Intelligent Engineering and Management for Industry 4.0

Industry 4.0 is changing how we manage operations to drive systems more intelligently. Technologies and applications are rapidly evolving. Disruptive technologies, such as artificial intelligence, big data, cloud computing and digital twin, are shaking up different industries and have motivated us to revisit engineering and management tools for improving system design, efficiency, effectiveness, reliability, and responsiveness. While these emerging technologies have powered new applications, novel industrial engineering methodologies are required to achieve the goals.

Industrial Engineering was sprouted from major engineering disciplines that called for better professional understanding of industrialization. Ever since, the discipline of Industrial Engineering has been the star role player in confronting emerging industries; be it manufacturing, service, high tech products, outer space technology, information technology, industrial policy, ergonomics, and now the world's greatest concern, sustainable development.

This book presents the state-of-the-art in industrial engineering research from different countries and cities around the globe. The book covers a wide range of topics in industrial engineering, including: Demand Chain Management, E-business / Information Technology, Evolutionary Algorithm, Green Manufacturing/Management, Health Care Systems and more.

Presents the state of the art in Industrial Engineering research Editors are all from the University of Hong Kong, one of the world's best Industrial Engineering programs Covers a wide range of topics

Auteur

Yong-Hong Kuo is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned his M.Phil and Ph.D. in Systems Engineering & Engineering Management at the Chinese University of Hong Kong. His research spans theory and actual application of mathematical modeling and optimization for decision problems encompassing the eld of operations research & management science with a focus on discrete optimization, system simulation, and simulation optimization. He is on the Editorial Advisory/Review Boards of Decision Sciences Journal and Transportation Research Part E.

Yelin Fu is a Post-doctoral Fellow at the Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong. Dr. Fu earned two Ph.D. degrees from the College of Business, City University of Hong Kong, and School of Management, University of Science and Technology of China. Dr. Fu does research in multiplecriteria decision analysis, robust optimization, composite indicators methodology and e-commerce logistics.

Peng-Chu Chen is an Assistant Professor in the Dept. of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned his Ph.D. in Industrial Engineering at Purdue University and his M.S. in Transportation Engineering at the University of California, Berkeley. He is a member of both INFORMS and SIAM.

Calvin Ka-lun Or is an Associate Professor in the Dept. of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned his Ph.D. in Industrial and Systems Engineering at the University of Wisconsin-Madison and his M.S. in Industrial Engineering at Mississippi State University. He was President of the Hong Kong Ergonomics Society from 2019-2021. He is an Editor for Applied Ergonomics Journal and is on the Editorial Board for various ergonomics and health informatics journals.

George G.Huang is Chair Professor and Head of Department in the Department of Industrial and Manufacturing Systems Engineering at The University of Hong Kong. He earned his BEng and PhD in Mechanical Engineering from Southeast University (China) and Cardiff University (UK) respectively. He has conducted research projects in the field of Physical Internet for Smart Manufacturing and Logistics with substantial government and industrial grants. He has published extensively including over two hundred refereed journal papers in addition to over 200 conference papers and ten monographs, edited reference books and conference proceedings.

Junwei Wang is an Assistant Professor in the Dept. of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned a Ph.D. at the University of Saskatchewan, Canada and another at Northeastern University, China. His research interests include Transportation Systems, Modeling and Optimization.

Contenu
Chapter 1: A Batch Scheduling Model for a Three-Stage Flowshop With Batch Processor and Heterogeneous Job Processor to Minimize Total Actual Flowtime.- Chapter 2: Batch scheduling of unique and common components for a three-stage hybrid flow shop processing different product types with multiple due dates to minimize total actual flow time.- Chapter 3: Interactive scheduling for a dual resource constrained job shop with manual and automated work units.- Chapter 4: Big Data-Based Similarity Network Model for Cloud Manufacturing Services.- Chapter 5: Evaluation methods for the reliability of a linear connected-(1, 2)-or-(2, 1)-out-of-(m, n):F lattice system.- Chapter 6: Exact Solution Method for Balancing of a Self-Balancing Production Line with Worker- and Station-Dependent Speed.- Chapter 7: A Novel Bi-Encoded NSGA-II for A DRC Scheduling Problem to Minimize the Makespan and Unbalanced Workload.- Chapter 8: A Study on Optimal Limit Order Strategy using Multi-Period Stochastic Programming considering Nonexecution Risk.- Chapter 9: Banking the Unbanked: The Fintech Revolution.- Chapter 10: Adaptive Intelligent Redeployment Strategy for Service Parts Inventory Management: A Case Study of a High-tech Company.- Chapter 11: Rehabilitation Staff Scheduling Problem Considering Mental Workload in Elderly Daytime Care Facility.- Chapter 12: Knowledge Management and Open Innovation for Improving Social Performance of Small and Medium Industry: A Pilot Study.- Chapter 13: A Design Method of the Joint Venture Formation in EPC Projects.- Chapter 14: The Importance of Information Sharing in Blanket Order: Case Studies of System Dynamics Simulation.- Chapter 15: Multi-objective Robust Optimization for the Design of Biomass Co-firing Networks.- Chapter 16: Co-Evolution Theory Based Collaborative Conceptual-Embodiment CAD System. <p