Journal articles: 'Mean time between failure'

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O.C.Onuigbo, and R.O. Edokpia. "Availability Assessment of Three 11kv Feeders Benin City, Edo State, Nigeria." Journal of Energy Technology and Environment 5, no. 2 (2023): 32–39. https://doi.org/10.5281/zenodo.8018218.

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Nigeria’s power supply has been experiencing incessant interruptions due to failures in the distribution system. The availability assessment of power system is a necessary criterion in meeting the customer’s demand. In this study, the availability of three 11kv feeder in Benin Electricity Distribution Company (BEDC), Edo State Nigeria were evaluated. These was carried out by collating the failure data which includes; time of failure, time outage was restored, outage duration, causes of failure, and load interruption from the Injection substations G.R.A Injection substations for the years, 2020 and 2021 using Monthly and Yearly data.  Mean time between failure (MTBF), Mean time to repair (MTTR), failure rate, repair rate, availability evaluated for the analysis. The results of the analysis reveals that there was a decrease for MTBF for the feeders (which implies decline in Performance). The year 2021 had the accumulated higher MTTR than 2020 as a result of decline in response to faults except for Ihama Feeder. After the computations, the year 2020 had a better availability than the year2021

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Alfionita, Silvana, and Fakhri Ikhwanul Alifin. "Preventive Maintenance Analysis Based on Mean Time Between Failure (MTBF) and Mean Time to Repair (MTTR)." Angkasa: Jurnal Ilmiah Bidang Teknologi 15, no. 2 (2023): 201. http://dx.doi.org/10.28989/angkasa.v15i2.1833.

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A company's ability to meet its goals depends heavily on the smooth operation of its production process. To ensure that the production machinery operates smoothly and without any breakdowns, it is essential to implement effective maintenance that addresses any issues related to the equipment. This research aims to identify the root causes of equipment failure in the soda and dolomite bucket elevator by analyzing the Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR), and conducting a qualitative evaluation using Failure Mode Effects Analysis (FMEA). The analysis reveals that the company performs preventive maintenance every 3 days, which is more frequent than the optimal schedule of once every 33 days. This suggests that the company may be addressing unforeseen failures. The FMEA analysis indicates that the highest Risk Priority Number is associated with suboptimal maintenance of the Staff. To address this issue, the company can use Radio-Frequency Identification (RFID) technology.

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Suleiman, K., and U.A. Ali. "Reliability Analysis of Distribution Transformer A Case Study of Gwiwa Business Unit, Sokoto." Greener Journal of Science, Engineering and Technological Research 3, no. 3 (2013): 88–92. https://doi.org/10.15580/gjsetr.2013.3.112212288.

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In this paper, the reliability of 11/0.415KV town feeder transformers comprising four sub-feeders (Town, GRA, Water Works and industrial) located at Gwiwa Business Unit, Sokoto were studied. The cost implications of failed transformers were also studied, using the data collected from Central Bank of Nigeria (CBN, 2009). It was found that the total amount lost was N37,997,732.40, N16,522,245.88, N20,934,463.70 and N25,559,391.64 for Town, GRA, Water Works and Industrial respectively, over the four years.  It is revealed that the approximate time any transformer under Town, GRA, Water Works and industrial feeder may be expected to function before fault or failure (Mean Time Between Failures, MTBF) is 9 months, 39 months, 20 months and 14 months respectively. It was also found that reliability of Town feeder is 52%, GRA79%, Water works 62% and Industrial feeder 50%. It was deduced that town and GRA are under semi-reliable conditions because they are subjected to load beyond their identified plate capacity. 

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Elijah, P.T., and M. Obaseki. "Application of Linear Regression Maintenance Models on Rotodynamic Systems." Nigerian Research Journal of Engineering and Environmental Sciences 6, no. 2 (2021): 695–705. https://doi.org/10.5281/zenodo.5805259.

