scholarly journals Analysis and Application of Mechanical System Reliability Model Based on Copula Function

2016 ◽  
Vol 23 (s1) ◽  
pp. 187-191 ◽  
Author(s):  
Hai An ◽  
Hang Yin ◽  
Fukai He
Keyword(s):  
Mechanical System ◽  
System Reliability ◽  
Reliability Function ◽  
Copula Function ◽  
Reliability Model ◽  
Reliability Modeling ◽  
Modeling And Analysis ◽  
Copula Theory ◽  
Model Based ◽  
Analysis Process

Abstract There is complicated correlations in mechanical system. By using the advantages of copula function to solve the related issues, this paper proposes the mechanical system reliability model based on copula function. And makes a detailed research for the serial and parallel mechanical system model and gets their reliability function respectively. Finally, the application research is carried out for serial mechanical system reliability model to prove its validity by example. Using Copula theory to make mechanical system reliability modeling and its expectation, studying the distribution of the random variables (marginal distribution) of the mechanical product’ life and associated structure of variables separately, can reduce the difficulty of multivariate probabilistic modeling and analysis to make the modeling and analysis process more clearly.

Reliability Modeling and Simulation of Mechanical Equipment Undergoing Maintenance

2010 ◽  
Vol 34-35 ◽  
pp. 1211-1216
Author(s):  
Liang Pei Huang ◽  
Wen Hui Yue ◽  
Zheng Li Gong
Keyword(s):  
Service Life ◽  
Mechanical System ◽  
Density Function ◽  
System Reliability ◽  
Mechanical Systems ◽  
Mechanical Equipment ◽  
Time To Failure ◽  
Reliability Model ◽  
Reliability Modeling ◽  
Maintenance Policies

The mechanical equipment faults result from parts failure in the period of service time, due to reassembly and maintenance, the reliability model for mechanical equipment is broken, so it is necessary to research and estimate the safety reliability of mechanical system. Based on the time-to-failure density function of parts, the mechanical system reliability model is constructed to track the change course of age structure of part population for the mechanical systems that are reassembled and maintained. By means of simulation of the system reliability model, concerned parameters with mechanical systems service life are defined, it is discussed how the time-to-failure density function have influence on the service life for mechanical systems undergoing reassembly and maintenance. It is significant to estimate reliability and failure rate of systems and to establish reasonable maintenance policies.

scholarly journals LED Lighting System Reliability Modeling and Inference via Random Effects Gamma Process and Copula Function

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Huibing Hao ◽  
Chun Su ◽  
Chunping Li
Keyword(s):  
Random Effects ◽  
System Reliability ◽  
Light Emitting Diode ◽  
Copula Function ◽  
Performance Characteristics ◽  
Assessment Model ◽  
Gamma Process ◽  
Unknown Parameters ◽  
Reliability Modeling ◽  
Lighting Systems

Light emitting diode (LED) lamp has attracted increasing interest in the field of lighting systems due to its low energy and long lifetime. For different functions (i.e., illumination and color), it may have two or more performance characteristics. When the multiple performance characteristics are dependent, it creates a challenging problem to accurately analyze the system reliability. In this paper, we assume that the system has two performance characteristics, and each performance characteristic is governed by a random effects Gamma process where the random effects can capture the unit to unit differences. The dependency of performance characteristics is described by a Frank copula function. Via the copula function, the reliability assessment model is proposed. Considering the model is so complicated and analytically intractable, the Markov chain Monte Carlo (MCMC) method is used to estimate the unknown parameters. A numerical example about actual LED lamps data is given to demonstrate the usefulness and validity of the proposed model and method.

scholarly journals Reliability modeling for competing failure systems with instant-shift hard failure threshold

2018 ◽  
Vol 42 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Jingyi Liu ◽  
Yugang Zhang ◽  
Bifeng Song
Keyword(s):  
Sensitivity Analysis ◽  
System Reliability ◽  
Reliability Model ◽  
External Shocks ◽  
Reliability Modeling ◽  
Soft Failure ◽  
Random Shock ◽  
Hard Failure ◽  
Engineering Practices ◽  
Random Shocks

Many researchers have modeled systems under multiple dependent competing failure processes (MDCFP) in recent years. Typically, those failure processes consist of degradation (soft failure) and random shock (hard failure). In previous papers the threshold of hard failure has been a fixed value, which does not reflect engineering practices. Threshold refers to the ability to resist external random shocks, which shifts with time as the system is used. Thus, this paper establishes a model for MDCFP with instant-shift hard threshold. The hard failure threshold changes with time instantaneously, and it is also influenced by external shocks. This paper also presents a system reliability model. The effectiveness of the presented model is demonstrated by a reliability analysis of the micro-engine at Sandia National Laboratories. In addition, a sensitivity analysis is performed for specific parameters.

Reliability Simulation and Prediction of Mechanical Equipment for Maintenance

2010 ◽  
Vol 139-141 ◽  
pp. 1060-1063
Author(s):  
Liang Pei Huang ◽  
Zheng Li Gong ◽  
Wen Hui Yue
Keyword(s):  
Service Life ◽  
Mechanical System ◽  
Density Function ◽  
System Reliability ◽  
Mechanical Systems ◽  
Mechanical Equipment ◽  
Time To Failure ◽  
Reliability Model ◽  
Estimate Reliability ◽  
Maintenance Policies

The mechanical equipment faults result from parts failure in the period of service time, due to reassembly and maintenance, the reliability model for mechanical equipment is broken, so it is necessary to research and estimate the safety reliability of mechanical system. Based on the time-to-failure density function of parts, the mechanical system reliability model is constructed to track the change course of age structure of part population for the mechanical systems that are reassembled and maintained. By means of simulation of the system reliability model, concerned parameters with mechanical systems service life are defined, it is discussed how the time-to-failure density function have influence on the service life for mechanical systems undergoing reassembly and maintenance. It is significant to estimate reliability and failure rate of systems and to establish reasonable maintenance policies.

scholarly journals A New Analytic Method of Cold Standby System Reliability Model with Priority

2018 ◽  
Vol 175 ◽  
pp. 03060
Author(s):  
Di Peng ◽  
Ni Zichun ◽  
Hu Bin
Keyword(s):  
System Reliability ◽  
Reliability Function ◽  
Matrix Analysis ◽  
Reliability Model ◽  
Reliability Indicators ◽  
Reliability Modelling ◽  
Maintenance Time ◽  
Cold Standby ◽  
The Matrix ◽  
Standby System

For different importance of components in equipment system, a cold standby system with two different components is studied when important components enjoy the priority in use and maintenance. Considering the application of exponential distribution, Weibull distribution and other typical distributions in resolving the problems subject to complicated calculation and strict constraints in the past reliability modelling, the highly applicable phase-type (PH) distribution is utilized to describe the life and maintenance time of system components in a unified manner. A system reliability model is built for wider applicability. With the matrix analysis method, expressions are obtained for a number of reliability indicators such as system reliability function, steady-state availability, mean up time and mean down time of system. In the end, examples are presented to verify the correctness and applicability of the model.

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