Wireless Predictive Maintenance to Fix a Dated Walk-Around Program
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Enterprise Asset Management Systems (EAM)
- Networks & Connectivity - WiFi
- Sensors - Pressure Sensors
- Sensors - Temperature Sensors
- Sensors - Vibration Sensors
- Life Sciences
- Maintenance
- Predictive Maintenance
C&W Services was using a manual condition monitoring program at one of its leading life sciences’ client up until last year. At best, data was collected manually every 30 days, even on the most critical machines, using a handheld data logger. After the data collection, all of the data analysis had to be outsourced to a third party for analysis. This approach has several limitations:
1. Unplanned Downtime
2. Shortage of Manpower
3. Safety and Access to Machines
4. Inconsistent Readings Collected by Manual Processes
After evaluating several options, C&W Services deployed Petasense’s IIoT-based PdM technology to monitor, analyze and predict the health of important industrial equipment such as AHUs, pumps, compressors, exhaust fans and chillers. C&W Services installed tri-axial vibration sensors called Motes, connected them to the facility’s Wi-Fi network and began receiving data and actionable intelligence instantly.
“The tri-axial data from the Motes improves the diagnostic capabilities by increasing the volume and variety of data available at your fingertips,” said Auton. “Also, when you take readings at the exact same time across multiple dimensions and machines, they become much more valuable.” “Further, it was very easy to install.” Auton was impressed by the intuitiveness, simplicity and elegance of the Petasense technology. The ease of implementation and its ability to run on LAN (IP 802.3 protocol) accessible everywhere was a huge value driver for the C&W Services team.