Development of an integrated information system for automated scheduling and control management in an aircraft maintenance plant

Chiang, Pu Hai; Torng, Chau Chen

doi:10.1504/ijise.2014.057942

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…Cheung et al (2005), propose an expert system for allocation of labor for aircraft maintenance services. Some of the literature pertaining to heavy aircraft maintenance checks include scheduling, sequencing and work planning (Samaranayake and Kiridena, 2012;Chiang and Torng, 2014), manpower planning (Bazargan 2004;De Bruecker et al, 2014), safety and quality (Ahmadi et al, 2010;Quinlan et al, 2013) and human factors concerns (Drurya et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Airline maintenance strategies – in-house vs. outsourced – an optimization approach

Bazargan

2016

Journal of Quality in Maintenance Engineering

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Purpose – The purpose of this paper is to offer a new mathematical modeling approach to help airlines identify which types of heavy aircraft maintenance checks be performed in-house or outsourced. Design/methodology/approach – This study offers a mathematical model to minimize the total cost of heavy maintenance programs over a planning period subject to performing all maintenance programs on time and other side constraints. Findings – The results are very encouraging and somewhat counter-intuitive. The solutions recommend that more expensive and labor intensive checks be outsourced. A detailed analyses of the total maintenance cost breakdown is presented with implications and recommendation. Originality/value – To the best of the knowledge, the literature on quantitative models for airline in-house and outsourced maintenance checks is very limited. The author believes the model and airline cases presented in this paper can help airlines with their strategic maintenance strategies and will initiate further studies in this important area.

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Section: Introductionmentioning

confidence: 99%

Airline maintenance strategies – in-house vs. outsourced – an optimization approach

Bazargan

2016

Journal of Quality in Maintenance Engineering

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“…On the other hand, heavy aircraft maintenance literature focuses on four important fields: reliability, safety and quality (Ahmadi et al , 2010; Quinlan et al , 2013); human factors (Drurya et al , 2010; Shanmugam and Robert, 2015); workforce optimization (Dijkstra et al , 1994; Alfares, 1999; Krishnasamy et al , 2005; Cheung et al , 2005b; Lind, 2009; Lodree et al , 2009); and planning and scheduling (Bazargan, 2004; Samaranayake and Kiridena, 2012; Chiang and Torng, 2014; De Bruecker et al , 2014). …”

Section: Introductionmentioning

confidence: 99%

“…planning and scheduling (Bazargan, 2004; Samaranayake and Kiridena, 2012; Chiang and Torng, 2014; De Bruecker et al , 2014).…”

Section: Introductionmentioning

confidence: 99%

A stochastic detailed scheduling model for periodic maintenance of military rotorcraft

Semaan

Yehia

2019

AEAT

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Purpose The purpose of this paper is to develop a stochastic detailed schedule for a preventive/scheduled/periodic maintenance program of a military aircraft, specifically a rotorcraft or helicopter. Design/methodology/approach The new model, entitled the military “periodic aviation maintenance stochastic schedule” (PAM-SS), develops a stochastic detailed schedule for a PUMA SA 330SM helicopter for the 50-h periodic inspection, using cyclic operation network (CYCLONE) and Monte Carlo simulation (MCS) techniques. The PAM-SS model identifies the different periodic inspection tasks of the maintenance schedule, allocates the resources required for each task, evaluates a stochastic duration of each inspection task, evaluates the probability of occurrence for each breakdown or repair, develops the CYCLONE model of the stochastic schedule and simulates the model using MCS. Findings The 50-h maintenance stochastic duration follows a normal probability distribution and has a mean value of 323 min and a standard deviation of 23.7 min. Also, the stochastic maintenance schedule lies between 299 and 306 min for a 99 per cent confidence level. Furthermore, except the pilot and the electrical team (approximately 90 per cent idle), all other teams are around 40 per cent idle. A sensitivity analysis is also performed and yielded that the PAM-SS model is not sensitive to the number of technicians in each team; however, it is highly sensitive to the probability of occurrence of the breakdowns/repairs. Practical implications The PAM-SS model is specifically developed for military rotorcrafts, to manage the different resources involved in the detailed planning and scheduling of the periodic/scheduled maintenance, mainly the 50-h inspection. It evaluates the resources utilization (idleness and queue), the stochastic maintenance duration and identifies backlogs and bottlenecks. Originality/value The PAM-SS tackles military aircraft planning and scheduling in a stochastic methodology, considering uncertainties in all inspection task durations and breakdown or repair durations. The PAM-SS, although developed for rotorcrafts can be further developed for any other type of military aircraft or any other scheduled maintenance program interval.

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Life cycle assessment of an aircraft component: a case study

Veeramanikandan¹,

Nithish²,

Sivaraj³

et al. 2017

IJISE

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Development of an integrated information system for automated scheduling and control management in an aircraft maintenance plant

Cited by 5 publications

References 22 publications

Airline maintenance strategies – in-house vs. outsourced – an optimization approach

Airline maintenance strategies – in-house vs. outsourced – an optimization approach

A stochastic detailed scheduling model for periodic maintenance of military rotorcraft

Life cycle assessment of an aircraft component: a case study

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