As air operators seek to streamline their avenues of expenditure, increasing attention is being paid to the role of knowledge engineering in high frequency maintenance of aircraft parts and components. In line with this, a recently published study commissioned by Susana Ferreiro, a computer engineer of Donostia-San Sebastián, addressed several factors of assistance to air operators in reducing their maintenance costs and improving air safety in the long term. The research focused on high frequency maintenance issues including the degradation of aircraft brakes, the appearance of burrs during the manufacture of components and the deterioration of oil quality used in lubrication. The results of the study provide topical value to fleet managers seeking to optimise their maintenance expenditures while offering sound reasoning in support of improved standards of flight safety.
‘Irrespective of the fleet scope, maintenance costs routinely account for anywhere between 10 and 45 percent of annual operating expenses. In any case, this equates to a substantial outlay for air operators. As no reasonable fleet manager would permit a drop in maintenance standards in an effort to reduce costs, many are turning to the role played by knowledge engineering in order to sustain a healthy level of competitiveness. This study was interesting from the point of view that it applied techniques based on artificial intelligence, data mining and machine learning to enhance certain elements of aircraft maintenance. Although it is too early to tell whether this study will hold a major bearing on changes to aircraft maintenance practices, we are always open to new ideas aimed at addressing lingering problems within the aviation industry,’ comments Dainius Sakalauskas, the Deputy Head of FL Technics Training.
Managing brake wear limits for aircraft landing gear entails routine line inspections of the assembly. Organised as part of the European TATEM project for increasing aircraft operability by managing the time and cost outlay for scheduled maintenance, the study made use of algorithms to model solutions to the predictive maintenance of aircraft brake wear. Specifically, the research looked into estimating the wear of individual brake components in order to plan an effective allocation of resources. This in turn would allow maintenance to be deferred to optimal locations (and times) as well as improve flight punctuality by lessening delays caused by corrective maintenance.
Additionally, the research sought solutions to controlling the emergence of burrs during the manufacture of aircraft parts. As mandated by the aviation industry, burrs (a material edge disturbance often caused by drilling) must not exceed 127 microns. The study aimed to develop a process whereby checks carried out for material burrs could be optimised by using the internal signals of a drilling machine to detect in real time when the burr limit has been exceeded. The process routinely and wholly applied to control material burring could thus be applied only when actually necessary.
Perhaps more notably however, the research proposed a model for detecting the extent of oil degradation (used in component lubrication) without the costly requirement for laboratory testing. It focused on spectrometric techniques to determine the basicity of the oil and thereby advise on its current state. As the properties of oil deplete over time, its monitoring is vital to ensure effective lubrication of various aircraft components. The method allows for a sensor to be incorporated into what is being monitored, making expensive lab testing near redundant.
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