Well-intentioned maintenance budget cuts often lead to reliability problems and production deferments, because it is hard to predict how maintenance changes affect future output.
MACH10 has an innovative approach to cost optimization: it uses an advanced Reliability, Availability, and Maintainability (RAM) model of the plant to test operating cost reduction options, ensuring that both cost and production targets are met.
Our method uses a probabilistic approach based on consolidated historical databases and innovative analytics to predict the future performance of a production asset. Our method uses the results of best-in-class RAM analysis software to assess maintenance plans, spare parts stock composition, logistics, and maintenance staff to determine how operating costs savings can be achieved with no- or acceptable impact on production efficiency.
Furthermore, this method allows simulating any cost saving initiative over a 20-year time-frame to determine its impact on future revenues.
We have carried out a pilot-study for an offshore operator in the Middle East, where our method has been applied to identify possible operating cost savings on a gas injection platform composed of three centrifugal compressors driven by gas turbines.
Before our study was carried out, a traditional cost-saving initiative had been applied to this asset to optimize spare parts stocking and maintenance intervals.
Our study identified further potential savings on spare parts inventory equivalent to 13% of the stored spare parts value, while it highlighted that a further 0.3% production efficiency improvement was possible through a further optimization of the maintenance regime. Furthermore, it was possible to demonstrate that a proposed spare parts inventory reduction aimed at saving costs would have actually caused a net loss to the asset.
Our method provides a tool for assets operating under high cost pressure to make conscious choices when implementing cost cuts or budget optimizations.
Traditionally this is done by looking mainly at the cost side; our method allows taking into account the effect of such initiatives also on future revenues, to avoid the well-known scenario of cost cuts generating higher operating costs shortly after they are implemented.
Our method is based on consolidated RAM analysis tools, however the innovative analytics we developed make affordable their use in the field of operating costs optimization.Download PDF