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Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study

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Title: Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study
Authors: Helge Nordal, Idriss El-Thalji
Source: Applied Sciences, Vol 11, Iss 3487, p 3487 (2021)
Publisher Information: MDPI AG
Publication Year: 2021
Collection: Directory of Open Access Journals: DOAJ Articles
Subject Terms: maintenance management, lifetime benefit, simulation modeling, multi-method simulation, industry 4.0, oil and gas, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Description: The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The ...
Document Type: article in journal/newspaper
Language: English
Relation: https://www.mdpi.com/2076-3417/11/8/3487; https://doaj.org/toc/2076-3417; https://doaj.org/article/fe5d142806474f70b6229b9be325c028
DOI: 10.3390/app11083487
Availability: https://doi.org/10.3390/app11083487
https://doaj.org/article/fe5d142806474f70b6229b9be325c028
Accession Number: edsbas.E96CF32B
Database: BASE
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  – Url: https://doi.org/10.3390/app11083487#
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  Data: Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study
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  Data: <searchLink fieldCode="AR" term="%22Helge+Nordal%22">Helge Nordal</searchLink><br /><searchLink fieldCode="AR" term="%22Idriss+El-Thalji%22">Idriss El-Thalji</searchLink>
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  Data: Applied Sciences, Vol 11, Iss 3487, p 3487 (2021)
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  Data: MDPI AG
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  Data: 2021
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  Data: Directory of Open Access Journals: DOAJ Articles
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  Data: <searchLink fieldCode="DE" term="%22maintenance+management%22">maintenance management</searchLink><br /><searchLink fieldCode="DE" term="%22lifetime+benefit%22">lifetime benefit</searchLink><br /><searchLink fieldCode="DE" term="%22simulation+modeling%22">simulation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22multi-method+simulation%22">multi-method simulation</searchLink><br /><searchLink fieldCode="DE" term="%22industry+4%2E0%22">industry 4.0</searchLink><br /><searchLink fieldCode="DE" term="%22oil+and+gas%22">oil and gas</searchLink><br /><searchLink fieldCode="DE" term="%22Technology%22">Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+%28General%29%2E+Civil+engineering+%28General%29%22">Engineering (General). Civil engineering (General)</searchLink><br /><searchLink fieldCode="DE" term="%22TA1-2040%22">TA1-2040</searchLink><br /><searchLink fieldCode="DE" term="%22Biology+%28General%29%22">Biology (General)</searchLink><br /><searchLink fieldCode="DE" term="%22QH301-705%2E5%22">QH301-705.5</searchLink><br /><searchLink fieldCode="DE" term="%22Physics%22">Physics</searchLink><br /><searchLink fieldCode="DE" term="%22QC1-999%22">QC1-999</searchLink><br /><searchLink fieldCode="DE" term="%22Chemistry%22">Chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22QD1-999%22">QD1-999</searchLink>
– Name: Abstract
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  Data: The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The ...
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  Data: https://www.mdpi.com/2076-3417/11/8/3487; https://doaj.org/toc/2076-3417; https://doaj.org/article/fe5d142806474f70b6229b9be325c028
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  Data: 10.3390/app11083487
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  Data: https://doi.org/10.3390/app11083487<br />https://doaj.org/article/fe5d142806474f70b6229b9be325c028
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  Data: edsbas.E96CF32B
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        Value: 10.3390/app11083487
    Languages:
      – Text: English
    Subjects:
      – SubjectFull: maintenance management
        Type: general
      – SubjectFull: lifetime benefit
        Type: general
      – SubjectFull: simulation modeling
        Type: general
      – SubjectFull: multi-method simulation
        Type: general
      – SubjectFull: industry 4.0
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      – SubjectFull: oil and gas
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      – SubjectFull: QH301-705.5
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      – TitleFull: Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study
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            NameFull: Helge Nordal
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            NameFull: Idriss El-Thalji
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