Combining periodic, in-service fluid analysis testing with continuous, in-line sensor data for industrial applications brings asset reliability management to the next level.
In the past sensor technologies had limitations and did not perform well in harsh environments. In recent years this technology has become more cost effective, reliable, and scalable using wireless technology. Options available for process/analyzing the data and integrating the data with other platforms have also improved in recent years. The improvement in in-line sensors for monitoring equipment condition has evolved complimenting in-service lubricant analysis in industrial applications.
Though testing of in-service lubricants and sensor technology have been around for a long time, both technologies have evolved in scope and reporting capabilities that allows these two disciplines to work more closely together and complement each other. Both are effective tools used within predictive maintenance programs that can detect faults or performance reliability issues that are not readily evident until noticeable damage has occurred.
- In-line or remote sensors monitor assets 24/7 and provide continuous real-time monitoring of parameters that the sensor is designed for. The sensors can provide an ‘early warning system’ to alert the need for more in depth diagnostics. In the case of in-line oil debris sensors, the likelihood of detecting small concentrations of debris is improved due to continuous flow of sample volume.
- Sampling in-service lubricants provides detailed information, a broad range of test parameters and levels of detection, that only a laboratory can provide and allows trending of data that highlights abnormalities to the trend.
Cloud or networked systems mean better data accessibility & reporting. Data can be combined into consolidated reporting for more powerful condition base monitoring to establish trends, predict failure, and predict the remaining life of an asset and fluid. In-Line sensors provide more frequent data, establishing trends in real-time, and are supplemented by more precise laboratory analysis, together these provide an accurate assessment of the equipment’s condition. Asset managers can utilize API applications (Application Programming Interface) to transfer and feed data to CMMS applications (Computerized Maintenance Management System) that incorporate both oil analysis data and data from in-line sensor technology. This use of combined predictive maintenance tools and integrating into CMMS applications is gaining popularity as the Industrial Internet of Things (IIoT) technology. In today’s world the way data is reported is as important, or more important, as the data itself.
In-line Sensor Technology:
- Vibration, Temperature & Noise Monitoring
- Oil condition (typically by electrical impedance sensor) and viscosity
- Ferrous & Non-Ferrous debris monitoring in industrial oils
- Creates rules using patterns for ‘machine learning’
- Remote hands-free monitoring
In-Service Oil Analysis:
- Fluid service life
- Excessive wear
- Asses fluid integrity
- Key warranty support
- Management reporting for overall asset inventory health
When it comes to testing in-service lubricants for monitoring asset reliability and scheduling proactive or predictive maintenance the key is follow-up by asset maintenance staff and managers, as well as assigned ownership of the data. The is also true for combining data generated from in-line sensors using CMMS tools for more powerful decision making strategies and planning.
ALS Tribology offers all of the above in-line sensor technologies and in service oil analysis and has robust API capabilities that are easy to integrate with client’s CMMS tools. ALS can team with your maintenance management systems to integrate in-line sensor data with in-service lubricant testing and trending analysis for consolidated reporting. For further information to integrate data into a more powerful reporting tool contact ALS Tribology at firstname.lastname@example.org.