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A new methodology to optimize Turnaround Maintenance (TAM) scheduling for gas plants

Elwerfalli, A.A.
; 
Khan, M. Khurshid
; 
Munive-Hernandez, J. Eduardo
Publication Date
2018-01
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Keywords
Turnaround Maintenance, TAM, Scheduling, Risk assessment, Fault Tree Analysis, FTA, Weibull distribution, Gas plants
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© 2018 World Scientific. Full-text reproduced in accordance with the publisher’s self-archiving policy.
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Yes
Open Access status
openAccess
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Engineering and Digital Technology Publications
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Abstract
Time, cost and risk are the main elements that effect the operating margin of the oil and gas companies due to Turnaround Maintenance (TAM). Turnaround Maintenance (TAM) is a methodology for the total shutdown of plant facilities during a pre-defined period to execute inspection actions, replacement and repairs according to Scope of Work (SoW). This paper presents a new methodology for improving TAM scheduling of oil and gas plants. The methodology includes four stages: removing Non-critical Equipment (NE) from reactive maintenance to proactive maintenance, risk-based inspection of Critical Static Equipment (CSE), risk-based failure of Critical Rotating Equipment (CRE), and application of failure distributions. The results from improving TAM scheduling is associated with decreasing duration and increasing interval between TAM leading to improved availability, reliability, operation and maintenance costs and safety risks. The paper presents findings from the TAM model application. The methodology is fairly generic in its approach and can also be adapted for implementation in other oil and gas industries that operate under similar harsh conditions.
URI
http://hdl.handle.net/10454/16161
Version
Accepted manuscript
Citation
Elwerfalli AA, Khan MK, Munive-Hernandez JE (2018) A new methodology to optimize Turnaround Maintenance (TAM) scheduling for gas plants. IAENG Transactions on Engineering Sciences. Vol II. Special Issue for the International Association of Engineers Conferences 2016. World Congress on Engineering (WCE 2016) & World Congress on Engineering and Computer Science (WCECS 2016). 29 Jun-1 Jul 2016, and 19-21 Oct 2016. London, UK and San Francisco, USA: 104-117.
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Link to Version of Record
https://doi.org/10.1142/9789813230774_0008
Type
Conference paper
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