Increase asset lifetime and eliminate breakdowns with smart maintenance

Constantly monitor health of critical assets, calculate likelihood of failure and notify deterioration to relevant service personnel.


Predict Asset Failure

Analyse historical and real-time condition of equipment to calculate likelihood and time of failure

Eliminate Failure root cause

Identify and prevent root cause of failures faster

Plan Maintenance Better

Prioritise maintenance of equipment likely to fail, modify maintenance frequency based on deterioration rate and procure minimal spares

Compare Multiple Assets

Analyse performance of multiple assets, failure rates, energy consumption and cost of maintenance for informed investment decisions

Increase Maintenance Effectiveness

Analyse equipment condition before and after maintenance to evaluate effective maintenance execution

Improve Product Quality

With insights from asset performance, fine-tune processes and setpoints to improve product quality

Install sensors to observe Machine Health

Automatically collect data about equipment health such as vibration, acoustics, temperature, energy consumption using sensors.  These sensors push the data at fixed frequencies or on events to the central system where it is aggregated. The sensors are chosen and installed based on equipment form factor, environment constraints and operating conditions.

Model and Predict

Aggregated sensor data combined with failure events are used to model equipment behaviour and predict future failures. The prediction model is implemented on the industry leading solution from IBM. Real-time data is constantly fed into the model to improve the prediction accuracy.

Integrate with Maintenance Planning

Failure prediction results provide most likely to fail equipment, estimated time between failures and probable root cause for failure. This information is sent to maintenance planners for targeted maintenance planning. Completed maintenance actions are provided to the predictive maintenance system for understanding equipment behaviour before and after maintenance.

Guide Maintenance Teams

Data related to likely failures, root cause and service effectiveness is pushed to maintenance personnel on their mobile devices for guided maintenance actions. Maintenance teams can also query equipment datasheets, work instructions and safety procedures from the system in an integrated manner.


  • Need Analysis

  • Sensors Implementation

  • Analyse and Optimise

  • Operations & Support

Success Stories