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The machining processes have become a common standard in any manufacturing industry and therefore, machine-tool maintenance is vital to ensuring the sustainability of both machine tools and manufacturing processes. It is commonly known that machining operation must be maintained for a long time in every period to achieve high productivity and prevent sudden failure or breakdown (Al Naggar et al., 2021). According to a recent study, “maintenance costs represent between 15 and 60 percent of the manufacturing cost of the final product” (Romanssini et al. 2023). One of the most popular non-invasive ways to accomplish an early detection of the machine condition is through vibration analysis. The increased level of vibration in machines typically warns about the possibility of machine breakdown or failure.
Condition monitoring and predictive maintenance can be particularly challenging in specialized industries that involve hazardous areas or environments impacted by pollution, humidity, or natural gas. These types of environments require more robust, sustainable solutions. Cassia Networks X2000 Bluetooth LE Gateway with a range of up to one kilometer paired with sophisticated vibration monitoring sensors is ideal for monitoring machines in such demanding industrial environments. The total solution is simple and very effective. Wireless sensors measure vibration levels and send wireless-connected signals. Cassia Networks X2000 gateways transfer data, analyze it through the IoT Access Controller and send early alerts to plant managers.
Solution Benefits:
- Sophisticated vibration analysis
- Wireless connection
- Transmission and analysis of raw data
- App for Android and IoS devices
- Long battery life – up to three years
- Easy installation
- Reduced cost and long-term cost savings
- Reduced machine down time.
- Easy to deploy and manage.
- Secure and reliable
Contact us at sales@cassianetworks.com to discuss your projects and request a demo.
Referenced Articles
Romanssini Marcelo, Paulo César C. de Aguirre , Lucas Compassi-Severo and Alessandro G. Girardi. 2023. “A Review on Vibration Monitoring Techniques for Predictive Maintenance of Rotating Machinery.” MDPI Journal 4: 1797 – 1817. Accessed https://www.researchgate.net/publication/371890784_A_Review_on_Vibration_Monitoring_Techniques_for_Predictive_Maintenance_of_Rotating_Machinery
Yahya Mohammed Al-Naggara, Norlida Jamila, Mohd Firdaus Hassanb, and Ahmad Razlan Yusoffa. 2021. “Condition Monitoring Based on IoT for Predictive Maintenance of CNC.” Procedia CIRP 102, 2021: 314-318. Accessed https://www.sciencedirect.com/science/article/pii/S2212827121007976
