Spacecraft Reliability and Multi-State Failures: A Statistical Approach

SPACECRAFT RELIABILITY AND MULTI-STATE FAILURES ]SPACECRAFT RELIABILITY AND MULTI-STATE FAILURES A STATISTICAL APPROACH The aerospace community has long recognized and repeatedly emphasizes the importance of reliability for space systems. Despite this, little has been published in book form on the topic. Spacecraft Reliability and Multi-State Failures addresses this gap in the literature, offering a unique focus on spacecraft reliability based on extensive statistical analysis of system and subsystem anomalies and failures. The authors provide new results pertaining to spacecraft reliability based on extensive statistical analysis of on-orbit anomaly and failure data that will be particularly useful to spacecraft manufacturers and designers, for example in guiding satellite (and subsystem) test and screening programs and providing an empirical basis for subsystem redundancy and reliability growth plans. The authors develop nonparametric results and parametric models of spacecraft and spacecraft subsystem reliability and multi-state failures, quantify the relative contribution of each subsystem to the failure of the satellites thus identifying the subsystems that drive spacecraft unreliability, and propose advanced stochastic modeling and analysis tools for the reliability and survivability of spacecraft and space-based networks. Spacecraft Reliability and Multi-State Failures provides new nonparametric results pertaining to spacecraft reliability based on extensive statistical analysis of on-orbit anomaly and failure data develops parametric models of spacecraft and spacecraft subsystem reliability and multi-state failures quantifies the relative contribution of each subsystem to the failure of the satellites proposes advanced stochastic modeling and analysis tools for the reliability and survivability of spacecraft and space-based networks provides a dedicated treatment of the reliability and subsystem anomalies of communication spacecraft in geostationary orbit.

