工管系榮獲2026全國商管暨跨域創新實務專題競賽第二名及佳作 展現跨域研究實力

 

競賽說明

為鼓勵大專校院學生提升專題製作、問題解決及創新實作能力，德明財經科技大學舉辦「2026全國商管暨跨域創新實務專題競賽」，透過書面審查及決賽口頭發表，提供全國學生交流研究成果與接受專業評審指導的平台。競賽並設立量化研究組、商務企劃組及跨域專題組，鼓勵學生整合商管、資訊、人工智慧、設計及永續等不同領域知識，發展具創新性與實務應用價值之專題成果。

本競賽旨在透過專題競賽之辦理，提升學生專題製作、問題分析與解決能力，並展現其多元學習成果與創新思維。藉由各校參賽學生之交流觀摩，以及專業評審之回饋與指導，促進實務研究發展與學術經驗互動，強化理論知識與實務應用之連結，進而激發師生學習動能、帶動整體研究風氣，培育具備創新能力、實作能力與未來競爭力之優質人才。本競賽分為初賽與決賽兩階段辦理，初賽採書面審查方式進行，決賽則以口頭發表方式評選；競賽組別包含量化研究組、商務企劃組及跨域專題組。其中，「跨域專題組」鼓勵學生整合商管、資訊、AI、設計、永續等不同領域知識，發展兼具創新性與實務應用價值之專題成果，以培養跨域整合能力，並回應當前產業發展趨勢。競賽總成績由初賽與決賽成績合併計算，初賽書面審查成績占30%，決賽口頭發表成績占70%。

 

獲獎說明

本系學生於本屆競賽表現優異，共榮獲一項第二名及一項佳作，展現學生在研究分析、跨域整合及專題實作方面的優異能力。

陳誼玲學生於王建智老師指導下，參加德明財經科技大學舉辦之「2026全國商管暨跨域創新實務專題競賽」，以專題作品「低碳製造下的品質風險預警模型：整合碳盤查資料與機器學習之實務應用」參賽，榮獲「量化研究組第二名」佳績。該專題結合低碳製造、碳盤查資料分析與機器學習技術，建構品質風險預警模型，展現學生於資料分析、永續製造與實務應用整合上的研究能力。此次獲獎不僅肯定學生專題研究成果與創新思維，也彰顯本校在培育跨域實務人才及推動產學應用研究方面之成效。

明志科技大學學生陳冠佑、曾子堂、陳信甫、徐名曜，在王建智老師指導下，參加德明財經科技大學舉辦之「2026全國商管暨跨域創新實務專題競賽」，以專題作品「融合電腦視覺與半監督式學習之自助餐自動化結帳系統：邁向計價公平性與服務流程一致性」參賽，榮獲「跨域專題組佳作」之肯定。

 

獲獎名單

量化研究組 第二名

• 陳誼玲同學
• 指導教授：王建智老師

 

研究成果介紹

專題作品「低碳製造下的品質風險預警模型：整合碳盤查資料與機器學習之實務應用」參賽，榮獲「量化研究組第二名」佳績。該專題結合低碳製造、碳盤查資料分析與機器學習技術，建構品質風險預警模型，展現學生於資料分析、永續製造與實務應用整合上的研究能力。此次獲獎不僅肯定學生專題研究成果與創新思維，也彰顯本校在培育跨域實務人才及推動產學應用研究方面之成效。

跨領域專題組 佳作

• 陳冠佑、曾子堂、陳信甫、徐名曜同學
• 指導教授：王建智老師

 

研究成果介紹

以專題作品「融合電腦視覺與半監督式學習之自助餐自動化結帳系統：邁向計價公平性與服務流程一致性」參賽，榮獲「跨域專題組佳作」之肯定。本專題結合電腦視覺、半監督式學習與餐飲服務流程應用，針對自助餐結帳過程中可能面臨之計價標準不一、人工判斷差異及服務效率等問題，提出具創新性與實務價值的自動化結帳系統構想。研究成果展現學生於人工智慧應用、資訊科技整合、服務流程優化及跨域實作方面之能力，並具備回應產業數位轉型與智慧服務發展趨勢之潛力。此次獲獎不僅肯定參賽學生在專題研究與實務應用上的努力成果，也彰顯本校培育學生跨域整合、創新思考與問題解決能力之成效。

 

獲獎意義

此次獲獎不僅展現本系重視理論與實務並重的教學成果，也彰顯師生於專題研究、資料分析及跨域創新應用之努力與成果。工管系全體師生恭賀獲獎同學與指導教授，並期許未來持續精進研究能量，再創佳績。

 

獲獎感言

量化研究組：很榮幸能參加德明財經科技大學舉辦之「2026全國商管暨跨域創新實務專題競賽」，並以「低碳製造下的品質風險預警模型：整合碳盤查資料與機器學習之實務應用」獲得量化研究組第二名的肯定。此次競賽讓我有機會將課堂所學應用於實務研究，並深入探討低碳製造、碳盤查資料與機器學習之間的整合應用，從資料蒐集、模型建構到成果發表的過程中，皆使我獲益良多。

能夠獲得此項榮譽，首先要感謝指導老師王建智老師在研究過程中給予耐心指導與專業建議，使我能逐步修正研究方向並提升專題品質。同時也感謝學校提供良好的學習資源與支持，讓我有機會參與全國性競賽，拓展視野並累積實務經驗。此次獲獎對我而言不僅是一份肯定，更是一項鼓勵。未來我將持續精進資料分析、永續管理與跨域整合能力，期許能將所學應用於產業實務，為低碳轉型與品質管理創新貢獻一份心力。

跨領域專題組：很榮幸能參加德明財經科技大學舉辦之「2026全國商管暨跨域創新實務專題競賽」，並以專題作品「融合電腦視覺與半監督式學習之自助餐自動化結帳系統：邁向計價公平性與服務流程一致性」榮獲跨域專題組佳作。此次獲獎對我們而言，不僅是一份肯定，更是持續精進與學習的重要鼓勵。在專題製作過程中，我們嘗試將電腦視覺、半監督式學習與餐飲服務情境相結合，思考如何透過科技應用改善自助餐結帳流程，提升計價公平性與服務一致性。從問題發想到系統規劃、資料整理、模型應用與成果發表，每一個階段都讓我們更加了解跨域整合與實務應用的重要性，也培養了團隊合作、溝通協調與問題解決能力。特別感謝指導老師王建智老師在專題研究過程中給予專業指導與建議，協助我們釐清研究方向並持續修正專題內容；同時也感謝學校提供學習資源與參賽機會，讓我們能夠將課堂所學實際應用於競賽與專題研究之中。此次參賽經驗讓我們收穫良多，也更加確立未來持續投入人工智慧應用、智慧服務與跨域創新領域的學習方向。未來我們將以此次獲獎作為前進的動力，持續提升專業能力與實作經驗，期許能將所學應用於實際產業問題，創造更具價值的解決方案。

 

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.