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This paper presents a maintenance model as well as its analysis for minimizing unexpected breakdowns, decrease in productivity and high maintenance cost, associated with rotodynamic systems failures. This work presented a case study of a gas compressing systems and integrates linear regression models derived from Weibull’s exponential distribution in determining the frequency of failure and the mean time between failures (MTBF) of the gas compressing systems. Results obtained showed that the gas compressing system’s frequency of failure and the mean time between failures were 0.00052% and 4.12 years respectively. The result presented established the comparison of the proposed maintenance model with the existing one at the case study to indicate a significant improvement.

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HANSSON, ANDERS. "Control of mean time between failures." International Journal of Control 59, no. 6 (1994): 1485–504. http://dx.doi.org/10.1080/00207179408923142.

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Dai, Yi, Xue Zhi Yang, and Ning Ji. "Distribution of Time Between Failures of Numerical Control System Based on Censored Data." Advanced Materials Research 544 (June 2012): 55–60. http://dx.doi.org/10.4028/www.scientific.net/amr.544.55.

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The calculation of mean time between failures (MTBF) is of significance in reliability engineering. The precondition before calculation of MTBF is to make sure what failure model the numerical control (NC) system follows. For different distributions, the corresponding calculation methods of MTBF are always different. Undertaken a 2 year period of timing censored test with replacement of NC lathe, authors apply a type I censored likelihood function to make the distribution fitting of time between failures of NC system. The tests of goodness-of-fit applying Hollander’s method demonstrate that the time between failures of NC system follows the Weibull distribution. The conclusion not only deeply analyzes the NC system failure law, but also establishes the basis of calculation for the mean time between failures of NC system based on censored data with replacement.

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Duer, Stanisław, Marek Woźniak, Jacek Paś, et al. "Reliability Testing of Wind Farm Devices Based on the Mean Time to Failures." Energies 16, no. 6 (2023): 2827. http://dx.doi.org/10.3390/en16062827.

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Nowadays, one of the main sources of renewable energy is wind energy; therefore, a wind farm’s electricity system must be effective. As a result, wind farm (WF) equipment must continuously operate without failure or damage. To achieve this, it is necessary to regularly monitor and assess the reliability of WF systems at every point of their “life”, including design, implementation, and continued use. Three key goals are presented in the article. First, a theory of fundamental theoretical quantities that can be used in reliability and maintenance analysis is presented. The second is to put forth a theoretical reliability link between mean time to failure and WF system fitness probability (Mean Time to Failures (MTTF—Mean time between failures. MTTF = t1 + t2 + … + tn/m, where: m—the number of all failures at time T, ti—i—ty time to failure)). The third goal is to analyze the time to failure as a function of service life and to assess the dependability of the WF under consideration as a function of service life. The three-state model of the WF operation process presented in the research serves as the foundation for the analytical analysis of WF reliability. The probability of fitness (Po(t)) of the WF system and the mean time to failure were calculated based on the analytical quantities denoting this model (MTTF). The WF owner can make the best choice regarding the proper WF renewal actions with the help of knowledge of these current dependability values for an in-service WF system.

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Abdul Wahid Arohman, Muhamad Agus, Solahhudin, and Desy Agustin. "Analisis Preventive Maintenance pada Mesin Injection Molding dengan Metode Mean Time Between Failure dan Mean Time to Repair di PT. XZY." Jurnal Serambi Engineering 9, no. 1 (2023): 7623–30. http://dx.doi.org/10.32672/jse.v9i1.720.

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A series of predictable preventive activities to overcome machine failure during operation is very important because it produces good and stable spare parts. This research was carried out with the aim of preventing machine damage due to short circuits that occur in injection molding machines used for the sudden production of automotive component spare parts. The research was carried out using the Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR) approaches to calculate the time between the machine breaking down and the time it was repaired. The MTBF calculation results in this research were 72.9 hours or less than 4 days the engine would experience damage or every 72.9 hours the engine would experience damage again. The MTTR value obtained is 2 hours, where in 2 hours the work to overcome the damage can be done.