Table of Contents:
1 On time, reliability, and spacecraft 1 1.1 On time and reliability 1 1.1.1 Reliability: from the word to the engineering discipline 1 1.1.2 Brief (pre)history of reliability engineering: the enablers and the catalyst 2 1.2 On spacecraft and reliability: early studies 4 1.2.1 Overview of early spacecraft reliability and on-orbit failure studies 6 1.2.2 Beyond the failure rate emphasis in spacecraft reliability studies 7 1.3 Book organization 7 2 Nonparametric reliability analysis of spacecraft failure data 9 2.1 Introduction 9 2.2 Database and data description 10 2.3 Nonparametric analysis of spacecraft failure data 11 2.3.1 Complete versus censored data set 11 2.3.2 Empirical reliability function from a complete data set 13 2.3.3 Kaplan–Meier estimator 14 2.3.4 Kaplan–Meier plot of satellite reliability 16 2.4 Confidence interval analysis 17 2.5 Discussion and limitation 20 2.A Appendix 21 3 Parametric analysis and Weibull modeling of spacecraft reliability 23 3.1 Weibull distribution: an overview 24 3.2 Probability plots or graphical estimation 25 3.2.1 Procedure 25 3.2.2 Weibull plot and Weibull fit of spacecraft reliability 25 3.2.3 Advantages and limitations of the graphical estimation method 26 3.3 Maximum likelihood estimation (MLE) 27 3.3.1 MLE derivation of a Weibull distribution 28 3.3.2 MLE Weibull fit for spacecraft reliability 30 3.4 Comparative analysis of the spacecraft reliability parametric fits 31 3.4.1 MLE versus graphical estimation Weibull fits 31 3.4.2 MLE Weibull versus MLE lognormal fits 33 3.5 Finite mixture distributions 33 3.5.1 Methods for estimating parameters of mixture distributions 34 3.5.2 The 2-Weibull mixture distribution of spacecraft reliability 36 3.6 Comparative analysis of the single versus the mixture distribution Weibull fits 38 4 Data specialization: statistical analysis of spacecraft reliability by orbit and mass categories 43 4.1 Introduction 43 4.2 Data description and mass categorization 45 4.3 Nonparametric analysis of satellite reliability by mass category 46 4.4 Parametric analysis of satellite reliability by mass category 48 4.4.1 MLE of single Weibull fit 49 4.4.2 Mixture distributions 51 4.4.3 Failure rates 54 4.5 Orbit characterization 56 4.6 Nonparametric analysis of spacecraft reliability by mass and orbit category 57 4.7 Parametric analysis of satellite reliability by mass and orbit category 60 4.8 Hypotheses for causal explanations 61 4.8.1 Testing 63 4.8.2 Procurement and parts selection 63 4.8.3 Factors intrinsically related to the design of the spacecraft 64 4.8.4 Factors related to the space environment 65 4.A Appendix: Tabular data and confidence interval analysis 67 4.A.1 Tabular data for the nonparametric reliability results in Figure 4.1 and Figure 4.8 67 4.A.2 Confidence interval analysis 68 5 Spacecraft subsystem reliability 71 5.1 Spacecraft subsystem identification 71 5.2 Nonparametric reliability analysis of spacecraft subsystems 72 5.3 Weibull modeling of spacecraft subsystem reliability 75 5.4 Comparative analysis of subsystem failures 78 6 Time to anomaly and failure of spacecraft subsystems: exploratory data analysis 83 6.1 Introduction 83 6.2 Anomaly and failure events 84 6.3 Distribution of anomalies and failure events by subsystem 86 6.4 Time to anomaly and failure of spacecraft subsystems 90 7 Multi-state failure analysis of spacecraft subsystems 97 7.1 Introduction 97 7.2 Setting the stage: multi-state failure analysis and the state transition diagram 99 7.3 Nonparametric analyses of spacecraft subsystems’ multi-state failures 101 7.3.1 Censored data and the Kaplan–Meier estimator 101 7.3.2 Confidence interval analysis 103 7.3.3 Nonparametric estimations of the conditional probabilities of transitioning between states 103 7.4 Parametric analyses of spacecraft subsystems’ multi-state failures 108 7.4.1 MLE Weibull fit of the nonparametric estimates ˆPi j 108 7.4.2 Testing the parametric models of the multi-state failure analysis 109 7.5 Comparative reliability and multi-state failure analysis of spacecraft subsystems 113 7.5.1 Gyro subsystem 113 7.5.2 Thruster subsystem 115 7.5.3 TTC subsystem 117 7.A Appendix 118 8 Toward survivability analysis of spacecraft and space-based networks 123 8.1 Introduction 123 8.2 Overview of survivability and resiliency 124 8.2.1 On survivability 125 8.2.2 On resiliency 126 8.2.3 Comparing survivability and resiliency 127 8.3 Survivability framework 128 8.4 Introduction to stochastic Petri nets (SPNs) 129 8.5 SPNs for spacecraft modeling and survivability analysis 131 8.5.1 Testing the SPN models 138 8.5.2 Monte Carlo simulation runs for the SPN models 140 8.5.3 Results 141 8.5.4 Limitations 144 A.8 Appendix: SPN model of the space-based network (SBN) in Figure 8.6 and its schematic explanation 146 Epilogue 149 Appendix A Geosynchronous communication satellites: system reliability and subsystem anomalies and failures 151 A.1 Part I: System reliability analysis 151 A.1.1 Nonparametric analysis of satellite failure data 152 A.1.2 Confidence interval analysis 153 A.1.3 Parametric fits of geosynchronous communication satellite reliability 155 A.2 Part II: Subsystem anomalies and failures 160 A.2.1 Subsystem health scorecard 161 A.2.2 Comparative analysis of subsystem health scorecard 164 Appendix B Electrical power subsystem: comparative analysis of failure events in LEO and GEO 179 B.1 Introduction 179 B.2 Database, sample analyzed, and classes of failure events 180 B.3 Brief literature review 181 B.3.1 Space environment in LEO and GEO 181 B.3.2 Operational constraints on the EPS in LEO and GEO 182 B.4 Reliability and multi-state failure analyses of the EPS 182 B.5 Comparative analysis of the EPS failure behaviour in LEO and GEO 185 B.6 Conclusion 193 References 195 Index 201

About the Author :
Joseph Homer Saleh and Jean-François Castet, Georgia Institute of Technology, USA