What is condition monitoring?

Condition monitoring, or condition-based monitoring, measures specific parameters for individual items of equipment to monitor their condition on a continual basis and pick up on early changes in its performance and state. 

Condition monitoring is used to predict part failure, which is a similar use case to predictive maintenance, but it operates on a different basis. Unlike predictive analytics, condition monitoring doesn’t use big data analytics or involve any AI learning systems like machine learning (ML) or deep learning (DL). Predictive analytics uses historic data to learn the norms of the entire plant, while condition monitoring uses current data only. 

With condition monitoring, plant employees set fixed values and thresholds for specific metrics. As long as the values remain stable, the equipment is considered to be in good working order. When the values exceed the preset thresholds, it triggers an alert. 

Condition monitoring typically includes:

  • Oil analysis
  • Ultrasound 
  • Vibration analysis
  • Thermography
  • Motor testing
  • Lubricant analysis
  • Acoustic emission 

Today’s condition monitoring solutions typically use IoT devices to gather the data.

Once a problem has been detected, plant engineers can monitor equipment more closely until it’s possible to repair it. Process plants can use these alerts to repair parts, before they fail entirely. 

Condition monitoring is a key element in predictive maintenance, since it generates early alerts about emerging faults in plant equipment, although the alerts are not as early as those produced by predictive analytics solutions. 

Why does condition monitoring matter to process manufacturing plants?

By noting changes in the condition and performance of equipment, conditioning monitoring gives plant engineers and maintenance teams early alerts about potential part failures. Condition monitoring alerts also provide maintenance teams with more information about the nature and scale of the problem. 

With the help of condition monitoring, process plants can:

  • Avoid unplanned downtime
  • Improve ROI on equipment
  • Carry out repairs and maintenance more efficiently and quickly
  • Increase safety by preventing employees from working on damaged equipment
  • Raise efficiency across the plant by fixing faults that impede performance
  • Reduce environmental impact by cutting the waste caused by suboptimal equipment

How can process plants implement condition monitoring effectively?

Ensure you have the necessary human resources

Before installing a condition monitoring solution, check that you have employees with the necessary analytical skills, and that they have time to take care of the solution. The best technology and the most skilled workers won’t help you if nobody has time to check alerts or adjust the parameters. 

Choose what you want to monitor 

You’ll need to decide which items of equipment to monitor, and select components within those items. Condition monitoring is typically used for: 

  • Rotating equipment
  • Items that are in continuous use
  • Equipment that handles dangerous or toxic materials
  • Parts that operate at very high speeds or pressure
  • Parts with little or no parallel or alternate capacity

It’s generally used on components where a failure is both most likely and most expensive to repair or serious for plant production or employee safety. 

Set your benchmarks

Before running condition monitoring solutions, you’ll need to establish benchmark values that represent normal conditions so that the solution can recognize variations from the norm. You might have this data already present in the plant, or you may need to gather it for this purpose. 

Establish parameters

Condition monitoring requires preset values. Choose which parameters to track for each item of equipment, and set the parameters that represent normal working order.