Next generation industrial and manufacturing technologies
摘要截稿:
全文截稿: 2019-04-30
影响因子: 4.135
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 2区
• 小类 : 计算机:跨学科应用 - 2区
• 小类 : 工程:工业 - 2区
Overview
Aims:
Industrial and manufacturing engineering has seen dramatic technology transformations during the past decades due to the development of emerging concepts and technologies such as Internet of Things (IoT), Cyber-physical System (CPS), Big Data Analytics (BDA), etc. Industry 4.0, Industrial Internet of Things, Cloud Manufacturing, and Artificial Intelligence have brought new opportunities for our next generation industrial and manufacturing technologies which are significant for the industrial revolution in the coming decades.
As the wide use of digital devices and smart sensors in industry, great myriad of data will be created. Decision-making based on the big data is attracting more and more attentions from both academic and practitioners. The next generation industrial and manufacturing technologies will the core of any business entities which are able to make full use of the cutting-edge technique for advanced decision-making. A number of recent attempts have used some advanced technologies for industrial applications such as advanced production planning and scheduling, smart manufacturing systems, data-driven business intelligence. However, there are some challenges which are required to be addressed from both theoretical and practical perspectives.
This special issueaims to disseminate recent theoretical and methodological developments, significant technical applications, case studies and survey results in areas such as Computers, Industrial Engineering, Manufacturing and Management on next generation industrial and manufacturing technologies.
All submissions will be subject to a double-blind peer-review process according to the rigorous procedure followed by Computers & Industrial Engineering.
Scope:
Topics to be covered include, but are not restricted to the following aspects of Next generation industrial and manufacturing technologies:
Applied Operations Research
Industry 4.0 implementation and case studies
Cloud manufacturing
Challenges, visions and concepts for Industry 4.0
Internet of Things and Industrial Internet
Data Mining, Knowledge Discovery and Computational Intelligence
Multi-Criteria Decision Making and Decision Analysis
System Simulation and Forecasting
Supply Chain Management & Logistics
E-Business and E-Commerce
Quality, Reliability and Maintenance
Human Factors, Industrial Ergonomics and Safety
Cyber-physical Systems
Big Data Analytics
Production/Manufacturing Systems & Processes
Agile Manufacturing; ERPI/APS
Artificial Intelligence & Expert Systems
Bio-manufacturing Systems
Healthcare Systems Applications
Design for Manufacturing, Robust Design, Reverse Engineering
Manufacturing Technologies, Group Technology & Cellular Manufacturing
Environmentally Conscious Manufacturing
Industrial Engineering Education and E-Learning
Service Systems including Energy, Transportation, Communication