Intelligent Manufacturing and Automation
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 5540
Special Issue Editors
Interests: composites; fatigue fracture mechanics; FEM; impact; mechanical engineering
Interests: digital transformation; materials and technologies for a circular economy; development and operation/use of sustainable products and manufacturing systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The current COVID-19 pandemic has created a significant challenge for manufacturing operations at a high production rate and automation level.
The cost of repair and operation breakdowns in manufacturing during the pandemic has set alarm bells ringing for designers, engineers, and manufacturers, who must decide whether the existing automation systems in production can be kept or whether their approach needs to change.
This Special Issue aims to cover recent advances in manufacturing and automation including the methods, and the use of Artificial Intelligence (AI), Internet of Things (IoT), cyber-physical control and own automation systems integrated with those of the suppliers’, distributors’ and customers’. Intelligent manufacturing and automation cover a range of topics, from material handling, process and production control, optimization and quality engineering to robotics, AI, IOT, just-in-time production, and all the tools used in advanced manufacturing to support highly efficient production of mechanical, civil, and electrical applications.
The aim of this issue is to share recent findings related to manufacturing and automation and how they can be applied toward fast and sustainable production in a circular economy resilient against the challenges brought on by the COVID-19 pandemic. Especially welcome are papers which are not too theoretical and which guide the reader in terms of how the research findings can be applied to their own manufacturing and automation systems.
Your contribution to this Special Issue is highly valued and appreciated.
Prof. Dr. Aidy Ali
Prof. Dr. Nader Asnafi
Guest Editors
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