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Oil and gas

RTAMO reduces maintenance hours by 44%.

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  • Client

    Due to sensitive information, the client has requested to remain anonymous

  • Asset type


  • >40%

    reduction in annualised maintenance hours

Client background

Our client’s core business is to design, engineer, construct, install and deliver Floating Production, Storage and Offloading (FPSO) systems. Floating Storage and Offloading (FSO) systems and Single Point Mooring (SPM) Systems.

Business challenge for the customer

Our client was looking at how to optimise their maintenance schedule, reduce unnecessary maintenance, and make efficient use of available resources. This included optimising planned maintenance (PM) whilst maintaining an acceptable level of risk.

Issues to tackle included:

  • The volume of Safety and Environmentally critical equipment (SECE) and Class-related PM was too high.
  • There was too much PM generated from the Computerised Maintenance Management System (CMMS).
  • PM activities were duplicated and not value-adding
  • They wanted to improve the quality of the specific Work Instructions (WIs)

How LRQA helped

Many critical assets like oil refineries, chemical plants and offshore platforms ignore the digital intelligence of their assets - resulting in maintenance schedules that put unnecessary pressure on operations and budgets. RTAMO quickly brings an expert view on vital infrastructure - reducing workloads, cutting spending and eliminating backlogs.

Note: RTAMO™ knowledge and expertise has now been built into our new solution - AllAssets Maintenance Optimisation, offering you even more functionality.

Using sophisticated risk-based algorithms, RTAMO applies engineering knowledge in Reliability-Centred Maintenance and Failure Modes and Effects Analysis to optimise planned maintenance.

Phase one of the project for our client was to identify the distribution of maintenance hours across the FPSO equipment types and systems.

From this analysis an annualised view of maintenance hours was derived and a picture clearly evolved, highlighting candidate areas for maintenance optimisation (as a secondary benefit, several areas were noted where work attribute data was missing - hours, craft, etc).

Phase two involved the optimisation of instrument maintenance tasks. Through analysis of recorded equipment failures, a set of failure rates was derived. This was benchmarked - grouping sets of values against LRQA library data published Reliability Data.

Frequency assessment was based on a target reliability and used failure rates derived from the assets own failure history to provide a robust justification for any resulting changes to maintenance intervals to be applied through an updated Maintenance Strategy.


In applying the new recommended intervals a >40% reduction in instrument maintenance hours was realised.

This carries an associated reduction in the direct costs of delivering maintenance as well as carrying through a reduced impact on production, with comparatively less disruptive tasks being conducted within the timeframe.

Figure 1 - Overall distribution of hours.
Figure 1 - Overall distribution of hours.


  • Reduction in annualised maintenance hours
  • Reduced annual maintenance costs
  • Optimised use of available resources
  • Reduced unnecessary maintenance
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