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.

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.

A Sequential Accelerated Life Testing Framework for System Reliability Assessment With Untestable Components

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Zhen Hu ◽  
Zissimos P. Mourelatos
Keyword(s):  
System Reliability ◽  
Reliability Assessment ◽  
Reliability Evaluation ◽  
Accelerated Life Testing ◽  
System Level ◽  
Life Testing ◽  
Component Level ◽  
Accelerated Life ◽  
Design Cycle ◽  
Framework System

Testing of components at higher-than-nominal stress level provides an effective way of reducing the required testing effort for system reliability assessment. Due to various reasons, not all components are directly testable in practice. The missing information of untestable components poses significant challenges to the accurate evaluation of system reliability. This paper proposes a sequential accelerated life testing (SALT) design framework for system reliability assessment of systems with untestable components. In the proposed framework, system-level tests are employed in conjunction with component-level tests to effectively reduce the uncertainty in the system reliability evaluation. To minimize the number of system-level tests, which are much more expensive than the component-level tests, the accelerated life testing (ALT) design is performed sequentially. In each design cycle, testing resources are allocated to component-level or system-level tests according to the uncertainty analysis from system reliability evaluation. The component-level or system-level testing information obtained from the optimized testing plans is then aggregated to obtain the overall system reliability estimate using Bayesian methods. The aggregation of component-level and system-level testing information allows for an effective uncertainty reduction in the system reliability evaluation. Results of two numerical examples demonstrate the effectiveness of the proposed method.

Sequential Accelerated Life Testing Design for System Reliability Analysis With Untestable Components

2018 ◽  
Author(s):  
Zhen Hu ◽  
Zissimos P. Mourelatos
Keyword(s):  
System Reliability ◽  
Reliability Assessment ◽  
Reliability Evaluation ◽  
Accelerated Life Testing ◽  
System Level ◽  
Life Testing ◽  
Component Level ◽  
Accelerated Life ◽  
Framework System ◽  
Testing Design

Testing of components at higher-than-nominal stress level provides an effective way of reducing the required testing effort for system reliability assessment. Due to various reasons, not all components are directly testable in practice. The missing information of untestable components poses significant challenges to the accurate evaluation of system reliability. This paper proposes a sequential accelerated life testing (SALT) design framework for system reliability assessment of systems with untestable components. In the proposed framework, system-level tests are employed in conjunction with component-level tests to effectively reduce the uncertainty in the system reliability evaluation. To minimize the number of system-level tests which are much more expensive than the component-level tests, the accelerated life testing design is performed sequentially. In each design cycle, testing resources are allocated to component-level or system-level tests according to the uncertainty analysis from system reliability evaluation. The component-level or system-level testing information obtained from the optimized testing plans are then aggregated to obtain the overall system reliability estimate using Bayesian methods. The aggregation of component-level and system-level testing information allows for an effective uncertainty reduction in the system reliability evaluation. Results of two numerical examples demonstrate the effectiveness of the proposed method.

SYSTEM RELIABILITY GROWTH ANALYSIS USING COMPONENT FAILURE DATA

1994 ◽  
Vol 01 (01) ◽  
pp. 71-83 ◽  
Author(s):  
M. XIE ◽  
T.N. GOH
Keyword(s):  
System Reliability ◽  
Growth Analysis ◽  
Simple Approach ◽  
System Level ◽  
Reliability Growth ◽  
System Failure ◽  
Component Level ◽  
Component Failure ◽  
Failure Data ◽  
Growth Estimation

In this paper the problem of system-level reliability growth estimation using component-level failure data is studied. It is suggested that system failure data should be broken down into component, or subsystem, failure data when the above problems have occurred during the system testing phase. The proposed approach is especially useful when the system is not unchanged over the time, when some subsystems are improved more than others, or when the testing has been concentrated on different components at different time. These situations usually happen in practice and it may also be the case even if the system failure data is provided. Two sets of data are used to illustrate the simple approach; one is a set of component failure data for which all subsystems are available for testing at the same time and for the other set of data, the starting times are different for different subsystems.

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.

