Maintenance and decommissioning real options models for life-cycle cost-benefit analysis of offshore platforms

Santa-Cruz, Sandra; Heredia‐Zavoni, Ernesto

doi:10.1080/15732470902842903

Cited by 20 publications

(8 citation statements)

References 12 publications

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“…ROA has been previously applied to the maintenance modeling problems. An ROA model for offshore platform life-cycle cost-benefit (LCCB) analysis is developed by treating maintenance and decommissioning as real options (Heredia-Zavoni & Santa-Cruz, 2004;Santa-Cruz & Heredia-Zavoni, 2011). Jin, Li, and Ni (2009) present an analytical ROA cost model to schedule joint production and preventive maintenance under uncertain demands.…”

Section: Review Of the Maintenance Modeling Literaturementioning

confidence: 99%

“…ROA-based models have been developed for the maintenance modeling problem (Heredia-Zavoni et al, 2004;Santa-Cruz & Heredia-Zavoni, 2011;Jin et al, 2009;Koide et al, 2001;Goossens et al, 2011). However none of these works consider PHM technologies and the predictive maintenance, rather they model preventive maintenance as real options.…”

Section: Shortcomings Of the State-of-the-art Modelsmentioning

confidence: 99%

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International Journal of Prognostics and Health Management, ISSN 2153-2648, 2016 008 PHM-Based Wind Turbine Maintenance Optimization Using Real Options

Lei

Sandborn

2020

IJPHM

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A simulation-based real options analysis (ROA) approach is used to determine the optimum predictive maintenance opportunity for a wind turbine with a remaining useful life (RUL) prediction. When an RUL is predicted for a subsystem in a single turbine using PHM, a predictive maintenance option is triggered that the decision-maker has the flexibility to decide if and when to exercise before the subsystem or turbine fails. The predictive maintenance value paths are simulated by considering the uncertainties in the RUL prediction and wind speed (that govern the turbine’s revenue earning potential). By valuating a series of European options expiring on all possible predictive maintenance opportunities, a series of option values can be obtained, and the optimum predictive maintenance opportunity can be determined. A case study is presented in which the ROA approach is applied to a single turbine.

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Section: Review Of the Maintenance Modeling Literaturementioning

confidence: 99%

Section: Shortcomings Of the State-of-the-art Modelsmentioning

confidence: 99%

International Journal of Prognostics and Health Management, ISSN 2153-2648, 2016 008 PHM-Based Wind Turbine Maintenance Optimization Using Real Options

Lei

Sandborn

2020

IJPHM

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“…This decision will only be made as the time of intervention draws close and more condition information is known. Previous work has indicated that this is possible using a real options approach, such as proposed by Zhao and Tseng (2003) and Santa-Cruz and Heredia-Zavoni (2011) in other civil engineering applications.…”

Section: Introductionmentioning

confidence: 99%

A Real Option Approach to Determine Optimal Intervention Windows for Multi-National Rail Corridors

Lethanh

Adey

2015

Journal of Civil Engineering and Management

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In this paper, a real option approach to determine the optimal time to execute interventions on rail infrastructure, when it is not known for certain which intervention is to be executed, is presented (i.e. the optimal intervention window). Such an approach is useful in the management of rail infrastructure that belongs to a multi-national rail corridor where multiple railway organizations, ideally, should coordinate their maintenance interventions, years in advance, to minimize service disruptions. The approach is based on an adaptation of the Black and Scholes differential equation model used to value European call options in financial engineering. It is demonstrated by determining the optimal intervention window for infrastructure in a fictive rail corridor.

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“…Recent work has indicated that this is possible using a methodology built on real options (RO), such as proposed by [2] in other civil engineering applications. A methodology built on RO makes it possible to directly take into consideration the probability of obtaining new information in the future and the fact that interventions will only be executed if certain conditions are met.…”

Section: Introductionmentioning

confidence: 99%

“…Almost no work has been focused on decision making related to the maintenance of existing infrastructure, and none on decision making related to the maintenance of railway infrastructure. The former includes the example given by [2] of how a RO methodology can be used in decision making related to the maintenance of offshore structures. Although no work has been done on the latter, however, many researchers are investigating the determination of optimal intervention strategies for rail infrastructure.…”

Section: Introductionmentioning

confidence: 99%

A real option methodology to determine the optimal intervention windows for railway infrastructure

Lethanh¹,

Adey²

2014

WIT Transactions on the Built Environment

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In this paper, a real option methodology is presented for the determination of the optimal expected time in the future for a railway infrastructure manager to decide what types of interventions, if any, are to be executed. This time is herein referred to as the optimal time to decide to execute an intervention to emphasize that when the time is fixed it is not yet known if interventions will actually be executed. Such a methodology is particularly useful in the management of railway infrastructure that belongs to a multinational freight corridor where multiple railway management organizations are involved. Every time one executes an intervention it can affect the flow of trains on the part of the infrastructure controlled by others. In the methodology an adaptation of the model used to value options in financial engineering using the Black and Scholes differential equation is used. The model enables the valuation of the ability to wait to decide to determine whether or not an intervention should be executed. The methodology is demonstrated by determining the optimal time to decide to execute interventions on a fictive rail corridor for a railway management organization. Use of the methodology is expected to improve the coordination of the execution of interventions on multiple parts of the corridor, and give a period of time in which it is relatively certain that no interventions will be executed.

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Maintenance and decommissioning real options models for life-cycle cost-benefit analysis of offshore platforms

Cited by 20 publications

References 12 publications

International Journal of Prognostics and Health Management, ISSN 2153-2648, 2016 008 PHM-Based Wind Turbine Maintenance Optimization Using Real Options

International Journal of Prognostics and Health Management, ISSN 2153-2648, 2016 008 PHM-Based Wind Turbine Maintenance Optimization Using Real Options

A Real Option Approach to Determine Optimal Intervention Windows for Multi-National Rail Corridors

A real option methodology to determine the optimal intervention windows for railway infrastructure

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