Smart Design, Smart Manufacturing and Industry 4.0
A special issue of Energies (ISSN 1996-1073).
Deadline for manuscript submissions: closed (31 December 2016) | Viewed by 39210
Special Issue Editors
Interests: Industry 4.0, smart design for manufacture, energy efficient engines, parallel computing and control, machine learning and optimisation, computational intelligence
Interests: cyber-physical systems, dynamics and control, robotics, multidisciplinary design and optimisation, reliability and risk analysis, computational intelligence
Interests: robotics and autonomous systems; mechatronics and automation; data analytics; intelligent control; computational intelligence; digital manufacturing
Special Issues, Collections and Topics in MDPI journals
Interests: computer science, informatics, energy-efficient computing, robotics
Interests: evolutionary computation, machine learning, computer applications, power electronics
Interests: computer science and technology, network and communication technology, cyber security
Special Issue Information
Dear Colleagues,
Smart manufacturing lies in the centre of “Industrie 4.0” or “Industry 4.0”, the first a-priori engineered and the fourth “industrial (r)evolution”, referring to “the industrial value chain and technological evolution upgrading the factory floor to a mass be-spoke innovation centre” (Siemens 2015). Its revolutionary value lies in the mass customisation made available at mass production through cyber-physical integration, information and communication technology, and computer-automated design, in which computer science and technology play a key role.
Energy-efficient design for smart manufacturing and Industry 4.0 is applicable to smart designs for customised production, networked embedded systems, “smart factories”, “industrial internet”, “Internet of Things”, “Internet of Everything”, and “Internet+”. This Special Issue welcomes original, high-quality research papers or reviews on these topics, including developments of energy-efficient methodologies and business environments for Industry 4.0. It also welcomes related topics on energy-efficient autonomous manufacturing, computer technology for manufacturing automation, autonomous systems, smart robotic systems, computational intelligence aided engineering, machine learning, system monitoring, and advanced control.
Prof. Dr. Yun Li
Dr. Yi (Leo) Chen
Dr. Erfu Yang
Prof. Dr. Hongnian Yu
Prof. Dr. Jun Zhang
Prof. Dr. Huaqiang Yuan
Guest Editors
Manuscript Submission Information
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Keywords
- energy efficiency
- energy efficient design
- energy efficient systems
- smart manufacturing
- autonomous manufacturing
- smart factories
- customised production
- industrial automation
- industry 4.0
- industrial internet
- cyber-physical systems
- internet of everything
- smart design
- autonomous design
- computer-automated design
- machine learning
- evolutionary computation
- computational intelligence
- business informatics
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Submitted Papers
Dear Colleagues,
Smart manufacturing lies in the centre of “Industrie 4.0” or “Industry 4.0”, the first a-priori engineered and the fourth “industrial (r)evolution”, referring to “the industrial value chain and technological evolution upgrading the factory floor to a mass be-spoke innovation centre” (Siemens 2015). Its revolutionary value lies in the mass customisation made available at mass production through cyber-physical integration, information and communication technology, and compute-automated design, in which computer science and technology play a key role.
Energy-efficient design for smart manufacturing and Industry 4.0 is applicable to smart designs for customised production, networked embedded systems, “smart factories”, “industrial internet”, “Internet of Things”, “Internet of Everything”, and “Internet+”. This Special Issue welcomes original, high-quality research papers or reviews on these topics, including developments of energy-efficient methodologies and business environments for Industry 4.0. It also welcomes related topics on energy-efficient autonomous manufacturing, computer technology for manufacturing automation, autonomous systems, smart robotic systems, computational intelligence aided engineering, machine learning, system monitoring, and advanced control.
Prof. Dr. Yun Li
Dr. Yi (Leo) Chen
Dr. Erfu Yang
Prof. Dr. Hongnian Yu
Prof. Jun Zhang
Prof. Huaqiang Yuan
Guest Editors