PreVail remote health monitoring highlights:

  • Provides timely, efficient machine health and performance knowledge
  • Recognizes familiar patterns and deviations from normal control limits
  • Makes connections between what is happening and what has occurred before
  • Enables you to identify and carry out the right actions at the right times to increase asset utilisation, efficiency, and production


The mining industry is highly innovative in its quest for greater efficiency and safety. And your P&H equipment plays a key role in that quest. Keeping equipment up and running at high reliability and productivity levels is a key factor to sustaining good cost control and profit growth.

The PreVail remote health management (RHM) technology provides your operations and maintenance teams with timely, efficient machine health and performance knowledge. With that knowledge, your teams can focus on optimising production as well as applying strategies for reliability-centred maintenance. The result is a focused drive towards greater levels of reliability, productivity, and profitability.

Critical indicators monitoring

The PreVail RHM monitors, 24/7, key machine health factors that have the potential to cause costly interruptions or instant and delayed shutdowns, including:

  • Main power supplied via high-voltage trail cable
  • Motor bearing thermal data
  • Brakes analytics
  • Dig attachment handle crowd belt tension

Reports and dashboards

The PreVail RHM system taps into the powerful communication, command, and control capabilities of the equipment’s electrical control system, transforming the data it produces into more refined knowledge, including key performance indicator (KPI) dashboards, graphical analysis tools, predictive modelling, and reporting tools.  The productivity and reliability information includes:

  • Fleet productivity (status, utilisation): helps you identify equipment performing less than optimally for corrective action
  • Utilisation analysis: shows which units are operating, non-operating, or fault side-lined
  • Mean time between shutdown analysis: provides reliability benchmarks to identify units requiring increased availability
  • Runtime distribution analysis: reveals equipment with lower runtime hours for corrective action, leading to increased availability
  • Filtered outage / sub-system analysis: identifies faults and systems requiring corrective action, leading to increased availability
  • Filtered outage list: provides analysis of faults using parameters such as parent-child faults by severity or faults linked to an operator for faster root cause findings and more uptime
  • System warnings analysis: points to patterns, highlighting potential failure modes
  • Alert management: expedites communication of fault alerts by severity for faster response, issue resolution, and more uptime
  • Load distribution (load count, average payload, under-loaded count, and over-loaded count: identifies operators who can benefit from making adjustments to operating techniques
  • Cycle time performance (average cycle time, dig time, swing time, tuck time, and swing angle): increases productivity by identifying training needs for inexperienced operators
  • Operating practices analysis: shows instances and severity of motor stalls, boom jacks, and swing impacts
  • Fuel burn visualisation: correlates the industry’s lowest wheel loader fuel burn advantage to the tonnage moved
  • Mobility analysis: tracks tons-per-hour moved over the percentage of time in propel
  • Detailed hole summary: provides details about what occurred while drilling a hole to better plan and execute blast plans, such as final depth, drilling time, and specific energy
  • Mobile device alert notifications: contains complete fault information, sent to your mobile communication device to expedite awareness that a fault has occurred

How the system works

  1. PreVail RHM uses condition-based equipment monitoring (CBEM) modules to detect certain system data trends that deviate from normal control limits.
  2. When real-time data collection and analysis reveals a system data anomaly, the CBEM model recognizes this development and its potential impact on the machine health. It responds by issuing a first-snapshot notification (FSN) to the nearest support office.
  3. Our prognostic and health monitoring personnel act upon the FSN by checking, interpreting, and verifying the development. They then issue a work order to launch corrective action.

We support several hundred PreVail-monitored machines in service worldwide. Therefore, PreVail RHM systems analysts are able to use this substantial and growing knowledge base to detect and analyse issues with greater speed and accuracy.

In addition, we are investing in an expanded base of prognostic and health monitoring centres worldwide, enabling us to provide you with consistently better machine monitoring, reliability, and productivity.