Three Levels of Condition-Based Maintenance to Maximize Uptime
Date: May 17, 2018
by Tianshu Zhang, Services Product Manager, Ingersoll Rand® Compression Technologies and Services
Even in today’s high-tech world, many companies still have a limited view of their compressed air system health, and often take a “better safe than sorry” approach, and prematurely replace components. This focus on routine or recommended compressor maintenance often needlessly costs compressed air users thousands in added maintenance expense.
A shift is occurring in maintenance of equipment and systems called prognostics and health management (PHM), and differs from PdM or Predictive Maintenance. PdM utilizes similar diagnostic tools such as infrared, vibration monitoring and oil analysis to deliver the current condition of components but does not correlate and trend the measured parameters. Prognostics is a scientific discipline which delivers “remaining useful life” (RUL) through modeling of a statistically significant sample of systems. The algorithms utilized in prognostics focus on assessing how far the component has degraded beyond “day one” health, and at what point the component will no longer perform its intended function.
When it comes to prognostics in compressed air systems, knowing what parameters should be measured and how they should be analyzed help to form good practices in condition based maintenance (CBM).
Comprehensive system insights for effective maintenance strategies and uptime
Fluid and vibration levels, noise, and air temperature are good parameters to assess the health of a compressed air system. While compressor controllers and performance indicators can provide certain readings, facilities often lack comprehensive knowledge and insight about their equipment, and the knowledge about how the different parts of a compressed air system relate to one another. A real-time snapshot of equipment isn’t enough – plants need a way to predict the future of their equipment.
A condition-based maintenance system ensures that all components of a system are running efficiently and helps operators predict issues that may occur down the road. This type of monitoring utilizes unique algorithms that calculate and predict service intervals based on the actual maintenance needs of equipment, not just an industry average.
There are three main tiers of condition-based maintenance to pay attention to. Each of the three have interdependencies and provide facility managers with insight so they can make informed, educated decisions based on facts about their equipment.
1. Lubricant condition-based maintenance: Monitoring the lubricant through sampling and lab testing determines contaminant and fluid integrity levels as well as metal content in the fluid. Determining the health of the oil allows for change-out at the right time. Changing too early creates needless expense and changing too late shortens the life of the compression element, called the airend. The health of the oil is an indicator of the health of the compressor, much like a blood test for a person. Additionally, signs of wear and aging of the airend can be determined through the metal content in the oil. For example, high levels of metal in the lubricant may indicate that the rotors or bearings are wearing down depending on the type of metal circulating in the lubricant. Another source of metal could be heat exchangers or other passages with which the oil contacts. The metal content in the lubricant, therefore, also informs the mechanical condition-based maintenance tier.
2. Mechanical condition-based maintenance: In addition to lubricant CBM, shock pulse monitoring examines the vibration and noise levels to provide a comprehensive view of the airend health. This typically involves special instruments and sensors to detect accurate vibration and noise levels. High noise or vibration levels can indicate an issue such as bearing wear or rotor degradation. Trending of the wear through vibration monitoring with detection of metals in the oil allow for correlations and predictive models to be built for remaining useful life.
3. Pneumatic condition-based maintenance: This type of monitoring takes a deep look into the air quality to make sure that the entire system is working efficiently. With condition-based monitoring, plants can make better decisions based on facts about their unique systems. Ingersoll Rand offers this type of service. Certified service technicians go to a facility and perform what’s called Air System Modeling and Simulation (ASMS). ASMS consists of creating an electronic model of an entire compressed air system, from compressors and accessories on the supply side, through to the piping distribution network and down to point-of-use devices. Compressed air systems are dynamic - ever changing with time - and through the advancements of ASMS, plants can better understand their specific compressed air systems. This level of monitoring tests the compressed air within the system, air pressure in the piping, air flow levels, humidity and more. ASMS can also indicate where the system needs another piece of equipment. For example, if a test shows that there is high humidity in the air, it indicates that the system may need dryer technology to dry the air before it exits the system.
Redefine reliability with IIoT and condition-based maintenance
The Industrial Internet of Things (IIoT) is at the forefront of the manufacturing industry, and connected data and monitoring can help facilities find potential issues sooner than basic methods, saving time and resources. Connected compressed air systems can help manufacturing facilities improve overall efficiency by allowing them to virtually monitor their systems and predict maintenance needs down the road. Additionally, some compressor controllers and maintenance cloud systems utilize advanced algorithms and parallel processors to enable operators to get the lowest energy consumption and best performance out of their compressed air systems.
With a total system approach to condition-based maintenance, facilities can improve efficiency by monitoring and storing data in the cloud to see how all of the air system components work together. Visibility into the interaction between the system components helps to predict exact maintenance intervals – there’s no guessing involved. From consumables to key parts like rotors, all the way to the end at the point-of-use, digital connectivity provides operators insight into every step of the process. This level of monitoring, through system design and diagnostics, enables plants to maintain higher levels of reliability, often called “reliability centered maintenance” (RCM).