Performance Analysis of Photovoltaic Systems Using (RAMD) Analysis

Journal of the Nigerian Society of Physical Sciences ◽

10.46481/jnsps.2021.194 ◽

2021 ◽

Author(s):

Anas Sani Maihulla ◽

Ibrahim Yusuf

Keyword(s):

Photovoltaic System ◽

Death Process ◽

Photovoltaic Systems ◽

Time To Failure ◽

Transition Diagram ◽

Highly Sensitive ◽

Random Failure ◽

Repair Facility ◽

Time Variables ◽

Mean Time

The primary aim of this present study is to examine how reliability, availability, maintainability, and dependability (RAMD) are used to describe the criticality of each sub-assembly in grid- connected photovoltaic systems. A transition diagram of all subsystems is produced for this analysis, and Chapman-Kolmogorov differential equations for each variable of each subsystem are constructed using the Markov birth-death process. Both random failure and repair time variables have an exponential distribution and are statistically independent. A sufficient repair facility is still available with the device. The numerical results for reliability, maintainability, dependability, and steady-state availability for various photovoltaic device components have been obtained. Other metrics, such as mean time to failure (MTTF), mean time to repair (MTTR), and dependability ratio, which aid in device performance prediction, have also been measured. According to numerical analysis. it is hypothesized that subsystem S4, i.e. the inverter, is the most critical and highly sensitive portion that requires special attention in order to improve the efficiency of the PV device plant. The findings of this research are very useful for photovoltaic system designers and maintenance engineers.

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Reliability Prediction of Computing Network with Software and Hardware Failures

International Journal of Reliability Quality and Safety Engineering ◽

10.1142/s0218539320400069 ◽

2019 ◽

Vol 27 (02) ◽

pp. 2040006

Author(s):

Chandra Shekhar ◽

Neeraj Kumar ◽

Madhu Jain ◽

Amit Gupta

Keyword(s):

Fault Tolerant ◽

Transient State ◽

Reliability Prediction ◽

Time To Failure ◽

Failure Times ◽

Machine Interference ◽

Random Failure ◽

Software And Hardware ◽

Hardware Failures ◽

Mean Time

In this paper, we investigate the reliability and queueing performance indices for the fault-tolerant computing network having a finite number of unreliable operating components with the provision of warm standby components. Operating and standby components are governed by dedicated software which is also prone to random failure. On failure of operating components, available standby component(s) may switch from the standby state to operating state with negligible switchover time. The switchover process may also fail due to some automation hindrance. The computing network is also subjected to common cause failure in lieu of external cause. The studied redundant fault-tolerant computing network is framed as a Markovian machine interference model with exponentially distributed inter-failure times and service times. For the reliability prediction of the computing network, various performance measures, namely, mean-time-to-failure (MTTF), reliability/availability, failure frequency, etc., have been formulated in terms of transient-state probabilities which we have obtained using the spectral method. To show the practicability of the developed model, numerical simulation has been done. Sensitivity analysis of reliability and other indices of the computing network with respect to different network parameters has been presented, and results are summarized in the tables and graphs. Finally, future scope and concluding remarks have been included.

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Performance and Cost Assessment of a Small Solar Photovoltaic System Using Gumbel-Haugaard Family Copula Analysis

10.21203/rs.3.rs-939621/v1 ◽

2021 ◽

Author(s):

Anas Maihulla ◽

Ibrahim Yusuf ◽

Saminu Bala

Keyword(s):

Sensitivity Analysis ◽

Photovoltaic System ◽

Cost Assessment ◽

Time To Failure ◽

Solar Photovoltaic ◽

Schematic Diagram ◽

System Availability ◽

Solar Photovoltaic System ◽

Mean Time ◽

Availability Model

Abstract The main objective of the present study is to analyze the availability of solar photovoltaic system. The solar photovoltaic system in this paper is simple one consisting of four subsystems namely, solar panel subsystem, charge controller subsystem, batteries subsystem and inverter subsystem. Through the schematic diagram of state of the system, availability model is formulated and Chapmen - Kolmogorov differential equations are developed and solved using Gumbel Haugaard family Copula technique. The numerical values for availability, reliability, mean time to failure (MTTF), cost analysis as well as sensitivity analysis are presented. The effects of failure rates to various solar photovoltaic subsystems were developed.

