Predictive model templates
Maximo® APM - Predictive Maintenance Insights SaaS comes with predictive model templates that you can use to quickly get started with the product.
The product includes the following templates:
- Failure probability prediction
- This model predicts imminent failures for assets by using IoT sensor data, meter data, and past failure history data. The goal is to build models that can characterize the probability that a particular asset will fail within a given future prediction window.
- Predicted failure dates
- This model predicts when the next failures will happen for assets by using IoT sensor data, meter data, and past failure history data. With this information reliability engineers can determine whether an asset is well-maintained. This information can be used to adjust the maintenance schedule.
- Anomaly detection
- The anomaly detection model helps identify unusual patterns in the behavior of the asset, which might indicate potential failures or pre-failure behaviors.
- Failure contribution breakdown
- In case of bad performance or equipment failure, domain experts are interested in understanding the cause of the bad outcome. This model provides the domain experts the needed visibility into the cause and factors that cause the undesirable outcome.
- Failure probability curve
- This model uses historical asset retirement data to estimate the probability of end of life failure for a given asset. Normally the failure probability goes up as the asset ages.