Aircraft accident evaluation using quality assessement tools

The case study is focused on the application of principal quality tools in a fourth generation jet fighter to evaluate a maintenance activity in an accident investigation process. The paper assesses aircraft engineers’ performance on checking aircraft tyre inflation pressure before the aircraft’s flight. Process evaluation is organized by the application of fundamental quality tools in order to provide vital information regarding the level of control. The methodology combines the benefits of statistical quality control, root cause determination, and preventive actions, to eliminate maintenance discrepancy in the future. The methodology revealed an approach to generate useful safety metrics from incident reporting data. Furthermore, this study pointed out the significance of participation at all technician levels for the successful implementation of Total Quality Management (TQM). Also, it discusses the value of TQM in aviation and suggests that continuous improvement is still needed. The paper is based on practical work being undertaken in a military squadron and, therefore, is demonstrated to be practical in an aviation environment. This study would encourage aviation personnel to rely on TQM methods for performing quality assessment monitoring and achieving continuous improvement

Development of a relationship management framework and related performance matrics for outsourced aircraft maintenance

Driven by an intensely competitive world, the use of outsourcing is extensive and growing especially in the service business area. Outsourcing provides companies with benefits such as cost reduction and performance enhancement. Despite these advantages, companies need to be aware that successful outsourcing requires an appropriate long term strategy in managing the relationships with their providers. In turn, the providers have to develop collaborative relationships with their customers in order to improve customer satisfaction. Although relationship management of relevance to outsourcing is recognised as an important concept, it has not received attention from both practitioners and researchers, especially with regard to aircraft maintenance outsourcing which is considered to be critical outsourcing associated with high financial and strategic risks. Therefore, the aim of this research study is “to improve aircraft maintenance outsourcing through relationship management”. This research has been divided into three stages to achieve the research aim. The first stage related to an exploration of the key factors for the management of outsourcing relationship, starting with a review of the relevant literature. A multiple case study was then selected to investigate today’s practices of the management of the IT outsourcing relationship, which has similar characteristics to aircraft maintenance outsourcing. A questionnaire survey was also conducted to explore key factors of relationship management for aircraft maintenance outsourcing. With these three sources of evidence, a conclusive finding is that relationship management of relevance to outsourcing comprises six key factors which are clearly defined requirements, agreement, delivery governance, service delivery, performance evaluation and inter-organisational coordination. The second stage focused on exploring how the relationship between an aircraft maintenance provider and an aircraft maintenance customer is managed. The three cases study relationships featuring the four case companies were selected to carry out an in-depth investigation of relationship management for aircraft maintenance outsourcing. The researcher used interview, observation and documentation to collect data from these four case companies. The findings showed that the six key factors identified in the first stage influence the establishment and development of the relationship between the aircraft maintenance provider and customer. Moreover, external factors also have an impact on the way that both parties manage their relationship. The third stage was to develop a proposed approach to performance measurement which is viewed as a key factor of the management of the relationship between an aircraft maintenance provider and an aircraft maintenance customer. The researcher conducted an action research in cooperation with the main subject of this research. The study discovered that the gap model is applicable for performance measurement in aircraft maintenance outsourcing. The improved version of performance measurement model includes new performance metrics that are essential for monitoring the gaps between the provider and customer

Applicability and Interpretability of Logical Analysis of Data in Condition Based Maintenance

Résumé Cette thèse étudie l’applicabilité et l’adaptabilité d’une approche d’exploration de données basée sur l’intelligence artificielle proposée dans [Hammer, 1986] et appelée analyse logique de données (LAD) aux applications diagnostiques dans le domaine de la maintenance conditionnelle CBM). La plupart des technologies utilisées à ce jour pour la prise de décision dans la maintenance conditionnelle ont tendance à automatiser le processus de diagnostic, sans offrir aucune connaissance ajoutée qui pourrait être utile à l’opération de maintenance et au personnel de maintenance. Par comparaison à d’autres techniques de prise de décision dans le domaine de la CBM, la LAD possède deux avantages majeurs : (1) il s’agit d’une approche non statistique, donc les données n’ont pas à satisfaire des suppositions statistiques et (2) elle génère des formes interprétables qui pourraient aider à résoudre les problèmes de maintenance. Une étude sur l’application de la LAD dans la maintenance conditionnelle est présentée dans cette recherche dont l’objectif est (1) d’étudier l’applicabilité de la LAD dans des situations différentes qui nécessitent des considérations particulières concernant les types de données d’entrée et les décisions de maintenance, (2) d’adapter la méthode LAD aux exigences particulières qui se posent à partir de ces applications et (3) d’améliorer la méthodologie LAD afin d’augmenter l’exactitude de diagnostic et d’interprétation de résultats. Les aspects innovants de la recherche présentés dans cette thèse sont (1) l’application de la LAD dans la CBM pour la première fois dans des applications qui bénéficient des propriétés uniques de cette technologie et (2) les modifications innovatrices de la méthodologie de la LAD, en particulier dans le domaine de la génération des formes, afin d’améliorer ses performances dans le cadre de la CBM et dans le domaine de classification multiclasses. La recherche menée dans cette thèse a suivi une approche évolutive afin d’atteindre les objectifs énoncés ci-dessus. La LAD a été utilisée et adaptée à trois applications : (1) la détection des composants malveillants (Rogue) dans l’inventaire de pièces de rechange réparables d’une compagnie aérienne commerciale, (2) la détection et l’identification des défauts dans les transformateurs de puissance en utilisant la DGA et (3) la détection des défauts dans les rotors en utilisant des signaux de vibration. Cette recherche conclut que la LAD est une approche de prise de décision prometteuse qui ajoute d’importants avantages à la mise en oeuvre de la CBM dans l’industrie.----------Abstract This thesis studies the applicability and adaptability of a data mining artificial intelligence approach called Logical Analysis of Data (LAD) to diagnostic applications in Condition Based Maintenance (CBM). Most of the technologies used so far for decision support in CBM tend to automate the diagnostic process without offering any added knowledge that could be helpful to the maintenance operation and maintenance personnel. LAD possesses two key advantages over other decision making technologies used in CBM: (1) it is a non-statistical approach; as such no statistical assumptions are required for the input data, and (2) it generates interpretable patterns that could help solve maintenance problems. A study on the implementation of LAD in CBM is presented in this research whose objective are to study the applicability of LAD in different CBM situations requiring special considerations regarding the types of input data and maintenance decisions, adapt the LAD methodology to the particular requirements that arise from these applications, and improve the LAD methodology in line with the above two objectives in order to increase diagnosis accuracy and result interpretability. The novelty of the research presented in this thesis is (1) the application of LAD to CBM for the first time in applications that stand to benefit from the advantages that this technology provides; and (2) the innovative modifications to LAD methodology, particularly in the area of pattern generation, in order to improve its performance within the context of CBM. The research conducted in this thesis followed an evolutionary approach in order to achieve the objectives stated in the Introduction. The research applied LAD in three applications: (1) the detection of Rogue components within the spare part inventory of reparable components in a commercial airline company, (2) the detection and identification of faults in power transformers using DGA, and (3) the detection of faults in rotor bearings using vibration signals. This research concludes that LAD is a promising decision making approach that adds important benefits to the implementation of CBM in the industry