Technical Deepdive: Fault Classification

In this second technical deep dive we cover Fault Classification, which is an extension of Anomaly Detection. Anomaly Detection finds abnormalities within your data and separates them. As explained in the previous post, the separation is based on how many samples have...

Technical Deepdive: Anomaly Detection

In the first series of posts, we presented you old and established maintenance models. Before diving into predictive maintenance, we want to show you methods to manipulate data which can be used for predictive maintenance. Therefore, the next four posts will explain...

Industry Insights: Interval Servicing

In this last post we take a closer look at the Interval Servicing maintenance model. Interval Servicing has a lot of similarities with Preventive Maintenance. The philosophy is to identify and solve small problems before they become big ones. Only with Interval...

Industry Insights: Preventive Maintenance

Last week, we presented the “bathtub” function which shows the failure rate of assets over their lifetime. When this function is approximately known for an asset, a new service model can be introduced to avoid long downtime, dangerous operation modes and untimeliness...

Industry Insights: Reliability Engineering

In our last post, we presented the service model run-to-failure. Before diving into the next models, it is important to understand their origin. The run-to-failure service model is most probably the oldest and simplest model. It does not require planning and...

Industry Insights: Run to Failure Service Model

This post is part of a series in which we will explain different service/employment models. In this particular post, we will take a closer look at the run-to-failure model. As the name already describes, this model is used with the intention that the product is...