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Analysing Uncertainty and Delays in Aircraft Heavy Maintenance

Salazar Rosales, Leandro Julian

[Thesis]. Manchester, UK: The University of Manchester; 2016.

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Abstract

Analysing Uncertainty and Delays in Aircraft Heavy MaintenanceThe University of ManchesterLeandro Julian Salazar RosalesDoctor of PhilosophyDecember, 2015This study investigates the influence of unscheduled maintenance activities on delays and disruptions during the execution of aircraft heavy maintenance services by developing a simulation model based on Systems Dynamics (SD) and supported by an Evidential Reasoning (ER) rule model.The SD model studies the complex interrelationship between scheduled and unscheduled tasks and its impact on delays during a maintenance service execution. It was found that the uncertain nature of the unscheduled maintenance tasks hinders the planning, control and allocation of resources, increasing the chances to miss deadlines and incur in cost overruns. Utilising causal loop diagrams and SD simulation the research explored the relevance that the resource allocation management, the precise estimation of the unscheduled tasks and their prompt identification have on the maintenance check duration. The influence that delays and attitudes in the decision-making process have on project performance was also investigated.The ER rule model investigates the uncertainty present during the execution of a maintenance check by providing a belief distribution of the expected unscheduled maintenance tasks. Through a non-parametric discretisation process, it was found that the size and array of distribution intervals play a key role in the model estimation accuracy. Additionally, a sensitivity analysis allowed the examination of the significance that the weight, reliability and dependence of the different pieces of evidence have on model performance. By analysing and combining historical data, the ER rule model provides a more realistic and accurate prediction to analyse variability and ambiguity.This research extends SD capabilities by incorporating the ER rule for analysing system uncertainty. By using the belief distributions provided by the ER model, the SD model can simulate the variability of the process given certain pieces of evidence.This study contributes to the existing knowledge in aircraft maintenance management by analysing, from a different perspective, the impact of uncertain unscheduled maintenance activities on delays and disruptions through an integrated approach using SD and the ER rule. Despite the fact that this research focuses on studying a particular problem in the airline industry, the findings and conclusions obtained could be used to understand and address problems embodying similar characteristics. Therefore, it can be argued that, due to the close similarities between the heavy maintenance process and complex projects, these contributions can be extended to the Project Management field.

Layman's Abstract

This study investigates the influence of unscheduled maintenance activities on delays and disruptions during the execution of aircraft heavy maintenance services by developing a simulation model based on Systems Dynamics (SD) and supported by an Evidential Reasoning (ER) rule model.Delays and cost overruns are mainly caused by the difficulty in managing a large number of maintenance activities and the considerable amount of limited resources required to accomplish them. Moreover, during the execution of the maintenance scheduled tasks, unexpected damage and failures are commonly discovered, which must be corrected by programming additional unplanned maintenance activities. As a result, the uncertainty of these unexpected maintenance activities triggers a complex interaction between scheduled and unscheduled maintenance tasks.The application of SD (utilising causal loop diagrams and SD simulation) provides a system-wide viewpoint to investigate the effect that unscheduled maintenance tasks have on maintenance check duration. The causal loop diagrams help to elucidate the complex interrelationship between scheduled and unscheduled tasks and its impact on delays during project execution. The SD simulation model provides a platform for exploring and analysing the impact of the occurrence and discovery of discrepancies during a maintenance check and for testing different maintenance strategies regarding workforce allocation. The ER rule is applied for building an inference model to estimate the unscheduled maintenance tasks that can occur during the execution of a maintenance check. By analysing and combining historical data related to the usage and maintenance of an aeroplane, this model provides a belief distribution of the unscheduled tasks rather than a rough estimation or an average value, commonly assumed in aircraft maintenance management studies. The ER rule model is used as a complementary method to describe the uncertainty of the process, principally for its ability to analyse variability and ambiguity and to provide a more realistic and accurate prediction. The integrated SD-ER model can be utilised as a supporting tool to experiment with and assess strategies for planning and controlling aircraft maintenance services. It provides a means for studying a recurrent and relevant problem in the aviation industry from a different perspective, complementing the tools traditionally used to analyse it. This research attempts to analyse from a novel point of view the uncertainty of unforeseen events that can cause delays and disruption in complex projects.

