Case Study Details

Power Generation Maintenance Review Project

Client: Confidential
Industry: Oil & Gas
Location: United Kingdom
Year Completed: 2020-2021

Project Summary

Optimal undertook a Failure Mode driven maintenance and spares strategy review for the main power generation gas turbines on two offshore platforms with the aim to increase availability of the turbines from 92% to 98%. Although there was redundant generative capacity there was still a high potential for power interruption during load shedding and run ups on switch over which caused production problems.

In total, there were 5 turbines (3 x PGT25 and 2 x LM2500 Dual Fuel Aeroderivative turbines) with differing age and manufacturing origins, and as a result maintenance and spares had to be developed for each turbine system. For this scope, Optimal carried out a holistic Reliability Centred Maintenance (RCM) derivation study (including vendor support tasks) for the whole of the power generation systems including:

  • A spare parts review
  • A spare parts preservation assessment
  • Vulnerability Analysis.

Key Benefits | Outcomes

The project delivered the following:

  • A completely new suite of bespoke systematic maintenance tasks (in a SAP compliant format) that could be proactively performed to prevent, or to diminish to a satisfactory degree, the consequences of failure
  • Visibility of vendor tasks created and aligned with the overall maintenance planning regime
  • Identified a total of 40 new vulnerabilities that could hinder the safe working of the turbine packages. Recommended mitigation activities were defined within the Vulnerability Report
  • Updated spare parts lists with preservation recommendations to meet availability targets and ensure rapid reinstatement after any down time
  • Demonstrated the capability to conduct a complex RCM project, which required collaboration with client’s personnel and external stakeholders through remote workshops/meetings.

Overall, Optimal were able to help the client reduce their risk, improve availability and optimise productivity.

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