scholarly journals Maintenance of Filter at The Gas Turbine Compressor Intake and Electric Transformer Connector Based on Operational Reliability

2021 ◽  
Vol 70 (1) ◽  
pp. 22-28
Author(s):  
Josip Ivankić ◽  
Deni Ćetković ◽  
Dario Matika
Keyword(s):  
Numerical Model ◽  
Gas Turbine ◽  
Hazard Function ◽  
Software Tool ◽  
Operational Reliability ◽  
Time To Failure ◽  
Anderson Darling ◽  
Statistical Sample ◽  
Gas Turbine Compressor ◽  
Mean Time

The article analyzes the operational reliability of filter on the gas turbine compressor intake and the operational reliability of electric transformer connector. Empirical data (statistical sample) were collected to determine the failure density function f (t), the hazard function λ (t), and the expected value of mean time to failure MTTF. The numerical model was created in the Minitab 19 software tool. The Anderson-Darling test was used to accept or reject the hypothesis.

scholarly journals Reliability Assessment of a Cement Industry by Application of Weibull Method

2019 ◽  
pp. 1-11
Author(s):  
Onoriode K. Idiapho ◽  
William E. Odinikuku ◽  
Onomine M. Akusu
Keyword(s):  
Failure Rate ◽  
Manufacturing Industry ◽  
Software Tool ◽  
Cement Industry ◽  
Time To Failure ◽  
Distribution Method ◽  
Mean Time To Failure ◽  
The Mean ◽  
Cement Manufacturing ◽  
Mean Time

The financial cost of downtime can be very significant, especially in manufacturing industries. As a result, no business wants to experience downtime. In this study, the reliability of two identical machines code named GDA and GDB used in a cement manufacturing industry was assessed by analysis of failure times data of components in the machines by applying Weibull distribution method. The estimates of the Weibull parameters, θ and β were obtained using a reliability software tool ‘Windchill Quality Solutions 11.0 Tryout’ and the mean time to failure, failure rate and reliability of the machines was successfully determined. The result obtained showed that, the machines are undergoing rapid wear out as the values of the shape parameter obtained were greater than four. The plots of the failure rate also showed that the machines are in their wear out periods as the failure rate curves were observed to be increasing. The values of the mean time to failure of the two machines were found to be very close. The reliability of the machines was found to be increasing as their values of scale parameter, θ increases with machine GDA having the highest reliability.

scholarly journals Optimization of Gas Turbine Maintenance Scheduling in PLN Tanjung Datuk Pekanbaru

2020 ◽  
Vol 64 (3) ◽  
pp. 88-93
Author(s):  
Bambang Nofri ◽  
◽  
Anita Susilawati ◽  
Romy Romy ◽  
◽  
...  
Keyword(s):  
Gas Turbine ◽  
Turbine Blade ◽  
Maintenance Scheduling ◽  
Optimal Scheduling ◽  
Turbine Engines ◽  
Optimal Time ◽  
Time To Failure ◽  
Optimal Maintenance ◽  
Critical Components ◽  
Mean Time

This study discusses determining the optimal scheduling for maintenance of gas turbine engines in PLN Tanjung Datuk Pekanbaru. The optimal maintenance scheduling is done on critical components, namely turbine blade and AVR (Automatic Voltage Regulator) using Monte Carlo simulation. The optimal scheduling maintenance scenario is done by generating random numbers from MTTF (Mean Time To Failure) and MTTR (Mean Time To Repair) values and data validity testing. The results of research for optimal checking of turbine engines are once every 10 days with the reliability of turbine engines 43%. The optimal time for repairing a gas turbine in case of damage is 1.49 hours. The checking time for critical components of the turbine blade is 9 days and AVR of 12 days. The scenario of preventive maintenance is likely need special repair or replacement periodically that is 117 days for turbine blade components and 173 days for AVR.

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

Electronics ◽  
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.

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

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.

Aerodynamic limits of gas turbine compressor during high air offtakes for minimum load extension

2021 ◽  
Vol 189 ◽  
pp. 116697
Author(s):  
Artur Szymanski ◽  
Uyioghosa Igie ◽  
Kamal Abudu ◽  
Richard Hamilton
Keyword(s):  
Gas Turbine ◽  
Gas Turbine Compressor

Influence of Non-Equilibrium Fluid Properties During Fogging on Intake Duct and Compressor Characteristics

2017 ◽  
Author(s):  
Christoph Günther ◽  
Franz Joos
Keyword(s):  
Relative Humidity ◽  
Gas Turbine ◽  
Thermophysical Properties ◽  
Ambient Air ◽  
Compressor Stage ◽  
Compression Process ◽  
Fluid Properties ◽  
Temperature And Pressure ◽  
Gas Turbine Compressor ◽  
Non Equilibrium

This study reports on numerically calculated thermophysical properties of air passing through a gas turbine compressor after passage through an intake duct affected by wet compression. Case of reference is unaffected ambient air (referenced to as dry scenario) passing through intake duct and compressor. Furthermore, ambient air cooled down by (overspray) fogging (referenced to as wet scenarios) was considered. Acceleration at the end of intake duct causing reduction of static temperature and pressure results in supersaturated fluid properties at inlet to gas turbine compressor. These supersaturated fluid properties are non-equilibrium with saturation level above relative humidity of φ = 1. Entrance of supersaturated fluid into gas turbine compressor can result in condensation within first compressor stage. At the same time delayed impact of evaporative cooling influences compression process.

Contribution to Rolling Bearing Reliability Modeling

2011 ◽  
Vol 110-116 ◽  
pp. 2497-2503 ◽  
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.

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

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.

Derivation of signatures for faults in gas turbine compressor blading

1998 ◽  
Vol 6 (8) ◽  
pp. 969-974 ◽  
Author(s):  
N. Aretakis ◽  
K. Mathioudakis ◽  
V. Dedoussis
Keyword(s):  
Gas Turbine ◽  
Gas Turbine Compressor

A Bayesian Estimation of Reliability Measures of Stepwise Exponential Distribution System

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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