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Business and Management
Publication date:
Location:
Manchester, UK
Total pages:
326
Abstract:
Analysing Uncertainty and Delays in Aircraft Heavy MaintenanceThe University of ManchesterLeandro Julian Salazar RosalesDoctor of PhilosophyDecember, 2015This study investigates the influence of unscheduled maintenance activities on delays and disruptions during the execution of aircraft heavy maintenance services by developing a simulation model based on Systems Dynamics (SD) and supported by an Evidential Reasoning (ER) rule model.The SD model studies the complex interrelationship between scheduled and unscheduled tasks and its impact on delays during a maintenance service execution. It was found that the uncertain nature of the unscheduled maintenance tasks hinders the planning, control and allocation of resources, increasing the chances to miss deadlines and incur in cost overruns. Utilising causal loop diagrams and SD simulation the research explored the relevance that the resource allocation management, the precise estimation of the unscheduled tasks and their prompt identification have on the maintenance check duration. The influence that delays and attitudes in the decision-making process have on project performance was also investigated.The ER rule model investigates the uncertainty present during the execution of a maintenance check by providing a belief distribution of the expected unscheduled maintenance tasks. Through a non-parametric discretisation process, it was found that the size and array of distribution intervals play a key role in the model estimation accuracy. Additionally, a sensitivity analysis allowed the examination of the significance that the weight, reliability and dependence of the different pieces of evidence have on model performance. By analysing and combining historical data, the ER rule model provides a more realistic and accurate prediction to analyse variability and ambiguity.This research extends SD capabilities by incorporating the ER rule for analysing system uncertainty. By using the belief distributions provided by the ER model, the SD model can simulate the variability of the process given certain pieces of evidence.This study contributes to the existing knowledge in aircraft maintenance management by analysing, from a different perspective, the impact of uncertain unscheduled maintenance activities on delays and disruptions through an integrated approach using SD and the ER rule. Despite the fact that this research focuses on studying a particular problem in the airline industry, the findings and conclusions obtained could be used to understand and address problems embodying similar characteristics. Therefore, it can be argued that, due to the close similarities between the heavy maintenance process and complex projects, these contributions can be extended to the Project Management field.
Layman's abstract:
This study investigates the influence of unscheduled maintenance activities on delays and disruptions during the execution of aircraft heavy maintenance services by developing a simulation model based on Systems Dynamics (SD) and supported by an Evidential Reasoning (ER) rule model.Delays and cost overruns are mainly caused by the difficulty in managing a large number of maintenance activities and the considerable amount of limited resources required to accomplish them. Moreover, during the execution of the maintenance scheduled tasks, unexpected damage and failures are commonly discovered, which must be corrected by programming additional unplanned maintenance activities. As a result, the uncertainty of these unexpected maintenance activities triggers a complex interaction between scheduled and unscheduled maintenance tasks.The application of SD (utilising causal loop diagrams and SD simulation) provides a system-wide viewpoint to investigate the effect that unscheduled maintenance tasks have on maintenance check duration. The causal loop diagrams help to elucidate the complex interrelationship between scheduled and unscheduled tasks and its impact on delays during project execution. The SD simulation model provides a platform for exploring and analysing the impact of the occurrence and discovery of discrepancies during a maintenance check and for testing different maintenance strategies regarding workforce allocation. The ER rule is applied for building an inference model to estimate the unscheduled maintenance tasks that can occur during the execution of a maintenance check. By analysing and combining historical data related to the usage and maintenance of an aeroplane, this model provides a belief distribution of the unscheduled tasks rather than a rough estimation or an average value, commonly assumed in aircraft maintenance management studies. The ER rule model is used as a complementary method to describe the uncertainty of the process, principally for its ability to analyse variability and ambiguity and to provide a more realistic and accurate prediction. The integrated SD-ER model can be utilised as a supporting tool to experiment with and assess strategies for planning and controlling aircraft maintenance services. It provides a means for studying a recurrent and relevant problem in the aviation industry from a different perspective, complementing the tools traditionally used to analyse it. This research attempts to analyse from a novel point of view the uncertainty of unforeseen events that can cause delays and disruption in complex projects.
Thesis main supervisor(s):
Thesis co-supervisor(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:300089
Created by:
Salazar Rosales, Leandro
Created:
11th April, 2016, 13:25:04
Last modified by:
Salazar Rosales, Leandro
Last modified:
20th April, 2016, 09:22:58

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