Reliability Growth Analysis of Satellite Systems

John W. Evans, Mark P. Kaminskiy, and Luis D. Gallo Jr.
Submission Type: 
Full Paper
Supporting Agencies (optional): 
NASA Goddard Space Flight Center
phmc_12_128.pdf250.97 KBSeptember 20, 2012 - 11:04am

A reliability trend/growth analysis methodology for satellite systems is suggested. A satellite system usually consists of many satellites successively launched over many years, and its satellites typically belong to different satellite generations. This paper suggests an approach to reliability trend/growth data analysis for the satellite systems based on grouped data and the Power Law (Crow-AMSAA) Non-Homogeneous Poisson process model, for both one (time) and two (time and generation) variables. Based on the data specifics, the maximum likelihood estimates for the Power Law model parameters are obtained. In addition, the Cumulative Intensity Function (CIF) of a family of satellite systems was analyzed to assess its similarity to that of a repairable system. The suggested approaches are illustrated by a case study based on Tracking and Data Relay Satellite System (TDRSS) and Geostationary Operational Environmental Satellite (GOES) data.

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Publication Volume: 
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Submission Keywords: 
reliability growth
multivariate regression
Weibull distribution
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
Systems and platform applications
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