Life extension decision making of safety critical systems: An overview

Shafiee, Mahmood; Animah, Isaac

doi:10.1016/j.jlp.2017.03.008

Cited by 40 publications

(43 citation statements)

References 89 publications

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“…The natural response would significantly cling on the effectiveness of maintenance and asset management (MAM) strategies. Maintenance can be described as the combination of technical, administrative and managerial endeavours that ensure that industrial assets cost-effectively and safely perform their designated tasks [10][11][12][13][14][15]. Maintenance philosophies can be broadly classified into breakdown maintenance (BM), planned periodic maintenance (PPM) and condition based maintenance (CBM).…”

Section: Trillion Kwh In 2012 To 223 Trillion Kwh In 2040)mentioning

confidence: 99%

A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems

Ayu¹,

Yunusa‐Kaltungo

2020

Energies

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The outburst of population as well as increasing industrialisation have triggered a very prominent imbalance between electricity demand and supply in emerging economies such as Indonesia. Based on this premise, electricity generation and distribution firms such as Perusahaan Listrik Negara (PLN) are faced with an urgent need to enhance availability and reliability through capacity expansion as well as the institutionalisation of cost-effective maintenance and asset management (MAM) principles. Some of the principles recommended here involve embedding customised overall health index (OHI) and total life cycle cost (LCC) estimation principles into engineering decisions that relate to asset renewal and/or replacement. While discussions about the fundamental theories and estimation approaches for OHI and LCC for power transformers (PTs) already exist in the current body of literature, however, they are mostly in a generic form which has somewhat limited proper implementation of these valuable principles in practice. This study is unique because it provides a very systematic framework towards achieving cost-effective MAM through a case study. Additionally, the proposed framework is all-encompassing, as it also assesses the impacts of human unreliability through the application or proven risk assessment techniques. The proposed framework commences with the evaluation of existing decision support system at PLN through a MAM audit, whereby the performance of the West Java arm of PLN with regards to critical MAM elements was examined.

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Section: Trillion Kwh In 2012 To 223 Trillion Kwh In 2040)mentioning

confidence: 99%

A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems

Ayu¹,

Yunusa‐Kaltungo

2020

Energies

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“…Also, in some countries due to highly restrictive regulations on construction of new fields, companies use life extension as means to avoid phasing out existing fields. Life extension of oil and gas facilities delivers some benefits such as increased production, reduced capital expenditures (CAPEX) associated with constructing new facility, increased job creation, reduced CO 2 emissions, and lowered financial risk compared to risk of investing in greenfield project (Shafiee and Animah, 2017).…”

Section: Distribution Of Studies Based On Oil and Gas Field's Lifecycmentioning

confidence: 99%

“…This is because significant number of facilities supporting operations in the upstream oil and gas sector are approaching or have already exceeded their original design lifetimes and asset managers have to make a decision between life extension and decommissioning. However, very few research studies have used DMS methods to address the challenges of life extension and/or decommissioning 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 20 decision-making in the oil and gas industry (Shafiee and Animah, 2017). Therefore, future work must direct efforts at applying DMS to address the challenges during life extension and decommission phase of asset life cycle in the upstream oil and gas sector.…”

