Estimation Of Basic And Mission Benefit Of Condition-Based Maintenance Deployment In HUMS Equipped AH-64 Aircraft Using NLP And Regression Analysis

Condition-based maintenance (CBM) is a maintenance practice that involves regular monitoring of the mechanical condition of components of interest, processing of information collected, and then decision-making to ensure both maximizing the time interval between repairs and minimizing the number of unscheduled failures. CBM also offers early detection of failure which can prevent major breakdowns and repairs. Vibration monitoring is one of the effective techniques for condition monitoring. Health and Usage Monitoring System (HUMS) is a powerful tool for aviation industry which monitors health status and trending data. Vibration Monitoring Unit (VMU) and Modernized Signal Processing Unit (MSPU) are two forms of HUMS used in AH-64 aircraft to implement CBM enabled environment. The tangible and intangible benefits of applying CBM concepts through HUMS in Army aviation is already well established. This dissertation aims to propose methods for further evaluation of value added to the system by implementing HUMS and CBM methodologies. This research involves two major case studies which addresses the two categories of benefits: tangible and intangible. Tangible benefits are measurable in monetary value, whereas intangibles are not. Reduction in part cost, and maintenance flight hours, increase in flight hour, decrease in mission aborts etc. are various form of tangible benefits. Intangible benefits are seen as an important indicator of overall effectiveness of CBM implementation. This creates incentives for Army personnel at all levels to adopt this practice. This is measured from the survey responses of Army maintainers, crews and pilots. But as survey responses are subject to dynamic human behavior, this a continuous evaluation process which should be repeated time-to–time. The first case study presents a step in the direction of better understanding of how mission benefit areas like morale, sense of safety etc. are perceived by army personnel who fly and maintain Army aircraft equipped with HUMS. Response data collected from seventy-six helicopter personnel was analyzed and a multiple linear regression model is proposed reducing survey time by 30% keeping the accuracy same. US Army is currently the world’s largest user of HUMS. This system requires cost to install, monitor and maintain. It is important to measure whether the benefit outweighs the cost. The goal of the second case study is to address the possible sources of benefits, estimate costs in forms of investments, quantify them in monetary values and finally measure the effectiveness though estimating return on investment. The significance of this study lies in its data collection, interpretation and analysis process