https://orcid.org/0009-0006-5482-551X
![Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5933/TOC-Subject-Sample-2021-Engineering-Tech.jpg"})
Abstract
In the realm of intelligent manufacturing, driven by the push towards smart factories and Industry 4.0, optimizing technology selection and sequencing is paramount for intelligent transformation. This complex decision-making process resembles a novel project selection and scheduling problem, characterized by Multiplicative Enhancement Effects (MEEs) where the collective benefits of multiple projects can exceed their individual contributions. Additionally, the uncertain duration of projects further adds complexity. Motivated by these practical challenges, a stochastic mixed-integer programming model that incorporates MEEs and uncertain delays is established. A conditional value-at-risk-based risk measure is integrated to control delay risk. The solution approach leverages an efficient branch and bound-based approach with cutting strategies, integrating a sample average approximation framework and a backward labeling algorithm to handle stochastic elements. A real-world technology implementation case study highlights the advantages of considering MEEs, uncovers myopic biases in technology selection, and identifies implementation patterns centred around core Industry 4.0 technologies. This research enhances our understanding of intelligent manufacturing decision-making, offering valuable insights and practical implications for technology-driven transformations.
Additional information
Funding
Notes on contributors
Xiaohang Liu
Xiaohang Liu received the BS degree from the School of Management, Beijing Normal University, Beijing, China, in 2020. He is currently a PhD student in Tsinghua University, major in industrial engineering. His research interests include production and operational management, project planning and scheduling in intelligent manufacturing.
Jingran Liang
Jingran Liang received the BS degree from the department of Industrial and System Engineering, Tsinghua University, Beijing, China, in 2017 and the PhD degree from the department of Industrial Engineering in Tsinghua University, Beijing, China, in 2023. His research interests include operation research, production planing and algorithm development for intelligent manufacturing.
Zhi-hai Zhang
Zhi-Hai Zhang is an associate professor in the Industrial Engineering Department at Tsinghua University. He received his BS and PhD in mechanical engineering from Tsinghua University in 1997 and 2002, respectively. His current research interests focus on production and operational management, resource allocation optimization, supply chain and logistics management, production planning and scheduling, large-scale optimization. He has published numerous articles in journals such as IISE Transactions, Production and Operations Management, Transportation Science, Transportation Research Part B, European Journal of Operational Research, Omega, etc.
Shun Yang
Shun Yang is assistant professor at the Department of Design, Production and Management at the University of Twente. He received his MS and PhD in Mechanical Engineering from the Karlsruhe Institute of Technology. He has diverse experience and solid expertise in global production strategy and intelligent automation, as well as sustainable manufacturing through collaboration with industry. He has published numerous articles in the field of production science, especially in the International Academy for Production Engineering.
Sina Peukert
Dr.-Ing. Sina Peukert is a postdoctoral researcher at the wbk Institute of Production Science of the Karlsruhe Institute of Technology (KIT), where she also completed her doctorate. Her research focuses on the planning, design and management of global production networks as well as on the implementation of digitalization and sustainability in production systems.
Gisela Lanza
Prof. Dr.-Ing. Gisela Lanza is member of the management board at the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology (KIT). She heads the Production Systems division dealing with the topics of global production strategies, production system planning, and quality assurance in research and industrial practice. She is an active member of the Germany Academy of Engineering Sciences (acatech) and the national platform Industrie 4.0, as well as of the Steering Committee of the Allianz Industrie 4.0 Baden-Württemberg. The holistic design and evaluation of production systems is a central research issue in numerous research and joint projects.