How can you assess the reliability of new spacecraft materials?

2 Reliability assessment

Reliability assessment is the process of estimating and verifying the reliability of a system or component based on available data and information. Reliability assessment can be performed at different stages of the system life cycle, such as concept, design, development, testing, operation, and disposal. Reliability assessment can use various methods and techniques, such as reliability models, failure modes and effects analysis (FMEA), fault tree analysis (FTA), reliability testing, reliability growth analysis, and reliability prediction.

3 Reliability models

Reliability models are mathematical representations of the failure behavior and characteristics of a system or component. Reliability models can be used to estimate the reliability parameters, such as failure rate, mean time to failure (MTTF), mean time between failures (MTBF), and availability. Reliability models can be classified into two types: empirical and analytical. Empirical models are based on statistical analysis of historical or experimental data, such as the Weibull distribution or the exponential distribution. Analytical models are based on physical or logical assumptions about the failure mechanisms and interactions, such as the series-parallel model or the Markov model.

5 Reliability testing

Reliability testing is the process of subjecting a system or component to various conditions and stimuli to observe and measure its failure behavior and performance. Reliability testing can be performed at different levels of complexity and realism, such as component testing, subsystem testing, system testing, and mission testing. Reliability testing can be classified into two types: destructive and non-destructive. Destructive testing is designed to induce failures and evaluate the failure modes and effects, such as accelerated life testing or stress testing. Non-destructive testing is designed to monitor and detect the degradation and anomalies without causing failures, such as health monitoring or inspection.

6 Reliability growth analysis and prediction

Reliability growth analysis and prediction are the processes of tracking and forecasting the reliability improvement of a system or component over time. Reliability growth analysis is based on the collection and analysis of failure data from reliability testing or operation, and the identification and correction of failure causes. Reliability growth analysis can use various models and methods, such as the Duane model, the Crow-AMSAA model, or the Bayesian approach. Reliability prediction is based on the extrapolation and projection of the reliability growth trend and the estimation of the reliability parameters at a future point or interval, such as the end of development, the beginning of operation, or the end of life.