Proactive Fault Detection And Component Planning To Support Helicopter Logistic Processes

Abstract

Digitization, process optimization, servitization and customer proximity are key elements for competing in the nowadays aerospace context. Consistent with these directions, the development and delivery of data-driven services, i.e., services based on the exploitation of available data, aimed at improving the level of service offered to customers with the enhancement of helicopter logistic processes and component planning activities. These services promote a paradigm shift in customer support: from being primarily reactive to events that have occurred, reaching the excellence of the current 24/7 FOC service, to a proactive and predictive approach, diagnostics, statistical and prognostic prediction capabilities enabled by the use of data (e.g., in-flight data, transactional data, ground reliability data, As-Built and As-Maintained Configuration). More in detail, an ecosystem of digital services described in the following represents an application and industrialization of statistical analytical solutions within the aerospace industry, and the development of prognostic solutions based on ML and AI applied to a cutting-edge context (predicting un-scheduled maintenance events), with limited reference literature. In this paper, the ecosystem of digital services is discussed in detail, spanning from an approach able to foresee scheduled and un-scheduled removals on the in-service fleet, to a customer-tailored tool supporting the maintenance event scheduling as well as component booking. Potential benefits have been evaluated after an early adoption session resulting in an increase in forecast accuracy and in spare parts availability.