Predictive Maintenance


Predictive Maintenance (PdM) provides users with a capability of monitoring equipment condition using AI and analytics including root cause analysis, anomaly detection, and remaining useful life prediction. It will help users to reduce both unnecessary and unplanned downtime and perform predictive maintenance only when it is needed.

 

Maintenance Dashboard

 
Maintenance-Dashboard

The maintenance dashboard shows an overview of shopfloor with machine position and status on a map. This information is useful for maintenance manager and operator to have a better picture of the maintenance activities.

 

Root Cause Analysis

 
Root-Cause-Analysis

PdM root cause analysis provides users the ability to easily identify the root cause of failures based on machine fault data via OPC-UA/MQTT. This page visualises the number and portion of faults in the selected machine, so that users can focus on the major fault of the machine.

 

Remaining Useful Life Prediction

 
Remaining-Useful-Life-Prediction

With the IIoT sensor data and AI model, the maintenance manager is able to estimate the remaining useful life of their critical equipment. This enables the maintenance manager to execute a cost-effective predictive maintenance program to minimize unscheduled downtime.

 

For enquiries, please contact:

Dr. Hong Jihoon
Scientist
☎ : 6590 3125 | ✉: hongjh@simtech.a-star.edu.sg