Energy from Waste Operator Saves £122,640 Through Predictive Maintenance

Energy from Waste Operator Saves £122,640 Through Predictive Maintenance

by AVT Admin

The problem

A major energy from waste operator was struggling to unify their condition monitoring across 9 plants around the UK. Little or no condition monitoring (CM) was in place at each of the sites, which meant the maintenance teams were primarily running over 1200 separate assets until failure.

They were able to collect data from the assets but not able to provide any analysis of their condition. The company management mandated that all data collected across their sites was to be summarised and reported. In addition, realtime reporting and analysis of each machine was required.


To address these issues, Machine Sentry® was put forward and accepted by the customer as the solution. The customer’s on-site teams are responsible for collecting data using mobile and fixed vibration sensors, which is then uploaded to the Machine Sentry® Portal, secured to ISO27001. Vibration experts from AVT Reliability® provide the remote routine analysis and reporting. The reporting is built within Machine Sentry® where all actions and recommendations are raised alongside the asset. This is viewable by the maintenance teams on site, at any time. The Machine Sentry® Portal also has the added benefit of ADA™ the Automated Diagnostic Assistant. ADA™ identifies many faults including stage 2, 3 and 4 bearing failure. All faults are colour coded based on the level of criticality, this simple and quick visual check enables the maintenance team to act quickly to prevent failures. This increase in visibility and the working together of both the customer and AVT Reliability® teams is anticipated to make for a more efficient CM program longer term compared to traditional solutions.

All necessary training and additional quarterly site visits are in place to ensure the client’s program runs as intended and adds value.


Machine Sentry® is now implemented across 1200 assets at 9 different locations. Data is collected on critical assets such as fans (76), gearboxes (130) and compressors (19). This includes boiler feed pumps, condensate systems (including ACC fans and pumps) and even diesel fire pumps.

Across all sites, 64% of the actions/recommendations are now predictive or proactive, meaning the client has moved away from what were primarily reactive maintenance tasks.

Throughout a typical month, over 5000 measurements are taken including, vibration, thermal, lubrication, process and oil sampling data. The KPIs are displayed on the Machine Sentry® Portal to show asset health and schedule compliance.

Figure 1 – Typical Boiler Feed Pump monitored using Machine Sentry®


Based on data from the Machine Sentry® Portal, on average, 7% of assets are likely to have a fault identified with corrective actions needed across the energy from waste sector per annum. The below table includes savings based on 84 ‘would be’ failures throughout the year from this ‘energy from waste’ client.

Total Amount SpentResultant saved amount
Planned labour. £50,316£44,184

53% saved
Unplanned labour.£94,500
Planned materials.£131,376£78,456

62% saved
Unplanned materials.£209,832
Total amount saved.£122,640

Using the in-built cost benefit analysis tool within Machine Sentry®, it is estimated that the client has saved over £100k through predictive maintenance. It is thought that the real savings would be much higher due to ageing and developing faults over time.