Today’s world is highly connected.
The technology we use everyday communicates seamlessly with the outside world.
Hardware enhancements entering industrial spaces take advantage of these connections to bring more intelligent design to our machines.
Condition-based Maintenance is the practice of conducting maintenance on a machine when the asset’s condition reaches a disruptive level. The equipment has sensors that communicate if it’s OK in real-time.
As the machine communicates its condition, the data is saved within a Computerized Maintenance Management System (CMMS) in a way that is easily read by humans.
Two goals must be accomplished to conduct condition-based maintenance:
- The sensors must be purchased and installed.
- Parameters for the equipment’s normal condition must be established based on reliable standards.
The high cost of this hardware once prevented smaller facilities from using cutting edge technology. Only the largest operations with high capital equipment were able to afford the sensors for reading real-time condition, but now those prices have been reduced thanks to widespread wireless technology.
If you’re familiar with the Internet of Things, this is precisely how maintenance operations are able to benefit. Physical objects are being enhanced to collect and store data from their environment.
What kind of information does condition-based maintenance exchange?
The Internet of Things touches on a variety of markets, and the sensors embedded into these things can track a lot of different information.
For the purposes of maintenance operations, there are a number of specific readings that help facilities prevent downtime which are dependent on the type of machine.
Here are a few of the most common variables a CMMS can monitor when enhanced for condition-based maintenance:
- Equipment temperatures through infrared imaging
- Lubricant viscosity and wear metals through oil analysis
- Pressure states for fluid and airflow
- Cavitation and related wear damage
- Vibration frequencies for detecting structural looseness, misalignment, bearing issues, sheave run-out, and many electrical problems
The machine is able to take these readings in real-time and store them within a CMMS. From there, a maintenance technician can take a look at them. When the readings are abnormal, the CMMS can trigger an alert to tell the technician attention is needed.
The rise of mobility goes hand-in-hand with condition-based maintenance. Technicians are able to move throughout a facility and monitor these readings on the go from a mobile device.
As a result, technicians’ jobs are changing to better deal with data. With each new machine enhancement, technicians jobs become more automated and efficient.
What other practices are related to condition-based maintenance?
There are essentially three maintenance strategies that build off one another. Starting from the most basic maintenance practice:
- Preventive Maintenance: The facility takes a proactive approach to most maintenance practices and regularly schedules routine maintenance. CMMS is used to track spare parts, labor hours, warranties and other information used to stay a step ahead of any downtime.
- Condition-based Maintenance: The information collected isn’t just manually documented by technicians during their daily routine, but also saved by the machines themselves. This gives the department even more information to help prevent downtime and bolster the bottom line.
- Predictive Maintenance: All of the information stored within a CMMS is used to predict when downtime will occur. Algorithms take historical data and compare it to real-time data to determine what variables will cause a breakdown. This supplements the expert technician’s role of analyzing the data and making a decision on when maintenance will be required.
It’s important to note that not all CMMS solutions have predictive maintenance. Condition-based maintenance is often confused with predictive maintenance. Experts have clarified the differences.
CMMS is often limited to condition-based maintenance and leaves any predictions up to human experts. While most CMMS vendors don’t incorporate predictive technology, some are able to integrate with third parties to enable it.
Other maintenance software vendors offer packages for Enterprise Asset Management (EAM) and incorporate many CMMS features to build on the level of automation. While predictive technologies and upgrades involving machine learning are relevant to how maintenance operations are changing, CMMS is part of a software category that focuses on reliable standards.
CMMS is a traditionally practical software solution for any facility and works well with condition-based maintenance routines. By storing useful information, maintenance facilities support better decision making.