Maintenance strategy selection problem: an MCDM overview

Shafiee, Mahmood

doi:10.1108/jqme-09-2013-0063

Cited by 126 publications

(102 citation statements)

References 64 publications

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“…These three methodologies gave as the optimum solution scheduled on-condition work, based on the judgements of a single expert and of a group. Finally, Shafiee (2015) includes a literature review on the use and application of MCDM techniques in maintenance strategy selection classifying contributions into those produced by researchers and by practitioners. It also sets out the MCDM techniques best suited to the specific needs of each organization.…”

Section: Literature Reviewmentioning

confidence: 99%

Maintenance strategy selection in electric power distribution systems

Carnero

Gómez

2017

Energy

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Section: Literature Reviewmentioning

confidence: 99%

Maintenance strategy selection in electric power distribution systems

Carnero

Gómez

2017

Energy

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“…This is the best known and simplest MCDA method (Shafiee, 2015a). WSM is also referred to as the simple addictive weighting (SAW) in the literature as it is suitable for handling single dimensional problems.…”

Section: Weighted Sum Model (Wsm)mentioning

confidence: 99%

“…MCDA methods can be categorized into two types of crisp and fuzzy models (Shafiee, 2015a). The crisp MCDA models express the importance weights of criteria using crisp numbers.…”

mentioning

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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“…Absolute importance Element i is absolutely more important than element j 2, 4,6,8 Intermediate values Represents compromise between the priorities…”

Section: Weightmentioning

confidence: 99%

Determination of the Most Suitable Technology Transfer Strategy for Wind Turbines Using an Integrated AHP-TOPSIS Decision Model

Dinmohammadi

Shafiee

2017

Energies

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Abstract:The high-speed development of industrial products and goods in the world has caused "technology" to be considered as a crucial competitive advantage for most large organizations. In recent years, developing countries have considerably tended to promote their technological and innovative capabilities through importing high-tech equipment owned and operated by developed countries. There are currently a variety of solutions to transfer a particular technology from a developed country. The selection of the most profitable technology transfer strategy is a very complex decision-making problem for technology importers as it involves different technical, environmental, social, and economic aspects. In this study, a hybrid multiple-criteria decision making (MCDM) model based on the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to evaluate and prioritise various technology transfer strategies for wind turbine systems. For this purpose, a number of criteria and sub-criteria are defined from the viewpoint of wind energy investors, wind turbine manufacturers, and wind farm operators. The relative importance of criteria and sub-criteria with respect to the ultimate goal are computed using the eigenvalue method and then, the technology transfer alternatives are ranked based on their relative closeness to the ideal solution. The model is finally applied to determine the most suitable wind turbine technology transfer strategy among four options of reverse engineering, technology skills training, turn-key contracts, and technology licensing for the renewable energy sector of Iran, and the results are compared with those obtained by classical decision-making models.Keywords: technology transfer; wind turbine; design and manufacture; multiple-criteria decision making (MCDM); analytic hierarchy process (AHP); technique for order of preference by similarity to ideal solution (TOPSIS)

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Maintenance strategy selection problem: an MCDM overview

Cited by 126 publications

References 64 publications

Maintenance strategy selection in electric power distribution systems

Maintenance strategy selection in electric power distribution systems

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

Determination of the Most Suitable Technology Transfer Strategy for Wind Turbines Using an Integrated AHP-TOPSIS Decision Model

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