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Performance improvement of a crystallization system through optimization and sensitivity analysis

International Journal of Quality & Reliability Management ◽

10.1108/ijqrm-06-2020-0184 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Anil Kr. Aggarwal

Keyword(s):

Sensitivity Analysis ◽

Performance Optimization ◽

Initial Boundary ◽

Time To Failure ◽

Transition Diagram ◽

Content Type ◽

Crystallization System ◽

Sugar Plant ◽

Maintenance Personnel ◽

Mean Time

PurposeThis paper deals with the performance optimization and sensitivity analysis for crystallization system of a sugar plant.Design/methodology/approachCrystallization system comprises of five subsystems, namely crystallizer, centrifugal pump and sugar grader. The Chapman–Kolmogorov differential equations are derived from the transition diagram of the crystallization system using mnemonic rule. These equations are solved to compute reliability and steady state availability by putting the appropriate combinations of failure and repair rates using normalizing and initial boundary conditions. The performance optimization is carried out by varying number of generations, population size, crossover and mutation probabilities. Finally, sensitivity analysis is performed to analyze the effect of change in failure rates of each subsystem on availability, mean time to failure (MTBF) and mean time to repair (MTTR).FindingsThe highest performance observed is 96.95% at crossover probability of 0.3 and sugar grader subsystem comes out to be the most critical and sensitive subsystem.Originality/valueThe findings of the paper highlights the optimum value of performance level at failure and repair rates for subsystems and also helps identify the most sensitive subsystem. These findings are highly beneficial for the maintenance personnel of the plant to plan the maintenance strategies accordingly.

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Surveillance System in Smart Cities: A Dependability Evaluation Based on Stochastic Models

Electronics ◽

10.3390/electronics10080876 ◽

2021 ◽

Vol 10 (8) ◽

pp. 876

Author(s):

Igor Gonçalves ◽

Laécio Rodrigues ◽

Francisco Airton Silva ◽

Tuan Anh Nguyen ◽

Dugki Min ◽

...

Keyword(s):

Surveillance System ◽

Smart Cities ◽

Heterogeneous Data ◽

Time To Failure ◽

Video Streams ◽

Dependability Evaluation ◽

The Mean ◽

Mean Time ◽

The Internet Of Things

Surveillance monitoring systems are highly necessary, aiming to prevent many social problems in smart cities. The internet of things (IoT) nowadays offers a variety of technologies to capture and process massive and heterogeneous data. Due to the fact that (i) advanced analyses of video streams are performed on powerful recording devices; while (ii) surveillance monitoring services require high availability levels in the way that the service must remain connected, for example, to a connection network that offers higher speed than conventional connections; and that (iii) the trust-worthy dependability of a surveillance system depends on various factors, it is not easy to identify which components/devices in a system architecture have the most impact on the dependability for a specific surveillance system in smart cities. In this paper, we developed stochastic Petri net models for a surveillance monitoring system with regard to varying several parameters to obtain the highest dependability. Two main metrics of interest in the dependability of a surveillance system including reliability and availability were analyzed in a comprehensive manner. The analysis results show that the variation in the number of long-term evolution (LTE)-based stations contributes to a number of nines (#9s) increase in availability. The obtained results show that the variation of the mean time to failure (MTTF) of surveillance cameras exposes a high impact on the reliability of the system. The findings of this work have the potential of assisting system architects in planning more optimized systems in this field based on the proposed models.

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On classes of life distributions based on the mean time to failure function

Journal of Applied Probability ◽

10.1017/jpr.2020.91 ◽

2021 ◽

Vol 58 (2) ◽

pp. 289-313

Author(s):

Ruhul Ali Khan ◽

Dhrubasish Bhattacharyya ◽

Murari Mitra

Keyword(s):

Damage Model ◽

Replacement Policy ◽

Time To Failure ◽

Mean Time To Failure ◽

Moment Convergence ◽

Life Distributions ◽

Cumulative Damage Model ◽

The Mean ◽

Age Replacement ◽

Mean Time

AbstractThe performance and effectiveness of an age replacement policy can be assessed by its mean time to failure (MTTF) function. We develop shock model theory in different scenarios for classes of life distributions based on the MTTF function where the probabilities $\bar{P}_k$ of surviving the first k shocks are assumed to have discrete DMTTF, IMTTF and IDMTTF properties. The cumulative damage model of A-Hameed and Proschan [1] is studied in this context and analogous results are established. Weak convergence and moment convergence issues within the IDMTTF class of life distributions are explored. The preservation of the IDMTTF property under some basic reliability operations is also investigated. Finally we show that the intersection of IDMRL and IDMTTF classes contains the BFR family and establish results outlining the positions of various non-monotonic ageing classes in the hierarchy.