More on optimal allocation of components in coherent systems

1996 ◽  
Vol 33 (02) ◽  
pp. 548-556 ◽  
Author(s):  
Fan C. Meng
Keyword(s):  
System Reliability ◽  
Binary Systems ◽  
Optimal Allocation ◽  
Reliability Theory ◽  
Parallel System ◽  
System Level ◽  
Coherent Systems ◽  
Component Level ◽  
Multistate Systems ◽  
Permutation Equivalent

More applications of the principle for interchanging components due to Boland et al. (1989) in reliability theory are presented. In the context of active redundancy improvement we show that if two nodes are permutation equivalent then allocating a redundancy component to the weaker position always results in a larger increase in system reliability, which generalizes a previous result due to Boland et al. (1992). In the case of standby redundancy enhancement, we prove that a series (parallel) system is the only system for which standby redundancy at the component level is always more (less) effective than at the system level. Finally, the principle for interchanging components is extended from binary systems to the more complicated multistate systems.

scholarly journals Optimal Robot Motion for Accelerated Life Testing of a 6-DoF Industrial Robot

2020 ◽  
Vol 10 (21) ◽  
pp. 7459
Author(s):  
Seungjin Yoo ◽  
Jin Jang ◽  
Jai-Kyung Lee ◽  
Jong-Won Park
Keyword(s):  
Industrial Robot ◽  
Geometric Mean ◽  
Industrial Robots ◽  
Acceleration Factor ◽  
Accelerated Life Test ◽  
System Level ◽  
Test Time ◽  
Robot Motion ◽  
Life Test ◽  
Accelerated Life

In order to verify the reliability of drive components for industrial robots, component-level life tests must be accompanied by a system-level life test using actual robots in which predefined robot motions are repeated throughout the test. To properly verify the durability of drive components through a system-level life test, it is important to design test modes so that the required test time is the same for all joint drive components of the robot, and it is necessary to design test modes with a high acceleration factor so as to shorten the required test time as much as possible. To solve this problem, the present research proposes a method for designing robot motions that makes the accelerated life test time for all the drive components of the robot equal. In particular, we solve a dynamic based motion optimization problem for an industrial 6-DoF (degrees-of-freedom) robot that minimizes the AM-GM (arithmetic mean to geometric mean) ratio of the acceleration factors of each joint. The results show that C2-continuous test modes with the same acceleration factor, which is inversely proportional to the cycle time of the robot motion, can be derived.

TEST PLAN ALLOCATION TO MINIMIZE SYSTEM RELIABILITY ESTIMATION VARIABILITY

2004 ◽  
Vol 11 (03) ◽  
pp. 257-272 ◽  
Author(s):  
JOSE E. RAMIREZ-MARQUEZ ◽  
DAVID W. COIT ◽  
TONGDAN JIN
Keyword(s):  
System Reliability ◽  
Reliability Estimation ◽  
System Structure ◽  
System Level ◽  
Reliability Estimate ◽  
Component Level ◽  
Component Reliability ◽  
Allocation Process ◽  
Reliability Estimates ◽  
Estimate Variance

A new methodology is presented to allocate testing units to the different components within a system when the system configuration is fixed and there are budgetary constraints limiting the amount of testing. The objective is to allocate additional testing units so that the variance of the system reliability estimate, at the conclusion of testing, will be minimized. Testing at the component-level decreases the variance of the component reliability estimate, which then decreases the system reliability estimate variance. The difficulty is to decide which components to test given the system-level implications of component reliability estimation. The results are enlightening because the components that most directly affect the system reliability estimation variance are often not those components with the highest initial uncertainty. The approach presented here can be applied to any system structure that can be decomposed into a series-parallel or parallel-series system with independent component reliability estimates. It is demonstrated using a series-parallel system as an example. The planned testing is to be allocated and conducted iteratively in distinct sequential testing runs so that the component and system reliability estimates improve as the overall testing progresses. For each run, a nonlinear programming problem must be solved based on the results of all previous runs. The testing allocation process is demonstrated on two examples.

Sign in / Sign up

Export Citation Format

Share Document