Remote Monitoring and Online Testing of Machine Tools for Fault Diagnosis and Maintenance Using MTComm in a Cyber-Physical Manufacturing Cloud
MTComm, Cloud based fault diagnosis, reomte online testing, cyber-physical manufacturing cloud
Existing systems allow manufacturers to acquire factory floor data and perform analysis with cloud applications for machine health monitoring, product quality prediction, fault diagnosis and prognosis etc. However, they do not provide capabilities to perform testing of machine tools and associated components remotely, which is often crucial to identify causes of failure. This paper presents a fault diagnosis system in a cyber-physical manufacturing cloud (CPMC) that allows manufacturers to perform diagnosis and maintenance of manufacturing machine tools through remote monitoring and online testing using Machine Tool Communication (MTComm). MTComm is an Internet scale communication method that enables both monitoring and operation of heterogeneous machine tools through RESTful web services over the Internet. It allows manufacturers to perform testing operations from cloud applications at both machine and component level for regular maintenance and fault diagnosis. This paper describes different components of the system and their functionalities in CPMC and techniques used for anomaly detection and remote online testing using MTComm. It also presents the development of a prototype of the proposed system in a CPMC testbed. Experiments were conducted to evaluate its performance to diagnose faults and test machine tools remotely during various manufacturing scenarios. The results demonstrated excellent feasibility to detect anomaly during manufacturing operations and perform testing operations remotely from cloud applications using MTComm.
"Remote Monitoring and Online Testing of Machine Tools for Fault Diagnosis and Maintenance Using MTComm in a Cyber-Physical Manufacturing Cloud", 3D Digital Imaging and Modeling, International Conference on, vol. , no. , pp. 532-539, Jul., 2018. doi: 10.1109/CLOUD.2018.00074