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Contribution to Rolling Bearing Reliability Modeling

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.110-116.2497 ◽

2011 ◽

Vol 110-116 ◽

pp. 2497-2503 ◽

Cited By ~ 1

Author(s):

Zdenek Vintr ◽

Michal Vintr

Keyword(s):

Operating Time ◽

Rolling Bearing ◽

Time To Failure ◽

Rolling Bearings ◽

Mean Time To Failure ◽

Reliability Modeling ◽

Time Between Failures ◽

Large Groups ◽

Mean Time

Rolling bearings are usually considered to be non-repaired items the reliability of which is characterized by mean time to failure, or so called basic rating life. Reliability describes these parameters well in case the bearings are used in operation up to the very time the failure occurs, or during the time corresponding with basic rating life. In case of railway applications the bearings are often used in large groups and are preventively replaced after much shorter operating time as compared with their basic rating life. In the article there is a model which enables us to describe the bearings reliability in this specific case and to specify a number of failures which might be expected from a group of bearings during operating time, or to determine mean operating time between failures of bearings.

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Filling machine preventive maintenance using age replacement method in PT Lucas Djaja

MATEC Web of Conferences ◽

10.1051/matecconf/201815401056 ◽

2018 ◽

Vol 154 ◽

pp. 01056

Author(s):

Fifi Herni Mustofa ◽

Ria Ferdian Utomo ◽

Kusmaningrum Soemadi

Keyword(s):

Maintenance Cost ◽

Time To Failure ◽

High Failure Rate ◽

Corrective Maintenance ◽

Replacement Method ◽

Critical Components ◽

Age Replacement ◽

Engine Maintenance ◽

A Company ◽

Mean Time

PT Lucas Djaja is a company engaged in the pharmaceutical industry which produce sterile drugs and non-sterile. Filling machine has a high failure rate and expensive corrective maintenance cost. PT Lucas Djaja has a policy to perform engine maintenance by way of corrective maintenance. The study focused on the critical components, namely bearing R2, bearing 625 and bearing 626. When the replacement of the failure done by the company is currently using the formula mean time to failure with the result of bearing R2 at point 165 days, bearing 625 at a point 205 days, and bearing 626 at a point 182 days. Solutions generated by using age replacement method with minimization of total maintenance cost given on the bearing R2 at a point 60 days, bearing 625 at the point of 80 days and bearing 626 at a point 40 days.

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A Bayesian Estimation of Reliability Measures of Stepwise Exponential Distribution System

9th Biennial Conference on Reliability, Stress Analysis, and Failure Prevention ◽

10.1115/detc1991-0005 ◽

1991 ◽

Author(s):

M. H. Hu

Keyword(s):

Bayesian Estimation ◽

Exponential Distribution ◽

Distribution System ◽

Failure Process ◽

Reliability Function ◽

Distribution Model ◽

Time To Failure ◽

Reliability Measures ◽

In Series ◽

Mean Time

Abstract This paper presents an analysis method for reliability measures of a system with step changes in failure and repair rates. Both failure and repair time have exponential function of time. Such a system is called a stepwise exponential distribution system. This kind of failure process can take place in various equipments. This paper deals with the system having components in series arrangement. Bayesian statistics is used in defining prior and posterior probability density functions of failure and repair rates. These functions provide information for the estimation of reliability measures: 1) failure and repair rates, 2) mean time to failure, 3) mean time to repair, 4) reliability function and 5) availability. A sample problem is given to illustrate the methodology. The Bayesian estimation of the stepwise exponential distribution model is useful in the planning of equipment predictive maintenance.

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