scholarly journals Reliability Assessment of Space Station Based on Multi-Layer and Multi-Type Risks

2021 ◽  
Vol 11 (21) ◽  
pp. 10258
Author(s):  
Xiaopeng Li ◽  
Fuqiu Li
Keyword(s):  
System Reliability ◽  
Early Stage ◽  
Space Station ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Assessment Process ◽  
Reliability Model ◽  
Using Data ◽  
Propagation Feature ◽  
Sufficient Test

A space station is a typical phased-mission system, and assessing its reliability during its configuration is an important engineering action. Traditional methods usually require extensive data to carry out a layered reliability assessment from components to the system. These methods suffer from lack of sufficient test data, and the assessment process becomes very difficult, especially in the early stage of the configuration. This paper proposes a reliability assessment method for the space station configuration mission, using multi-layer and multi-type risks. Firstly, the risk layer and the risk type for the space station configuration are defined and identified. Then, the key configuration risks are identified comprehensively, considering their occurrence likelihood and consequence severity. High load risks are identified through risk propagation feature analysis. Finally, the configuration reliability model is built and the state probabilities are computed, based on the probabilistic risk propagation assessment (PRPA) method using the assessment probability data. Two issues are addressed in this paper: (1) how to build the configuration reliability model with three layers and four types of risks in the early stage of the configuration; (2) how to quantitatively assess the configuration mission reliability using data from the existing operational database and data describing the propagation features. The proposed method could be a useful tool for the complex aerospace system reliability assessment in the early stage.

Green system reliability assessment method based on life cycle: Resources and economical view

2020 ◽  
Vol 251 ◽  
pp. 119786
Author(s):  
Jun-Gang Zhou ◽  
Ling-Ling Li ◽  
Ming-Lang Tseng ◽  
Guo-Qian Lin
Keyword(s):  
Life Cycle ◽  
System Reliability ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Green System

RELIABILITY MODEL FOR COMPONENT-BASED SYSTEMS IN COSMIC (A CASE STUDY)

2008 ◽  
Vol 18 (04) ◽  
pp. 515-539 ◽  
Author(s):  
OLGA ORMANDJIEVA ◽  
MANAR ABU TALIB ◽  
ALAIN ABRAN
Keyword(s):  
System Reliability ◽  
Reliability Assessment ◽  
Software Component ◽  
Assessment Model ◽  
Assessment Process ◽  
Component Technology ◽  
Substantial Impact ◽  
Effort Reduction ◽  
Typical Component

Software component technology has a substantial impact on modern IT evolution. The benefits of this technology, such as reusability, complexity management, time and effort reduction, and increased productivity, have been key drivers of its adoption by industry. One of the main issues in building component-based systems is the reliability of the composed functionality of the assembled components. This paper proposes a reliability assessment model based on the architectural configuration of a component-based system and the reliability of the individual components, which is usage- or testing-independent. The goal of this research is to improve the reliability assessment process for large software component-based systems over time, and to compare alternative component-based system design solutions prior to implementation. The novelty of the proposed reliability assessment model lies in the evaluation of the component reliability from its behavior specifications, and of the system reliability from its topology; the reliability assessment is performed in the context of the implementation-independent ISO/IEC 19761:2003 International Standard on the COSMIC method chosen to provide the component's behavior specifications. In essence, each component of the system is modeled by a discrete time Markov chain behavior based on its behavior specifications with extended-state machines. Then, a probabilistic analysis by means of Markov chains is performed to analyze any uncertainty in the component's behavior. Our hypothesis states that the less uncertainty there is in the component's behavior, the greater the reliability of the component. The system reliability assessment is derived from a typical component-based system architecture with composite reliability structures, which may include the composition of the serial reliability structures, the parallel reliability structures and the p-out-of-n reliability structures. The approach of assessing component-based system reliability in the COSMIC context is illustrated with the railroad crossing case study.

