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The aim of predictive maintenance module is to predict when equipment failure might occur using the historical data collected through multiple sensors attached to that equipment.

Predictive Maintenance process is divided into two phases.

  • Learning phase : Predictive maintenance algorithm learns from the historical data of a failed equipment/asset. In case there are no failed equipment in the system, all equipment/assets will stay in learning mode until at least one asset fails and gets marked as "Down" in Assets.
  • Prediction phasePrediction algorithm runs every day at 12:00 AM when It collects all records from all sensors attached to the equipment during last day and makes a new prediction.Output of the prediction process are shown in Predictive Maintenance Dashboard as follows:
    • RUL : Remaining Useful Lifetime : expected remaining time before equipment next failure.
    • Status: The current status of the equipment.
    • Prediction Accuracy: a percentage of prediction accuracy. 

Rest of the document discusses how to configure Predictive Maintenance module for an equipment.

Create New Asset

Asset needs to be created in Labeeb IOT for any equipment which needs to be monitored under predictive maintenance.

Steps to add Asset:

  1. Login to Labeeb IoT Platform
  2. Open Assets under Platform Management in left menu
  3. In the Assets page click on "+" to add new Asset
  4. Specify Asset name, operation start date and other optional fields as required
  5. Set the current status for asset and corresponding time stamp for this status
  6. Add details (Device name, Data types, class, min & max range) of sensors used for monitoring the equipment. 
    Note that:
    1. All sensors/devices need to be pre-created under "Devices" section of Labeeb IOT to appear in the "Device name" drop down list.
    2. Data Types which needs to be used for these sensors should also be pre-created under "Data Types" section of Platform Management.
    3. For vibration sensor select the class of machine in order for specifying level of vibration severity to be used in calculations and for display in predictive dashboard
    4. For noise and temperature sensors specify the minimum and maximum which will be used for indicating severity for calculations as well as for display in predictive dashboard
  7. Additional sensors can be added to the asset under Devices option. The availability of these sensors/devices (based on sending data) will be used for predictive maintenance calculations and also can be viewed in the predictive dashboard under "Devices Availability".
  8. Click on Save for creating the Asset.

Once an asset is created successfully a corresponding dashboard is created in predictive maintenance.





Manage Assets

Assets created in the system can be viewed by clicking on "View Assets" option available under top right corner. Use options under Actions column for each asset to edit or delete it.


This dashboard can be accessed from the left menu. For each asset (equipment) a dashboard is created which is listed under the home menu on this page, see snapshot.

Select an asset from the drop down list, of Home menu, to view its corresponding predictive maintenance dashboard consisting of the following items:

  • Estimated Remaining Lifetime : which is the expected remaining time before next failure of equipment
  • Status : Once learning phase is completed it shows current status of the equipment
  • Prediction Accuracy percentage
  • Last value for each of the below sensors if readings available within last one hour
    • Vibration
    • Temperature
    • Noise
  • Device availability for the remaining sensors added under Devices section for the Asset. Select different time ranges on the top right corner of the dashboard to view device availability values during that period.