Human Behavior Modelling in Engineering Management under Industry 4.0
1Central South University, Changsha, China
2City University of Hong Kong, Hong Kong
3Xi'an University of Architecture and Technology, Xian, China
4China University of Mining and Technology, Xuzhou, China
5London South Bank University, London, UK
Human Behavior Modelling in Engineering Management under Industry 4.0
Description
Human society is entering the era of Industry 4.0. Automatic production and intelligent manufacturing are proliferating rapidly across industries, freeing the workforce from simple but repetitive work. The roles of humans in engineering systems are continuously changing. In addition, engineering systems are becoming more intelligent and complex, which further increases the difficulties in engineering management. Engineering management is facing unprecedented opportunities and challenges. As humans are the most important and determining factor of management, human behavior can significantly affect the efficiency of engineering management.
However, it is usually not easy to understand the mechanism of decision-making process and human behavior in engineering management. This often requires interdisciplinary knowledge in engineering, management, neural engineering, mathematics, and psychology. Efficient tools for human behavior modelling and simulation are urgently needed. With the development of mathematical algorithms and computational technologies, intelligent modelling and simulation bring innovation to research on human behavior in engineering management. Specifically, advanced modelling and simulation methods, such as machine learning, deep learning, big data, system dynamics, and agent-based modelling, enable revealing the mechanism of decision-making process and predicting human behavior under various circumstances. Intelligent modelling and simulation provide valuable information and databases for managers to improve the efficiency of engineering management. There should be continuous research exploring applying intelligent techniques to model and simulate human behavior in engineering management.
The aim of this Special Issue is to solicit research and offer a timely opportunity to scholars and industry practitioners to discuss, share, and disseminate current innovations in intelligent modelling and simulation techniques for human behavior in engineering management under Industry 4.0. Authors are invited to present original research and review articles that will stimulate continuing efforts in this field. We hope that this Special Issue helps solve practical engineering problems and bring theoretical contributions.
Potential topics include but are not limited to the following:
- Human behavior changes in engineering management under Industry 4.0
- Intelligent modelling and simulation methods for human behavior in engineering management
- Dynamic relationships between human behavior and the efficiency of engineering management under Industry 4.0
- Machine learning and deep learning for human behavior in engineering management
- Data mining for human behavior in engineering management
- System dynamics for human behavior in engineering management
- Agent-based modelling for human behaviour in engineering management
- Complex employee relationship network modelling in engineering management under Industry 4.0
- Intelligent prediction, monitoring, assessment, and management of human behavior in engineering management
- Data-driven and intelligent decision support systems in engineering management under Industry 4.0