Predictive Maintenance

Reduce unplanned downtime and optimize asset maintenance
for better efficiency

Unplanned downtime costs industrial manufacturers approximately $50 billion annually.

We have the solution to this.

A ‘crystal ball’ to predict your asset’s health

Make unplanned downtime due to equipment breakdown a thing of the past. Business owners with high-value assets can be notified about potential breakdowns to better prioritize maintenance works and allocate resources more efficiently. This translates to huge cost and time savings in the long run.

Seamless data collection
through sensors and
cameras

Automated data
analysis

Actionable
Insights

We are the ‘Machine Doctor’

Monitor asset health and detect anomalies in real-time via a user-friendly platform. Receive diagnoses of future asset fatigue, degradation or potential failure from the comfort of your seat. Achieve higher level operational excellence through better strategic planning from now on.

Potential Cost Savings

Average cost of unplanned equipment downtime is $260,000/
hour and lasts around 4 hours

$260.000

$260.000

$260.000

$260.000

$1.04 million

saved for every unplanned
downtime reduced

The Benefits

Reduce unplanned
downtime

Full clarity on machine
capabilities

Extend lifespan of
machinery

Achieve long-term cost
savings from
unnecessary maintenance works

Improve overall
productivity

Avoid operational
stress from sudden
breakdowns

Our 3 Step Solution

Stage 3 - The Forwarder
  • Leverage Machine Learning to accurately predict potential machine failures
  • Use Decision Optimization to prioritize maintenance works of machinery to reduce operational downtime and to better allocate resources
  • Get 100% clarity on machine capabilities
Stage 2 - The Tracker
  • Real-time monitoring of tracked machinery or equipment with proper indicators of actual machinery performance
  • Instant notification if machinery is underperforming
Stage 1 - The Mine
  • Efficient data collection housed in a solid data repository
Stage 1 - The Mine
  • Efficient data collection housed in a solid data repository
Stage 2 - The Tracker
  • Real-time monitoring of tracked machinery or equipment with proper indicators of actual machinery performance
  • Instant notification if machinery is underperforming
Stage 3 - The Forwarder
  • Leverage Machine Learning to accurately predict potential machine failures
  • Use Decision Optimization to prioritize maintenance works of machinery to reduce operational downtime and to better allocate resources
  • Get 100% clarity on machine capabilities

Resources

Predictive Maintenance in the Oil and Gas Industry

Predictive maintenance has been broadly used in the oil and gas industry over the past 20 years. The volatile oil market is one of the key reasons for the increased use of predictive maintenance. This is because companies are looking to reduce costs associated with unplanned downtime.  How does predictive…

Predictive Maintenance: Using Sound as the Primary Indicator

Predictive maintenance is a technique that helps monitor the equipment condition as well as to determine the appropriate maintenance activities. This is done through artificial intelligence (AI), machine learning and predictive analytics. The system will be able to predict the future trend of the equipment’s condition i.e. potential failure and…

Digital Transformation for Smart Cities

Population expansion and 5G– More than half of the world’s population live in cities and call it their home but it’s definitely increasing with the growing population. The ongoing exponential surge in population is subsequently sparking urbanisation efforts with smart city designs and solutions developed to accommodate the challenges and…

    Get in touch with our experts to find out how to optimize your high-value assets with Predictive Maintenance.


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