What is Predictive Maintenance?
Today’s maintenance teams are leveraging INDUSTRY 4.0 driven PdM to bring digital transformation to their maintenance practice.
Predictive maintenance (PdM) is maintenance that measures the performance and condition of equipment of in-service equipment during normal operation to identify any faults developing. It provides cost savings and better reliability over routine or time-based preventive maintenance.
Where Should I Use It?
Where Does It Fit in Your Maintenance Strategy?
Common PdM Tools
- Vibration analysis
- Acoustic or ultrasound analysis
- Electrical signature analysis
- Infrared thermography
- Insulation analysis
- Laser alignment
- Oil analysis
- Dissolved gas analysis
Root Cause Analysis (RCA) Makes PdM Even More Powerful
The goal of predictive maintenance is to measure equipment condition and then predict its failure, followed by a root cause analysis and then preventing the failure through corrective maintenance.
Now is the right time to change how we sense, predict and troubleshoot machine failures
IIoT sensor technology has made it possible to measure machine condition parameters like vibration, ultrasound, temperature, etc affordably and without human intervention. Machine-learning models can increase the accuracy of the predictions and make it easy for the maintenance team to run the program across a large number of equipment with minimal knowledge of condition monitoring techniques.
Benefits of IoT and ML driven digital transformation in maintenance
- Reduce unexpected failure by up to 55%
- Reduce inventory carrying costs for spares by up to 28%
- Reduced overall maintenance costs by up to 30%
- Reduce maintenance interval without compromising on equipment reliability
- The maintenance team can make data-driven decisions
- Improved HSE compliance
- Establish clear correlation between events that led to the breakdown. Data driven root cause analysis can improve plant reliability