Proceedings of Industrial Engineering and Management

International Conference on Smart Manufacturing, Industrial & Logistics Engineering and Asia-Pacific Industrial Engineering and Management Systems Conference
Erscheinungsjahr 2026
ISBN: 978-981-9202-12-6
Verlag: Springer Verlag, Singapore

Buch, Englisch, 1017 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Mechanical Engineering

This book is a compilation of selected papers from the 25th Asia-Pacific Industrial Engineering and Management Systems Conference (APIEMS2025) & the 4th International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE2025). The book focuses on the recent theoretical and methodological developments, significant technical applications, case studies and survey results in the areas of Industrial Engineering, Artificial Intelligence, Smart Manufacturing, Ergonomic/Human Factor, Production and Operation Management, Sustainability Development, Big data analytics & data mining, modelling and decision analysis, Internet of Things, green supply chains and intelligent logistics, and Circular Economy. The contents make valuable contributions to academic researchers, engineers in industrial engineering, smart manufacturing, and logistics. As well, readers will encounter new ideas to promote the application and development of Artificial Intelligence.

Zielgruppe

Research

Autoren/Hrsg.

Chien, Chen-Fu

Dou, Runliang

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Einkauf, Logistik, Supply-Chain-Management
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik

Inhaltsverzeichnis

Study of SPC control charts for non-homogeneous continuous production: a case study of the filament making process in a cigarette factory.- Application of Six Sigma DMAIC to Reduce Inventory Cost in Small Enterprise: A Dried Food Case Study.- Data-Driven Modeling of Multi-Factory Production Systems with Tran, Product-mix and Re-entrant flows.- Metal Processing Scheduling Problem Using Semi-Automatic Machines.- Fine-Tuning Large Language Models for Algorithm Selection in the Flexible Job Shop Scheduling Problem.

Über Autor(innen)

Prof. Chen-Fu Chien is the President of Zhen Ding Technology Group (ZDT). Before joining ZDT, he was the Executive Vice President of National Tsing Hua University and Tsing Hua Chair Professor in the Department of Industrial Engineering and Engineering Management. He is the Director of the Artificial Intelligence for Intelligent Manufacturing Systems (AIMS) Research Center, and the founding Director of Decision Analysis Lab (DALab) in National Tsing Hua University. His research focuses on developing better analytical solutions via AI, big data analytics, digital decision, and optimization algorithms for critical decision problems involved in strategy, manufacturing, and technology that are characterized by uncertainty and a need for trade off among various objectives to empower flexible decisions in real settings.

Prof. Runliang Dou is the Dean of Department of Industrial Engineering in Tianjin University and in Tianjin Key Laboratory of Complex Management System. Prof. Dou also serves as Secretary General in Chinese Industrial Engineering Institution, CMES and Global Forum for Chinese Industrial Engineering Department Heads; committee member in Industrial Big Data and Intelligent System Institution, CMES and Vice-president in Asia Pacific Industrial Engineering and Management Society. His research interests mainly focus on Big Data Analytics and Intelligent Decision, Machine Learning and Data Mining, Product and Service Innovation, and Customer Demand Analytics.