Soft computing represents computing technologies applied in machine learning, computer science, and some engineering disciplines, studies, simulations, and analysing complex problems and phenomena. Industry 4.0 is also called Industrial Internet, Smart Factory or Smart Manufacturing. With the help of new technologies such as Internet of Things (IoT) and widespread usage of mobile technologies, organizations can generate large amounts of data in different formats faster than before.

Among them, advanced soft computing methods and decision-making technologies can be used to extract useful information (for example, the data may come from the field components, and/or Manufacturing Execution System (MES)/ Supervisory Control and Data Acquisition (SCADA)/ Enterprise Resource Planning (ERP) system) and obtain effective manufacturing intelligence. Additionally, equipment automation can be combined with decision-making technologies, and useful rules and patterns can be retrieved from the data. In some cases, potential failures, defect diagnosis, advanced equipment/ process control, cycle time reduction, cost reduction, and productivity improvement, and other issues at early stages can be foreseen.

This Special Issue aims to collect the latest research concerning the latest developments, problems, and challenges of the application of soft computing in the manufacturing process of Industry 4.0. Original research, as well as review articles, are welcomed.

Potential topics include but are not limited to the following:

• Innovative methods for soft computing analysis
• Big data machine learning
• Industry 4.0 applications
• Potential failure and defect diagnosis and analysis
• Intelligent quality tools and methods
• Production planning and control
• Performance evaluation
• Soft computing analysis applied to industry, medicine, or the environment
• Case studies of effective production and operations management