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 “Industry 4.0” or “smart 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’ demands for high-quality products/applications. In practice, smart factories lie at the core of both, Industry 4.0 and smart manufacturing.
Indicative list of anticipated themes: Computational intelligence applications on manufacturing systems; Manufacturing data analysis and diagnostics for real-time reporting using intranet capabilities and/or the cloud; Machine learning techniques to improve process control and part quality; Human-machine interaction for intelligent manufacturing; Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques; Innovative sensing strategies for process monitoring and tracking of product history; Big data analytics in data management and machine intelligence; Fog, Edge and on-demand availability of computer system resources; Use of Industrial Internet of Things (IoT) for monitoring and maintenance; Cloud-based applications for smart manufacturing; Intelligent scheduling and optimization in manufacturing; Digital twin driven intelligent manufacturing; Real-time health assessment and analysis of industrial equipment.