Assessing the influence of the scale of operations on maintenance costs in the airline industry

Vega, Diego Javier Gonzales; Pamplona, Daniel Alberto; Oliveira, Alessandro V. M.

doi:10.1590/2238-1031.jtl.v10n3a2

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…Preventive maintenance (PM) is defined as all actions performed at defined intervals to retain an item in a serviceable condition by systematic inspection, detection, replacement of items that have worn out, adjustment, calibration, and cleaning (Gonzales-Vega et al 2016). In this way, optimization models can help to determine effective and efficient maintenance schedules and plans in complexes of architectural heritage buildings.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Modeling of the Functional Service Life of Architectural Heritage Buildings

Prieto

Macías-Bernal

Diego

et al. 2017

J. Perform. Constr. Facil.

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This paper addresses maintenance planning in heritage buildings. Currently, social, economic, and environmental factors raise concerns about the durability and service life of buildings. This study on the service life of historical buildings in terms of functionality presents a complex analysis that has yet to be developed in great depth. In this sense, a new expert system based on fuzzy logic for the prognosis of the functional service life of buildings is established. The system developed intends to manage vulnerabilities and risk variables that affect a building's performance. These parameters are involved in the building management and maintenance process and indicate durability in terms of serviceability as an output model parameter. The aim of this paper is to describe a new application of a fuzzy inference system based on expert knowledge. This approach discusses the serviceability of architectural heritage buildings using a Mamdani fuzzy model. In this methodology, the vulnerability and risk condition of nine theoretical case studies and five real buildings located in southern Spain are analyzed. In this case study, the application model is shown in a set of a five heritage buildings situated in southern Europe (Andalusia, Spain), which were only analyzed through in situ visual inspections. This system is able to give priorities relating to preventive conservation activities in homogeneous groups of heritage buildings. The approach gives useful information based on a functional criterion regarding the current state of the buildings. The fuzzy model aims to be an indicator for the future evolution of a building's functionality.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Modeling of the Functional Service Life of Architectural Heritage Buildings

Prieto

Macías-Bernal

Diego

et al. 2017

J. Perform. Constr. Facil.

View full text Add to dashboard Cite

show abstract

“…In this sense, preventive maintenance covers all actions that are conducted at defined intervals to retain an item in a condition of use. These actions are performed through systematic inspection, de-tection, replacement of worn items, adjustment, calibration and cleaning (Vega et al, 2016). From this approach, greater importance is given to tools that allow better management for the care of heritage buildings.…”

Section: Introductionmentioning

confidence: 99%

Expert Panel on in-Situ Visual Inspections for Masonry Churches Maintenance Stage

Carpio

Ortega

Prieto

2021

Journal of Civil Engineering and Management

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The incorporation of protocols in heritage building preservation is important for the definition of preventive conservation actions. Such integration is needed to avoid restoration actions and to promote preventive maintenance instead of corrective maintenance actions. This paper presents the application of an innovative digital management system using artificial intelligence that can quantify the suitability of a sample. This kind of application can support the maintenance management of buildings and minimise human error in data collection. The fuzzy system showed slight differences between the members of the expert panel during the in-situ visual inspection. These results indicate that, despite differences between various experts’ evaluation of a building, the proposed digital method helps minimise the uncertainty in the results. The paper highlights input variables, which present high dispersion (load state modification, fire and occupancy), and input parameters, which present low dispersion (preservation, roof design and overloads). Fuzzy systems can adequately manage the uncertainties associated with different experts’ assessment of sample that present constructive homogeneity. This study can give advantages to stakeholders during the inspection, diagnosis and evaluation stages in the improvement of mitigation policies focused on preventive maintenance programs dedicated to the resilience of heritage buildings, specifically churches emplaced in Chile.

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“…Therefore, the proposed mathematical model cannot be used to estimate the availability of avionics systems. An empirical model to estimate the unit cost per hour depending on the total flight time, aircraft size, load factor, average flight time, exchange rate, number of passengers per airline, and gross domestic production was proposed in [19]. The proposed cost equation is purely economic in nature and cannot be used to select the optimal option of avionics maintenance.…”

Section: Introductionmentioning

confidence: 99%

Maintenance Model of Digital Avionics

Raza

2018

Aerospace

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Abstract:The cost of avionics maintenance is extremely high for modern aircraft. It can be as high as 30% of the aircraft maintenance cost. A great impact on the cost of avionics maintenance is provided by a high level of No Fault Found events (NFF). Intermittent faults are the leading cause of the NFF appearance in avionics. The NFF rate for avionics systems is between 20% and 50%. The practice of avionics operation and maintenance confirms the relevance of assessing the impact of intermittent faults on the maintenance cost and the choice of such option of the maintenance management, in which the negative impact of the intermittent faults is minimized. In this paper, a new mathematical model of digital avionics maintenance is developed. Key maintenance effectiveness indicators are selected. General mathematical expressions are obtained for the average availability, mean time between unscheduled removals (MTBUR), and expected maintenance cost of single unit and redundant avionics systems, which are subject to permanent failures and intermittent faults. The dependence of the maintenance effectiveness indicators on the rate of permanent failures and intermittent faults is investigated for the case of exponential distribution of time to failures and faults. The dependence of average availability on the number of spare units in the airline's warehouse is also analyzed. On the base of the proposed maintenance model, different options of avionics maintenance management are considered. Numerical examples illustrate how to reduce the expected maintenance cost of avionics systems.

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Assessing the influence of the scale of operations on maintenance costs in the airline industry

Cited by 7 publications

References 3 publications

Fuzzy Modeling of the Functional Service Life of Architectural Heritage Buildings

Fuzzy Modeling of the Functional Service Life of Architectural Heritage Buildings

Expert Panel on in-Situ Visual Inspections for Masonry Churches Maintenance Stage

Maintenance Model of Digital Avionics

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