A framework for making maintenance decisions for oil and gas drilling and production equipment

Tang, Yula; Zou, Zhengwei; Jing, Jiajia; Zhang, Zhidong; Xie, Chao

doi:10.1016/j.jngse.2015.07.038

Cited by 24 publications

(12 citation statements)

References 18 publications

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“…Then, the MDMETs on the mechanical equipment of the petrochemical industry are established by referencing the logic decision diagram in the reliability centered maintenance (RCM) theory. The MDMETs are shown in detail as follows [18][19][20]:…”

Section: Research On Maintenance Decision-making Methods Based On Thementioning

confidence: 99%

Maintenance Decision Method Based on Risk Level

Tang¹,

Yang²,

Wang³

2021

Operations Management - Emerging Trend in the Digital Era

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Maintenance decision method of the mechanical equipment still has some deficiencies and shortcomings, including unreasonable maintenance methods, surplus or insufficient repair, and unscientific inspection and repair intervals, especially for equipment with different risks. As a consequence, more frequent failures and higher maintenance costs of the mechanical equipment occur along with some major safety accidents and economic losses in the process of production. To overcome these problems, a framework for maintenance decision method based on risk level is presented for mechanical equipment in the petrochemical industry. First, 10 evaluation indexes and a set of scoring criteria quantifying the subjective evaluation are defined to evaluate the risk level of each mechanical equipment. Based on the analytic hierarchy process (AHP), the weight of the evaluation indexes and the evaluation model of the risk levels were established. Then, the subjective effects in the scoring process were removed using the Monte Carlo simulation (MCS) approach. Next, maintenance decision-making trees of the mechanical equipment were formulated by referencing the logic decision tree of reliability-centered maintenance. Finally, the feasibility of the framework was effectively verified by testing a well-control system in the oil field, for which the risk level and maintenance methods were obtained.

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Section: Research On Maintenance Decision-making Methods Based On Thementioning

confidence: 99%

Maintenance Decision Method Based on Risk Level

Tang¹,

Yang²,

Wang³

2021

Operations Management - Emerging Trend in the Digital Era

Self Cite

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“…Moreover, their ERV calculated in the last step can be taken as the risk scores under evaluation criterion of SR, ER, and MCR. Thus, the ERV and RPN of integrated risk of ach failure mode have been calculated by using traditional Borda method and the MLBM, respectively, in Figure 6 [18].…”

Section: Case Studymentioning

confidence: 99%

Quantitative Risk Evaluation Model of the Multilevel Complex Structure Hierarchical System in the Petrochemical Industry

Tang

Shu

et al. 2019

Mathematical Problems in Engineering

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In the petrochemical production system, the high-risk items malfunction may lead to major accidents so that the risk level of the items has become the highest focus of attention for the enterprises in petrochemical industry. Based on structural composition and risk relationship, a risk evaluation framework of the petrochemical production system can generally be divided into subsystems (SS), components and parts (CP), failure modes (FM), risk types, and risk factors. So it is a characteristic of multilevel, complex structure, and lack of evaluation criteria that the evaluated object has in the process of risk evaluation. However, there are few targeted modeling and calculation methods to carry out quantitative risk evaluation in the face of the evaluated object. In order to achieve risk quantitative evaluation of the complex structure hierarchical system, a multilevel Borda model (MLBM) is presented innovatively by us based on the traditional Borda method in this study. Moreover, the MLBM are applied to realize quantitative risk evaluation of the main structure system of truss type crane on the offshore platform. In this case study, the equivalent risk value (ERV) and risk priority number (RPN) of the evaluated object with multilevel, complex structure, and inadequate evaluation criteria are calculated and the risk ties in the RPN are effectively reduced. Then, the quantitative risk results can clarify the risk level and distribution of the high-risk items throughout the production system and provide data support for the development of risk control measures to better protect the production safety. Hence, the feasibility and practicability of the method are verified with the case study. The MLBM can be used to solve other comprehensive evaluation problems with a complex hierarchical structure as well.

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“…Many studies on maintenance directs attention to technical issues such as scheduling [4,6,30]. Internal degradation and external shock damage [18], prioritisation [27], decision making (Tang et al [45]), reliability centred maintenance [38] are other areas of maintenance focus. Piasson et al [38] presented a multi-objective reliability-centred maintenance framework aimed at reducing the cost of preventive maintenance in power distribution system.…”

Section: Maintenance and Sustainability Issuesmentioning

confidence: 99%

A multi-hierarchical framework for ranking maintenance sustainability strategies using PROMETHEE and fuzzy entropy methods

Ighravwe

Oke

2017

J Build Rehabil

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Today, maintenance plays a significant responsibility in all stages of equipment life due to strong government interests in environmentally conscious manufacturing. The need of the hour is to ignore the sparse attention to sustainable maintenance research and pursue valuable links between maintenance strategy and sustainable maintenance. In maintenance strategy choice, available reports have not sufficiently addressed the imbalance caused by uncertainties in maintenance practices. In addition, current reports on maintenance strategy sustainability focus on technical and economic aspects of maintenance and scantily treat environmental, social and safety criteria. This affects the quality of decisions in maintenance systems. To remedy this situation, this study applies fuzzy entropy weight and PROMETHEE (Preference Ranking Organisation Method for Enrichment Evaluation) in ranking maintenance sustainability strategies. The proposed approach is tested in a cement plant. Based on the choice criteria, the PROMETHEE methods results identified the best maintenance strategy as maintenance optimisation strategy. Workforce training strategy was identified as the worst maintenance sustainability strategy. These obtained results were compared with fuzzy TOPSIS (Technique of Preference Order by Similarity to Ideal Solution) approach and the practical application of the approach was verified. The results serve as a basis and a platform for further application of the approach in other manufacturing companies.

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A framework for making maintenance decisions for oil and gas drilling and production equipment

Cited by 24 publications

References 18 publications

Maintenance Decision Method Based on Risk Level

Maintenance Decision Method Based on Risk Level

Quantitative Risk Evaluation Model of the Multilevel Complex Structure Hierarchical System in the Petrochemical Industry

A multi-hierarchical framework for ranking maintenance sustainability strategies using PROMETHEE and fuzzy entropy methods

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