GOALI/Collaborative Research: Improved Spare Parts Inventory Management in Aircraft Engines through Hybrid Sensing

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Abstract for Collaborative Research/GOALI: Improved Spare Parts Inventory Management in Aircraft Engines through Hybrid SensingThe objective of this GOALI award is to develop the basic science and necessary tools to transform sensor measurements from a large set of machine equipment in the field into reliable forecasts and inventory policies for the spare parts required to maintain that equipment. While equipment health monitoring is of relevance to many manufacturers, the application context of this research is commercial jet engines. The research consists of four key steps: advancing sensing methods and the interpretation of signals to diagnose engine condition; developing procedures for transforming this data into predictions of time-to-overhaul and resource-requirements; building part forecasting methods and inventory policies that aggregate this information across engines in the field, with consideration of usage and economic conditions; and creating a simulation tool for the monitoring and maintenance of a large fleet to validate the methodology. This research will establish a framework for modeling and simulating the process of engine maintenance, and will produce theoretical results that can be translated into applicable tools of practical value to the industrial partner and the aerospace industry at large, leading to improved forecasting and inventory management for spare parts. While currently-used sensor data can provide an indication of the overall health of the engine, the advanced sensing technologies developed in this research offer the potential to predict which specific parts will need replacement before an overhaul is initiated, thus providing more time to secure the necessary resources. This research will determine the economic impact of the additional health information and improved decision-making enabled by these advanced sensing technologies, and will potentially make the case for their pervasive installation. Although the models will primarily be validated within the industrial partner's business units, they will be beneficial to a wide array of manufacturing firms for whom after-sales service is a critical component of their business.