Investigating the Desirability of Navy Aircraft Service Life Extension Programs

Keating, Edward G.; Blickstein, Irv; Boito, Michael; Chandler, Jess; Peetz, Deborah

doi:10.1080/10242694.2013.821234

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…2 Related to this line of research are other studies more specifically focused on calibrating the optimal time to replacement of military equipment (e.g. Dixon 2005;Francis and Shaw 2000;Persselin 2002, 2003;Jondrow et al 2002;Keating et al 2014; see Maybury 2015 for a thorough review of this literature).…”

Section: Introductionmentioning

confidence: 97%

The long term effects of an aging fleet on operational availability and cost: evidence from the U.S. coast guard

Lavin

McNab

Sullivan

2016

Defence and Peace Economics

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This paper empirically examines whether the aging of a fleet affects operational availability and operating cost using a unique data-set on the 117 47-foot Motor Lifeboats (MLBs) of the United States Coast Guard (USCG). Procured from 1997 to 2003, the 47-foot MLB is the standard lifeboat of the USCG and all 117 MLBs remain in service. The aging of the MLB fleet has resulted in higher annual operating costs and lower operational availability, although the nature of this relationship remains unclear. Our estimation strategy utilizes an error components estimator to examine these issues. We employ three variants of the dependent variables (i.e. the standard logarithmic transformation as is most commonly seen in the literature, inverse hyperbolic sine [IHS], and level outcomes). The point estimates from the standard logarithmic model finds operational availability for the MLBs decreases at a rate between 0.83 and 1.8% per year and cost increases at a rate between 0.33 and 7.81% per year. Similar effects are shown with the IHS and level outcome specifications. In terms of nonlinearity effects, we find the most pronounced changes in operational availability and cost occur for MLBs aged 15 years or more (in comparison to younger MLBs).

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Section: Introductionmentioning

confidence: 97%

The long term effects of an aging fleet on operational availability and cost: evidence from the U.S. coast guard

Lavin

McNab

Sullivan

2016

Defence and Peace Economics

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“…In modern industrial economics, the need for scientifically justified replacement decisions is increasing at an extremely rapid pace. Practical and effective replacement decisions are required for different assets, for example personal computers in higher education (Babbitt et al 2009), public infrastructure assets (Al-Douri et al 2020;van den Boomen et al 2019), machines and equipment in steel production (Šebo et al 2013), machines and equipment in forestry (Diniz and Sessions 2020), navy aircraft (Keating et al 2014) and expensive mining machinery (Al-Chalabi et al 2015a, b).…”

Section: Introductionmentioning

confidence: 99%

Development of an economic replacement time model for mining equipment: a case study

Al-Chalabi

2022

Life Cycle Reliab Saf Eng

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In mining operation equipment replacement represents a strategic decision problem. This paper presents an economic replacement time model for mining drill rigs. A total ownership cost minimization model was developed to optimize the lifetime of a drill rig used in Tara underground mine in Ireland. The developed methodology allows an innovative practical evaluation of the replacement process by applying sensitivity and regression analysis to rank the factors affecting the replacement time of existing and new models of the production drill rig. Compared to previous studies presented in the literature, the present study represents a further development in this field as it has resulted in a practical optimization model that can be used to estimate the economic replacement time of repairable equipment used in the mining and other production industries. The proposed model shows that the absolute economic replacement time of the drill rig investigated in this case study is 81 months and the mining company operating the rig can replace it with an identical one within an optimal replacement range of 6 months (i.e. from month 79–84) when the minimum total cost can still be achieved in practice. Sensitivity and regression analyses show that the maintenance cost has the largest impact on the economic replacement time of the drill rig. The study finds that decreasing the operating and maintenance costs of the drill rig will have the positive effect of increasing the economic replacement time linearly for a new model of the drill rig. The proposed model helps decision-makers to plan the replacement of old rigs and purchase new ones from an economic view point. Thus, this new model can be extended and used for more general applications in the mining industry.

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“…The need in scientifically justified replacement decisions increases fast in modern economy. Effective replacement decisions are urgently required for all asset categories, from personal computers in higher education (Babbitt et al, 2009), to expensive machinery in mining (Al-Chalabi et al, 2015), forestry (Diniz and Sessions, 2020) and steel production (Sebo et al, 2013), to the replacement of navy aircraft (Keating et al, 2014) and public infrastructure assets (van den Boomen et al, 2019). It happens because the purchasing price of machines and their operating and maintenance costs increase.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, many categories of industrial equipment should be replaced more frequently than in the past because of technological improvements (Regnier et al, 2004;Hartman, 2007;Mardin and Takeshi, 2012;Yatsenko and Hritonenko, 2016). Modern industrial reality with abundance of detailed data about various machine costs, technological improvements and possible strategic alternatives (Keating et al, 2014;Diniz and Sessions, 2020) requires combining classic replacement techniques, such as the EL method, with contemporary tools of data analytics.…”

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confidence: 99%

Analytics of machine replacement decisions: economic life vs real options

Yatsenko¹,

Hritonenko

2020

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PurposeDespite the existence of multiple asset replacement theories, the economic life replacement method remains a major practical technique for making rational machine replacement decisions. The purpose of this paper is to bridge this method with comprehensive data analytic tools and make it applicable it to modern business reality with abundant data on operating and replacement costs.Design/methodology/approachThis study employs operations research, discrete and continuous optimization, applied mathematical modeling, data analytics, industrial economics and real options theory.FindingsConstructed stochastic algorithms extend the deterministic economic life method and are compared to the contemporary theory of stochastic asset replacement based on real options and dynamic programming. It is proven that both techniques deliver similar results when the cost volatility is small. A major theoretic finding is that the cost uncertainty speeds up the replacement decision.Research limitations/implicationsThis research suggests that the proposed stochastic algorithms may become an important tool for managerial decisions about replacement of many similar machines with detailed data on operating and replacement costs.Originality/valueCompared to the real options replacement theory, major advantages of the proposed algorithms are that they work equally well for any distribution of age-dependent stochastic operating cost. The algorithms are tested on a real industrial case about replacement of medical imaging devices. Numeric simulation supports obtained analytic outcomes.

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Investigating the Desirability of Navy Aircraft Service Life Extension Programs

Cited by 7 publications

References 9 publications

The long term effects of an aging fleet on operational availability and cost: evidence from the U.S. coast guard

The long term effects of an aging fleet on operational availability and cost: evidence from the U.S. coast guard

Development of an economic replacement time model for mining equipment: a case study

Analytics of machine replacement decisions: economic life vs real options

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