Optimal Service Points (OSP) for PHM enabled condition based maintenance for oil and gas applications

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Abstract

In recent years, various Original Equipment Manufacturers (OEM) have started to provide different service offerings using data driven methods to enable condition monitoring of assets used in oil and gas operations. However, a significant part of the value proposition to operators focuses on value generated at the component level, with a derived reduction in asset downtime. This limits the broad economic benefits that a condition-based maintenance approach can provide, at the enterprise level. This paper therefore provides a cost benefit analysis framework that utilizes a combined technical economic approach to determine the minimum requirements for implementing condition-based maintenance for an oil and gas asset. The framework uses prognostic algorithms for fault detection and overall system performance.
The case study tackled a set of valves in a typical Christmas tree subsystem and it showed that a prognostic enabled system provides commercial benefits at the component level and act as an enabler for CBM implementation. However, the cash flows generated at the component level becomes commercially viable when its discounted form offsets the CBM integration cost at the enterprise level. Secondly, the maintenance cost of assets, as well as the enterprise level profitability is directly influenced by the nature of failure distribution and PHM system performance, respectively.Finally, enterprise level financial viability, as well as OEM profitability in CBM implementation, requires an Optimal Service Point (OSP). This is a function of the minimum predictive requirement of the PHM system and serves as a basis for a service based business model and the identification of the technical requirements for the PHM capability.
Original languageEnglish
Title of host publicationProceedings of the 6th European Conference of the Prognostics and Health Management Society 2021
EditorsPhuc Do, Steve King, Olga Fink
Pages17-31
Number of pages15
Volume6
Edition1
ISBN (Electronic)9781936263349
DOIs
Publication statusPublished - 29 Jun 2021

Keywords

  • Optimal Service Point (OSP), condition based maintenance, annual service fee (ASF), minimum predictive requirement

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