Data Stream Evaluation for Decision Enhancement to Prescribe Maintenance
Master thesis
Permanent lenke
https://hdl.handle.net/11250/2678616Utgivelsesdato
2020-06-18Metadata
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Sammendrag
Nowadays, global competition and rapid technological advancement in the oil and gas industry induce organizations to enhance their maintenance strategies. Oceaneering, as a company within the energy industry, employs applicable standards and utilizes data streams to conduct maintenance instead of applying common maintenance strategies. Data stream is an alternative for determining preservation programs such as prescriptive, selective, Original Equipment Manufacturer (OEM), and Offshore and Onshore Reliability Data (OREDA). Each data stream has different objectives and techniques to resolve the problem in each component. Selecting the most appropriate data stream to prescribe maintenance becomes a complex issue among decision-makers in Oceaneering Asset Integrity (OAI). Furthermore, the perplexing inquiry emerges when feasible data streams present different recommendations to conduct maintenance. Additionally, decision-makers face multiple contradictory criteria for consideration when selecting the most trustworthy data stream.
Selecting a data stream to conduct maintenance can be categorized as a multi-criteria decisionmaking (MCDM) method since it requires a complex examination. This method is applied in this thesis to select the most appropriate data stream for conducting maintenance of a bearing in a centrifugal pump system. This approach presents weight criteria and ranking evaluation for the alternatives of data streams, which eventually helps decision-makers in making better decisions. The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are part of the MCDM method. The AHP method is used for assessing the weight criteria in this thesis, while the fuzzy TOPSIS is utilized for evaluating the ranking of the alternative data streams. After applying the selection model in this thesis, selective data stream is chosen to prescribe maintenance of the bearing in the centrifugal pump system with misalignment failure mode. The purpose of choosing the most appropriate data stream is to streamline maintenance activities, reduce operational costs, mitigate unplanned stops, and increase production. Furthermore, this enhancement model affects the longevity of machinery, the reliability, and the availability of the system.
Beskrivelse
Master's thesis in Industrial asset management
Utgiver
University of Stavanger, NorwaySerie
Masteroppgave/UIS-TN-IMBM/2020;Beslektede innførsler
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