Cloud-Based Analytics Module for Predictive Maintenance of the Textile Manufacturing Process

Industry 4.0 has remarkably transformed many industries. Supervisory control and data acquisition (SCADA) architecture is important to enable an intelligent connected manufacturing factory. SCADA extensively used in Internet of Things (IoT) applications, including analytics visualization. Product quality management across most In this study, we develop a cloud-based module for production predictive maintenance (PdM) 4.0, thus targeting textile processes. The proposed incorporates complete knowledge discovery database process. Machine learning algorithms were employed analyze preprocessed provide suggestions management. Equipment analyzed using the system with average mean-squared error ~0.0005. trained was implemented as application programming interface use IoT applications third-party systems. This study provides basis improving by predicting optimized equipment settings processes industry.