Complex System Modelling in Engineering Under Industry 4.0
1Louisiana College, Pineville, USA
2Central South University, Changsha, China
3University of Management and Technology, Lahore, Pakistan
Complex System Modelling in Engineering Under Industry 4.0
Description
The time for Industry 4.0 is coming. Smart manufacturing has become one of the most funded and advanced technological research areas in developing and developed countries. It encompasses all engineering fields such as civil and environmental engineering, mechanical engineering, electronic engineering, medical engineering, etc. Progressively, we are experiencing exciting and rapidly evolving engineering systems leaning towards automation, intelligence, and sustainability.
In-depth understanding of complex engineering systems plays an important role in the future development of various engineering fields under Industry 4.0. Modelling complex engineering systems to further promote smart manufacturing has become interesting for scholars and engineers from both academia and industry backgrounds. Emerging complex system modelling techniques, such as big data, fast computing, machine learning, and deep learning address practical engineering problems and provide solutions for specific engineering problems with universal methodologies. It is therefore of great significance to develop and innovate efficient modelling techniques of complex engineering systems under Industry 4.0.
The aim of this Special Issue is to solicit original research articles offering a timely opportunity to scholars and engineers to discuss, share, and summarize current innovations in modelling techniques of complex engineering systems under Industry 4.0. This Special Issue particularly focusses on trends in modelling techniques for smart manufacturing within various engineering fields. Review articles summarising advances in complex engineering system models under Industry 4.0 are also welcome. We hope that this Special Issue helps solve some practical engineering problems.
Potential topics include but are not limited to the following:
- Complex systems and dynamics analysis in engineering
- Complex engineering system analysis and control
- Automation, intelligence, and sustainability in complex engineering systems
- Modelling complex engineering systems and smart manufacturing
- Machine learning for complex engineering system modelling
- Deep learning for complex engineering system modelling and control
- Artificial intelligence for complex engineering system modelling
- Fast computing for complex engineering system modelling
- Big data technologies for complex engineering system modelling and control