The aim of the special issue is to present the latest advances and developments of computational intelligence applications, new methods\/techniques, systems and tools dedicated to technological advancement applications for smart manufacturing and Industry 4.0. Defining the term \u201cIndustry 4.0\u201d or \u201csmart factory can be summarized into four major components like Cyber-physical systems, IoT, On-demand availability of computer system resources and Cognitive computing. Today, a number of trends such as the internet of things (IoT), digital manufacturing, computational methodologies and cybernetics are considered key elements of the definition and implementation of Industry 4.0. Technological advancements in the ability to collect, transfer and analyze vast amounts of data very rapidly are at the core of this trend. Closely related, smart manufacturing is a concept that aims at developing smart intelligent systems that integrate these new technologies to rapidly adapt and respond to changes in the markets\u2019 demands for high-quality products\/applications. In practice, smart factories lie at the core of both, Industry 4.0 and smart manufacturing.
\nIndicative list of anticipated themes: Computational intelligence applications on manufacturing systems;\u00a0Manufacturing data analysis and diagnostics for real-time reporting using intranet capabilities and\/or the cloud;\u00a0Machine learning techniques to improve process control and part quality;\u00a0Human-machine interaction for intelligent manufacturing;\u00a0Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques;\u00a0Innovative sensing strategies for process monitoring and tracking of product history;\u00a0Big data analytics in data management and machine intelligence;\u00a0Fog, Edge and on-demand availability of computer system resources;\u00a0Use of Industrial Internet of Things (IoT) for monitoring and maintenance;\u00a0Cloud-based applications for smart manufacturing;\u00a0Intelligent scheduling and optimization in manufacturing;\u00a0Digital twin driven intelligent manufacturing;\u00a0Real-time health assessment and analysis of industrial equipment.<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"template":"","format":"standard","topic":[192,429,430,628,577,644,576,597,573,443,446,669,635,464,528,17,559,467,615,470,545,649,634,572,637,480,481,604,681,502,674,575],"country":[331],"nsj_language":[57],"class_list":["post-1205","call_for_papers","type-call_for_papers","status-publish","format-standard","hentry","topic-artificial-intelligence","topic-augmented-reality","topic-big-data","topic-clean-technologies","topic-cybernetics","topic-data-analysis-processes","topic-data-management","topic-data-sensing-and-analysis","topic-design-computing-systems","topic-digital-fabrication","topic-digital-technologies","topic-enabling-technologies","topic-future-developments","topic-history-of-design","topic-human-computer-interface","topic-industrial-design","topic-industrial-engineering","topic-industry-4-0","topic-innovative-technologies","topic-internet-of-things","topic-machine-learning","topic-maintenance","topic-manufacturing-systems","topic-monitoring","topic-networks","topic-process-innovation","topic-process-management","topic-process-modeling-and-simulation","topic-remote-sensing","topic-smart-design","topic-smart-systems","topic-smart-tools","country-united-kingdom","nsj_language-english"],"acf":[],"yoast_head":"\n