Industrial cyber-physical system for condition-based monitoring in manufacturing processes

Nowadays, manufacturing processes is adopting solutions with more sensoring systems on the basis of Industrial Cyber-Physical System (ICPS) approaches in order to carry out real-time process monitoring, optimal parametrization and self-reconfiguration of machine tools, robots and industrial processes from individual equipment's to global production environments. The present article introduces an ICPS architecture for condition-based monitoring to manage alarm and events combining local information extracted by multiple sensors integrated a family of CNC machine tools with a cloud information as a service to manage and update the local parametrization in order to predict failure pattern in CNC machine tools. The architecture is divided in two modes: a local mode embedded in each CNC machine tool and a global mode able to connect and reconfigure the local monitoring system based on global information knowledge. Finally, a case study based on a bearing benchmark is selected to evaluate the behavior and accuracy of the proposed architecture and the implemented condition-based monitoring system in multiple local CNC Machines tool (local modes) with self-learning and optimal parametrization provided by the cloud service (global mode).