LAUSR

ABSTRACT A cloud-based manufacturing process monitoring framework for online smart diagnosis services has been developed with the aim of performing tool condition monitoring during machining of difficult-to-machine materials. The proposed architecture allows to share process monitoring tasks between different resources, which can be geographically dislocated and managed by actors with different competences and functions. Distributed resources with enhanced computation and data storage capability allow to improve the efficiency of tool condition diagnosis and enable more robust decision-making, exploiting large information and knowledge sharing. Diagnosis on tool conditions is offered as a cloud service, using an architecture where the computing resources in the cloud are connected to the physical manufacturing system realising a complex cyber-physical system using sensor and network communication. Based on sensorial data acquired at the factory level, smart online diagnosis on consumed tool life and tool breakage occurrence is carried out through knowledge-based algorithms and cognitive pattern recognition paradigms. On the basis of the cloud diagnosis, the local server activates the proper corrective action to be taken, such as tool replacement, process halting or parameters change, sending the right command to the machine tool control.