A multi-sensor based online tool condition monitoring system for milling process

Tool condition monitoring has been considered as one of the key enabling technologies for manufacturing optimization. Due to the high cost and limited system openness, the relevant developed systems have not been widely adopted by industries, especially Small and Medium-sized Enterprises. In this research, a cost-effective, wireless communication enabled, multi-sensor based tool condition monitoring system has been developed. Various sensor data, such as vibration, cutting force and power data, as well as actual machining parameters, have been collected to support efficient tool condition monitoring and life estimation. The effectiveness of the developed system has been validated via machining cases. The system can be extended to wide manufacturing applications

Lightweight Synchronization Algorithm with Self-Calibration for Industrial LORA Sensor Networks

Wireless sensor and actuator networks are gaining momentum in the era of Industrial Internet of Things IIoT. The usage of the close-loop data from sensors in the manufacturing chain is extending the common monitoring scenario of the Wireless Sensors Networks WSN where data were just logged. In this paper we present an accurate timing synchronization for TDMA implemented on the state of art IoT radio, such as LoRa, that is a good solution in industrial environments for its high robustness. Experimental results show how it is possible to modulate the drift correction and keep the synchronization error within the requirements