Machine Monitoring

Avoid costly unplanned downtime and increase productivity.


One of the biggest threats to any operation is equipment not running, despite it being scheduled for production. Negative impacts include lost production, revenue, and costs associated with idle labour, work-in-progress scrap, machine repairs, and clean-up. Organisations are estimated to lose £31,000 annually, or 3% of all working days, due to faulty machinery. There is an increasing need for real-time visibility of the health and performance of equipment so that businesses can monitor, react and predict critical events.

Real-Time Machine Monitoring

Machine Monitoring Solutions can help organisations access real-time data on the condition of machinery, predict the ongoing operational efficiency, as well as identifying the next preventative maintenance window. Sensor types can include Temperature, Vibration, Current, Speed, Pressure, Flow, and Amperage. Operations Teams will be alerted if machines exceed or meet thresholds, to ensure that that remedial action is taken before any failures occur. Businesses can use this data to make more informed and proactive maintenance decisions, reduce unplanned downtime and associated costs, whilst achieving better manufacturing efficiencies.

Common Failures Detected with the System:

  • Bearing Failure Stage I, II, III, and IV
  • Imbalance
  • Shaft and Bearing Wear
  • Mechanical Looseness
  • Misalignment
  • Electrical noise
  • Resonance

Data Insights

IoT Horizon provides data visualisation, real-time alerts, and analytics to enable a predictive maintenance strategy. If any of the sensors deviate or exceed thresholds, an alert is generated to notify production teams of the change. The facility can implement remedial actions before equipment fails to reduce downtime, avoid lost capacity, and immediately respond to critical instances.

The insights generated can also be used to identify patterns in the data and predict machine failures.

Key Benefits

Continous monitoring of mission critical equipment

Detect and prevent issues faster with real-time data

Decrease maintenance costs

Predict the future status of machines

Manage energy by machine to reduce costs and the carbon footprint

Implement new profitable revenue streams

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