Give your customers a better understanding of their machines with our Fault Diagnosis service. This service gives you actionable insights on machine faults by automatically matching labelled data patterns with your machine data.
Get real-time alerts of detected faults combined with a specific root cause, providing you with actionable insights.
Change the service to your customers from reactive to proactive and notify your customers on why maintenance is necessary.
Perform maintenance only when faults are detected and extend machine lifetime with lower maintenance costs.
Use different data sources and machine learning methods to detect patterns you didn’t know exist.
All fault diagnoses are based on the knowledge base you’ve built, which ensures you only provide accurate insights on why machine performance deteriorated.
Fault Diagnosis is used to interpret machine data, either streaming or batch. Conclusions are integrated in your CMMS system.
A valuable fault diagnosis service tells you exactly why machine performance declined. What’s the effect and which machine part caused it? The answers can be found in the knowledge base, holding your data patterns and providing you with the correct root cause analysis. With the Fault Diagnosis service, you’ll match current data with stored data in the knowledge base to identify the root cause of important, recurring faults. When a new fault occurs that isn’t recognized by the service, we will go through the proper data labelling process to properly diagnose this fault in the future. This way, you’ll continuously improve your Fault Diagnosis service and expand your understanding of your machines.
Our Fault Diagnosis is powerful alone, but it’s more valuable in combination with our Root Cause Analysis, Fault Prediction and Service Planning AI services.
Label data patterns with relevant expert knowledge and build the knowledge base that shows you why maintenance decisions are made.
Determining when a condition leads to a critical machine failure and calculate the remaining useful life of the machine.
Act on predictions and prioritise automatically generated service orders in the CMMS based on the potential impact of machine OEE.
Plan the right maintenance engineer for the right service order. Know exactly who has to be where and do what.