am also grateful to the University for providing excellent learning resources and opportunities to participate in this national competition. Receiving this award is not only a recognition of my efforts but also a strong motivation for future growth. I will continue strengthening my expertise in data analytics, sustainable management, and interdisciplinary integration, with the goal of applying my knowledge to industrial practice and contributing to innovations in low-carbon transformation and quality management.
Interdisciplinary Project Division
We are honored to participate in the 2026 National Business Management and Interdisciplinary Innovation Project Competition organized by Takming University of Science and Technology and to receive an Honorable Mention in the Interdisciplinary Project Division with our project "An Automated Cafeteria Checkout System Integrating Computer Vision and Semi-Supervised Learning: Toward Fair Pricing and Consistent Service Processes."
Receiving this award is not only a recognition of our efforts but also an encouragement for continuous learning and improvement. Throughout the project, we integrated computer vision, semi-supervised learning, and food service applications to explore how technology can improve cafeteria checkout processes by enhancing pricing fairness and service consistency. From problem identification and system planning to data preparation, model implementation, and final presentation, every stage strengthened our understanding of interdisciplinary collaboration and practical application while enhancing our teamwork, communication, and problem-solving skills.
We sincerely thank Professor Chien-Chih Wang for his professional guidance and continuous support throughout the project, helping us refine our research direction and improve the quality of our work. We also appreciate the University's abundant learning resources and opportunities to participate in national competitions, allowing us to transform classroom knowledge into practical applications.
This competition has been an invaluable learning experience and has further strengthened our commitment to pursuing interdisciplinary innovation, artificial intelligence applications, and intelligent service development. We will continue improving our professional knowledge and practical skills and strive to develop innovative solutions that address real-world industrial challenges.
