Costs associated to unscheduled and excessively prudent maintenance can contribute significantly to an airline's expenditure. Due to the complex nature of aviation related operations, reliability practices have been limited. In an attempt to improve component reliability, i.e. reduce maintenance-related costs, a new strategy was proposed which pursuits new avenues w.r.t. reliability modelling. The strategy focusses on identifying operational factors affecting component reliability and assessing whether these can be used to reduce the number of unscheduled occurrences (i.e. failures). Currently, reliability models are limited to exponential distributions, which assume hazard rates remain constant throughout the component's operational life. Studies have shown that time-independent Proportional Hazard Models (PHMs) could improve overall reliability, however, due to poor data, this was not verified. In this solution, the benefits of both time-independent and -dependent PHMs are assessed. Furthermore, underlying hazard functions were supplemented by introducing: normal, log-normal, logistic, exponential, Weibull, and gamma distributions. To address repairables, restoration events were simulated using Kijima type II General Repair Processes (GRPs). This project would not have been possible without the cooperation of QantasLink that supplied the data required. Results obtained from analysing historical data of the top ten components w.r.t. unscheduled removals indicated that adopting new maintenance schedules, derived from the proposed reliability models, could reduce the number of unscheduled occurrences by approximately 37% while limiting the increase in Mean Time Till (next) Repair (MTTRep). The variables identified by the solution were validated using literature, however, due to variable reduction and data limitations, the exact nature of component failures is yet to be established. Undeniably the potential benefits of adopting the proposed strategy are extensive. Nonetheless, numerous assumptions were introduced to overcome challenges imposed by the complex nature of the data. To overcome these challenges, recommendations and suggestions were proposed for the future development of airline reliability practices.