Maintenance policy optimization for a cold standby system considering multiple failure types

2019 ◽  
Vol 25 (2) ◽  
pp. 182-198
Author(s):  
Faqun Qi ◽  
Binghai Zhou
Keyword(s):  
Sensitivity Analysis ◽  
System Reliability ◽  
Transition Probabilities ◽  
Maintenance Policy ◽  
Repair Shop ◽  
Content Type ◽  
Modeling Methods ◽  
Cold Standby ◽  
Random Failure ◽  
Standby System

Purpose The purpose of this paper is to develop novel preventive maintenance (PM) modeling methods for a cold standby system subject to two types of failures: random failure and deterioration failure. Design/methodology/approach The system consists of two components and a single repair shop, assuming that the repair shop can only service for one component at a time. Based on semi-Markov theory, transition probabilities between all possible system states are discussed. With the transition probabilities, Markov renewal equations are established at regenerative points. By solving the Markov regenerative equations, the mean time from the initial state to system failure (MTSF) and the steady state availability (SSA) are formulated as two reliability measures for different reliability requirements of systems. The optimal PM policies are obtained when MTSF and SSA are maximized. Findings The result of simulation experiments verifies that the derived maintenance models are effective. Sensitivity analysis revealed the significant influencing factors for optimal PM policy for cold standby systems when different system reliability indexes (i.e. MTSF and SSA) are considered. Furthermore, the results show that the repair for random failure has a tremendous impact on prolonging the MTSF of cold standby system and PM plays a greater role in promoting the system availability of a cold standby system than it does in prolonging the MTSF of system. Practical implications In practical situations, system not only suffers normal deterioration caused by internal factors, but also undergoes random failures influenced by random shocks. Therefore, multiple failure types are needed to be considered in maintenance modeling. The result of the sensitivity analysis has an instructional role in making maintenance decisions by different system reliability indexes (i.e. MTSF and SSA). Originality/value This paper presents novel PM modeling methods for a cold standby system subject to two types of failures: random failure and deterioration failure. The sensitivity analysis identifies the significant influencing factors for optimal maintenance policy by different system reliability indexes which are useful for the managers for further decision making.

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.

System reliability computation and estimation based on a cumulative damage–threshold–shock model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siju K.C. Siju K.C. ◽  
Mahesh Kumar
Keyword(s):  
Sensitivity Analysis ◽  
Maximum Likelihood ◽  
System Reliability ◽  
Damage Threshold ◽  
Likelihood Estimation ◽  
Threshold Level ◽  
Cumulative Damage ◽  
Maximum Likelihood Estimates ◽  
Shock Model ◽  
Content Type

PurposeThis article considers a reliability model where the failure is due to cumulative damage exceeding a threshold level. The concept that the threshold level of cumulative damage at each arrival of shock can change based on whether the magnitude of each shock exceeds its defined threshold level is considered to compute the system reliability.Design/methodology/approachThe stochastic process approach is used to obtain the cumulative damage based on Poisson arrival of shocks. The general expression for reliability is obtained using the conditional probability over each arrival of shock. The method of maximum likelihood estimation is used to obtain the estimators of the parameters and system reliability. A sensitivity analysis is performed to measure the effect of the parameter representing the rate of arrival of shock.FindingsThe maximum likelihood estimates of the reliability approach the actual reliability for increasing sample size. A sensitivity analysis study on the parameter representing the rate of arrival of shock shows that as the values of parameter increase (decrease), the reliability value decreases (increases).Originality/valueObtained a new expression for the cumulative damage–shock model and the findings are positively supported by presenting the general trend of estimated values of reliability approaching the actual value of reliability. The sensitivity analysis also genuinely supports our findings.

scholarly journals Contribution to ECDIS Reliability using Markov Model

2014 ◽  
Vol 3 (2) ◽  
pp. 149-157 ◽  
Author(s):  
Dean Sumić ◽  
Dragan Peraković ◽  
Marinko Jurčević
Keyword(s):  
Information System ◽  
Markov Model ◽  
Simulation Model ◽  
System Reliability ◽  
Design Concept ◽  
Cold Standby ◽  
Electronic Chart ◽  
Standby System ◽  
Reliability And Availability ◽  
Bridge System

An Integrated Bridge System (IBS) contains a fully duplicated Electronic Chart Display and Information System (ECDIS). Although duplication should increase system reliability, reliability and availability are not improved. Proper ECDIS maintenance includes updating both: the information system and the provided chart system. This procedure, in practice, tends to decrease reliability and availability. A Markov ECDIS simulation model is given. A new design concept is presented and proposed. The entire ECDIS system is improved by adding a cold standby system preventing the occurrence of errors due to updating and upgrading of the system device.

Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Reza Pourhassan ◽  
Sadigh Raissi ◽  
Arash Apornak
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Performance ◽  
Failure Process ◽  
State System ◽  
Failure Behavior ◽  
Simulation Approach ◽  
Critical System ◽  
Content Type ◽  
System Reliability Analysis

PurposeIn some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.Design/methodology/approachIn some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.FindingsThis study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.Originality/valueThe results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

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