Resource Allocation for System Reliability Assessment Using Accelerated Life Testing

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Kassem Moustafa ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
Igor Baseski ◽  
Monica Majcher
Keyword(s):  
Resource Allocation ◽  
System Reliability ◽  
Failure Time ◽  
Reliability Assessment ◽  
Accelerated Life Test ◽  
Assessment Process ◽  
System Level ◽  
Component Level ◽  
Accelerated Life ◽  
Failure Time Distributions

Abstract Accelerated life test (ALT) has been widely used to accelerate the product reliability assessment process by testing a product at higher than nominal stress conditions. For a system with multiple components, the tests can be performed at component-level or system-level. The data at these two levels require different amount of resources to collect and carry different values of information for system reliability assessment. Even though component-level tests are cheap to perform, they cannot account for the correlations between the failure time distributions of different components. While system-level tests can naturally account for the complicated dependence between component failure time distributions, the required testing efforts are much higher than that of component-level tests. This research proposes a novel resource allocation framework for ALT-based system reliability assessment. A physics-informed load model is first employed to bridge the gap between component-level tests and system-level tests. An optimization framework is then developed to effectively allocate testing resources to different types of tests. The information fusion of component-level and system-level tests allows us to accurately estimate the system reliability with a minimized requirement on the testing resources. Results of two numerical examples demonstrate the effectiveness of the proposed framework.

scholarly journals Competitive failure analysis of a stochastic degradation system based on performance characteristics fusion

2021 ◽  
Vol 39 (2) ◽  
pp. 439-447
Author(s):  
Qinglai Dong ◽  
Weiwei Wang ◽  
Shubin Si
Keyword(s):  
System Reliability ◽  
Failure Modes ◽  
Reliability Assessment ◽  
Degradation Process ◽  
Assessment Method ◽  
Performance Characteristics ◽  
Reliability Modeling ◽  
Numerical Examples ◽  
Degradation Models ◽  
Bivariate Wiener Process

With the aim of solving the reliability modeling and calculation of multivariate stochastic degradation systems, two stochastic degradation models based on the bivariate Wiener process are proposed, in which two performance characteristics are composited to one variable. Two different failure modes including the defect-based failure and the duration-based failure are considered. The explicit expressions of the system reliability are derived in the cases that the performance characteristics are not composited or the performance characteristics are composited according to the linear combination of the degradation measurements. An algorithm based on the Monte Carlo simulation is proposed to simulate the degradation process, in which the performance characteristics are composited in arbitrary forms, and the correctness of the analytical results is also verified. Finally, some numerical examples are presented to illustrate the present reliability assessment method。

Resource Allocation for System Reliability Analysis Using Accelerated Life Testing

2019 ◽  
Author(s):  
Kassem Moustafa ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
Igor Baseski ◽  
Monica Majcher
Keyword(s):  
Resource Allocation ◽  
System Reliability ◽  
Failure Time ◽  
Reliability Assessment ◽  
Accelerated Life Test ◽  
Assessment Process ◽  
System Level ◽  
Component Level ◽  
Accelerated Life ◽  
Failure Time Distributions

Abstract Accelerated life test (ALT) has been widely used to accelerate the product reliability assessment process by testing product at higher than nominal stress conditions. For a system with multiple components, the tests can be performed at component-level or system-level. The data at these two levels require different amount of resources to collect and carry different values of information for system reliability assessment. Even though component-level tests are cheap to perform, they cannot account for the correlations between the failure time distributions of different components. While system-level tests can naturally account for the complicated dependence between component failure time distributions, the required testing efforts are much higher than that of component-level tests. This research proposes a novel resource allocation framework for ALT-based system reliability assessment. A physics-informed load model is first employed to bridge the gap between component-level tests and system-level tests. An optimization framework is then developed to effectively allocate testing resources to different types of tests. The information fusion of component-level and system-level tests allows us to accurately estimate the system reliability with a minimized requirement on the testing resources. Results of one numerical example demonstrate the effectiveness of the proposed framework.

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