MTI Wireless Case StudyTackling Oil Filter Clogs


How Wireless Monitoring Improved Operational Efficiency


Introduction:
This case study presents a wireless condition-based monitoring system to address oil filter clogging issues in a manufacturing facility. The main objective of the case study is to demonstrate the system’s effectiveness in detecting clogged filters, preventing machine shutdowns, and improving overall operational efficiency. The key findings highlight the benefits of the wireless monitoring system, including reduced machine downtime, increased productivity, and better maintenance insights.

Background and Context:
A customer faced frequent issues with clogged oil filters in their manufacturing facility. Two oil filters were installed for each line in the basement, and operators were unaware when the filters were clogged and needed to switch to the auxiliary filter. This lack of monitoring often led to machines starving for oil and shutting down until the filter switch could be made. When the filter clogs, the pipes feeding the filter would begin to vibrate, indicating a potential issue.

System Description:
The wireless monitoring system features multiple dual-axis sensors that measure velocity, acceleration, and temperature. These sensors transmit data to a controller every 10 minutes, which is then sent to a secure website for further analysis and trend monitoring. The system also incorporates a light bar with an audible alarm for real-time notifications at each predetermined operator station.

Implementation Process:
A custom implementation was designed to address the customer’s specific needs. Vibration sensors were attached to the pipes feeding the filters. These were coordinated with light towers with audible alarms installed at all operator stations. After several days of measurements, the warning and critical alarm parameters were established. The operators were now alerted when to switch to the auxiliary oil filter and clean the dirty one when an alarm was triggered.

Results and Outcomes:
The wireless monitoring system effectively eliminated machine downtime caused by clogged filters. The operators could switch filters before machines were starved for oil, preventing shutdowns. Moreover, the system provided valuable trending data, enabling maintenance teams to understand each machine’s requirements better and identify potential problem areas.

Lessons Learned and Best Practices:
The successful implementation of the wireless monitoring system underscores the importance of real-time monitoring, early detection, and proactive maintenance. Key takeaways include the value of customizing solutions to address specific problems, the need for thorough data collection and analysis, and the benefits of incorporating visual and audible alerts for operators.

Conclusion:
The wireless condition-based monitoring system significantly improved operational efficiency by addressing oil filter clogging issues in the manufacturing facility. With real-time monitoring, operators could switch filters, avoiding machine downtime and promoting productivity proactively. Additionally, the system provided valuable insights for maintenance teams, enabling them to optimize their efforts and focus on problematic machines. The case study demonstrates the potential of wireless monitoring technology to enhance operational performance and streamline maintenance processes.