Section: Concluding Remarks and Future Research Directionsmentioning

confidence: 99%

Decision support methods and applications in the upstream oil and gas sector

Shafiee

Animah

Alkali

et al. 2019

Journal of Petroleum Science and Engineering

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Decision-making support (DMS) methods are widely used for technical, economic, social and environmental assessments within different energy sectors, including upstream oil and gas, refining and distribution, petrochemical, power generation, nuclear power, solar, biofuels, and wind. The main aim of this paper is to present a comprehensive literature review and classification framework for the latest scholarly research on the application of DMS methods in the upstream oil and gas industry. To achieve this aim, a systematic review is conducted on the current state-of-the-art and future perspectives of various DMS methods applied to different upstream operations (such as exploration, development and production) which take place prior to shipping of crude oil and natural gas to the refineries for processing. Journal and conference proceeding sources that contain literature on the subject are identified, and based on a set of inclusion criteria the related papers are selected and reviewed carefully. A framework is then proposed to classify the literature according to the year and source of publications, type of fossil fuel sources, oil and gas field's lifecycle phases, data collection techniques, decision-making methods, and geographical distribution and location of case studies. The proposed literature classification and content analysis can help upstream oil and gas industry stakeholders such as field owners, asset managers, service providers, policy makers, environmentalist, financial analyst, and regulatory agencies to gain better insight about their business activities with well-informed decision-making processes. AbstractDecision-making support (DMS) methods are widely used for technical, economic, social and environmental assessments within different energy sectors, including upstream oil and gas, refining and distribution, petrochemical, power generation, nuclear power, solar, biofuels, and wind. The main aim of this paper is to present a comprehensive literature review and classification framework for the latest scholarly research on the application of DMS methods in the upstream oil and gas industry. To achieve this aim, a systematic review is conducted on the current state-of-the-art and future perspectives of various DMS methods applied to different upstream operations (such as exploration, development and production) which take place prior to shipping of crude oil and natural gas to the refineries for processing. Journal and conference proceeding sources that contain literature on the subject are identified, and based on a set of inclusion criteria the related papers are selected and reviewed carefully. A framework is then proposed to classify the literature according to the year and source of publications, type of fossil fuel sources, oil and gas field's lifecycle phases, data collection techniques, decision-making methods, and geographical distribution and location of case studies. The proposed literature classification and content analysis can help upstream oil and gas industry stakeholders such as fiel...

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“…1. These include the following: life extension, repowering and decommissioning (Shafiee and Animah 2017;Ortegon et al 2013). Life extension involves prolonging the asset lifespan, whereas the repowering involves replacement of the original wind turbines with new and improved wind turbine components.…”

Section: Introductionmentioning

confidence: 99%

“…A case study of a 500 MW baseline offshore wind farm is proposed to illustrate the models' Fig. 1 End-of-life (EOL) strategies for offshore wind farms (Shafiee and Animah 2017) applicability. The results show that the removal of wind turbines and foundation structures is the most costly and lengthy stage of the decommissioning process due to many requirements involved in carrying out the operations.…”

Section: Introductionmentioning

confidence: 99%

An economic assessment framework for decommissioning of offshore wind farms using a cost breakdown structure

Adedipe

Shafiee

2021

Int J Life Cycle Assess

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Purpose As wind power generation increases globally, there will be a substantial number of wind turbines that need to be decommissioned in the coming years. It is crucial for wind farm developers to design safe and cost-effective decommissioning plans and procedures for assets before they reach the end of their useful life. Adequate financial provisions for decommissioning operations are essential, not only for wind farm owners but also for national governments. Economic analysis approaches and cost estimation models therefore need to be accurate and computationally efficient. Thus, this paper aims to develop an economic assessment framework for decommissioning of offshore wind farms using a cost breakdown structure (CBS) approach. Methods In the development of the models, all the cost elements and their key influencing factors are identified from literature and expert interviews. Similar activities within the decommissioning process are aggregated to form four cost groups including: planning and regulatory approval, execution, logistics and waste management, and post-decommissioning. Some mathematical models are proposed to estimate the costs associated with decommissioning activities as well as to identify the most critical cost drivers in each activity group. The proposed models incorporate all cost parameters involved in each decommissioning phase for more robust cost assessment. Results and discussion A case study of a 500 MW baseline offshore wind farm is proposed to illustrate the models’ applicability. The results show that the removal of wind turbines and foundation structures is the most costly and lengthy stage of the decommissioning process due to many requirements involved in carrying out the operations. Although inherent uncertainties are taken into account, cost estimates can be easily updated when new information becomes available. Additionally, further decommissioning cost elements can be captured allowing for sensitivity analysis to be easily performed. Conclusions Using the CBS approach, cost drivers can be clearly identified, revealing critical areas that require attention for each unique offshore wind decommissioning project. The CBS approach promotes adequate management and optimisation of identified key cost drivers, which will enable all stakeholders involved in offshore wind farm decommissioning projects to achieve cost reduction and optimal schedule, especially for safety-critical tasks.

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Life extension decision making of safety critical systems: An overview

Cited by 40 publications

References 89 publications

A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems

A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems

Decision support methods and applications in the upstream oil and gas sector

An economic assessment framework for decommissioning of offshore wind farms using a cost breakdown structure

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