Innovations in Intelligent Machinery and Industry 4.0

Dear Colleagues,

Intelligent machinery and Industry 4.0 are often viewed in three levels, i.e., the device level, the connection level, and the systems management level. In the device level, intelligent machine tools need to have the ability to process and communicate information of inputs, outputs, and intermediary data for smart machining. The level of connection allows machine tools to exchange information and interrogate each other intelligently. The systems management level enables the entire factory or supply chain system to be operated and managed with full synchronization of humans, machines, and systems physically and cybernetically. This Special Issue calls for research papers which present innovative and advanced theories and practices in intelligent machinery and Industry 4.0.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

1. AI, machine learning, and deep learning approaches for complex decision making in smart machinery, such as intelligent control, intelligent diagnosis, and intelligent manufacturing planning;
2. Management and full utilization of big data collected in real-time from supply chains for intelligent decision makings;
3. Cloud and edge computing architectures, frameworks, and practical applications for smart machinery;
4. IT governance, data security, and accessibility issues for complex manufacturing systems and their stakeholders;
5. Real cases of innovative machinery design, intelligent machinery applications, implementations, and their impacts on manufacturing and services;
6. Lifecycle value chain management for smart machinery and Industry 4.0;
7. Advanced and integrated digital transformation (DT) technologies and applications for Industry 4.0;
8. Theoretical and empirical performance models for AI applications;
9. Explainable AI, responsible AI, and trustworthy AI for Industry 4.0;
10. Sustainable and smart product-service system (smart PSS) in Industry 4.0;
11. Managing risk of new technologies in Industry 4.0;
12. Green and circular economy concept-centric digital transformation (DT) and innovation ecosystems in Industry 4.0;
13. Business model-centric digital transformation (DT) and innovation ecosystems in Industry 4.0;
14. Green and circular economy concept-centric digital transformation (DT) and innovation ecosystems in Industry 4.0;
15. Forecasting and industrial competitiveness analysis for emerging digital technologies in Industry 4.0 based on bibliometrics and patent analysis;
16. Human factors and design for emerging manufacturing and servitization model in Industry 4.0;
17. Analyzing the functional dynamics and new models of supply chain and demand chain in Industry 4.0;
18. Industry 4.0-based industrial innovation model and technology policy research based on emerging digital technologies;
19. Expert systems, knowledge-based systems, and clouding manufacturing systems for Industry 4.0.

We look forward to receiving your contributions.

Prof. Dr. Amy J.C. Trappey
Prof. Dr. Ching-Hung Lee
Prof. Dr. John P.T. Mo
Guest Editors

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