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Silvia, Silvia, Reviana Inda Dwi Suyatmo, and Murnianti Murnianti. "Analisis Preventive Maintenance Berdasarkan Mean Time Between Failure (MTBF) Dan Mean Time To Repair (MTTR) Pada Alat Blow Molding Di PT XYZ." Jurnal Pengabdian Masyarakat Bangsa 2, no. 8 (2024): 3471–78. http://dx.doi.org/10.59837/jpmba.v2i8.1495.

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PT XYZ merupakan perusahaan yang bergerak di bidang manufaktur aksesoris mobil otomotif dan interior kelautan yang berkembang. Sebagian besar produk plastik yang dihasilkan dibuat menggunakan mesin blow molding dengan produk yang sangat bervariasi Sehingga, apabila terjadi kerusakan maka akan menyebabkan produksi tidak bisa berjalan sebagaimana semestinya. Tujuan kegiatan ini adalah menganalisis Preventive Maintenance berdasarkan Mean Time Between Failure (MTBF) dan Mean Time To Repair (MTTR) pada alat blow molding. Preventive maintenance merupakan bagian dari Planned Maintenance Pillar yang merupakan salah satu pillar dalam Total Productive Maintenance (TPM). Metode ini merupakan bagian utama dari sistem pemeliharaan yang banyak diterapkan oleh perusahaaan Jepang dan memiliki peranan penting, karena dapat menekan biaya produksi, meningkatkan produktivitas, dan efisiensi mesin/peralatan sehingga kerugian yang diakibatkan oleh kerusakan mesin dapat dihindarkan. Berdasarkan data yang diperoleh, nilai MTBF mesin blow 2 dan 3 lebih rendah daripada mesin blow molding 1 dan 4 sedangkan nilai MTTR sebesar 104,5 menit. Total failure pada mesin blow molding 1, 2, 3, dan 4, failure pada jet loader dan pressure paling sering terjadi. Untuk penentuan kebijakan preventive maintenance dilakukan dengan meminimalkan biaya dilakukan. Rekomendasi yang dapat dilakukan adalah pelaporan waktu perbaikan tiap terjadi kerusakan dilengkapi, estimasi biaya untuk menghitung jangka waktu preventive maintenance, serta perhitungan MTBF MTTR untuk mesin yang lain.

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Mondro, M. J. "Approximation of mean time between failure when a system has periodic maintenance." IEEE Transactions on Reliability 51, no. 2 (2002): 166–67. http://dx.doi.org/10.1109/tr.2002.1011521.

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Novarika, Wirda, Mahrani Arfah, and Ridho Agustian. "Analisis Preventive Maintenance pada Mesin Heater Kernel Dengan Metode Menghitung Mean Time Between Failure (MTBF) dan Mean Time To Repair (MTTR) di PT. Supra Matra Abadi." JURNAL UNITEK 16, no. 2 (2023): 259–67. http://dx.doi.org/10.52072/unitek.v16i2.544.

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Tujuan dari penelitian ini untuk meminimalisir dan mengetahui jadwal Preventive Maintenance mesin Heater Kernel yang efektif dan mengetahui sejauh mana Preventive Maintenance pada mesin Heater Kernel dengan metode Mean Time Between Failure (MTBF) dan Mean Time To Repair (MTTR) dapat membantu mengurangi Breakdown dan downtime. Mean Time Between Failure (MTBF) dan Mean Time to Repair (MTTR) adalah salah satu metode sebagai acuan untuk menetapkan jadwal perawatan yang efektif. Oleh karena itu perlu tindakan preventive maintenance agar dapat meningkatkan kinerja dari perusahaan, hasil analisa didapatkan nilai Mean Time Between Failure (MTBF) 18.830 menit, yang mana hasil perhitungan ini didapat dari menghitung waktu mesin selesai diperbaiki sampai mesin mengalami kerusakan kembali dan Mean Time to Repair (MTTR) 257 menit, yang dihasilkan dari perhitungan mekanik mulai memperbaiki mesin sampai mekanik selesai memerbaiki mesin. Hasil penerapan tindakan preventive maintenance rata-rata 79,80% sehingga mesin mampu bekerja secara optimal

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Fatma, Nur Fadilah, Henri Ponda, and Rizky Aditya Kuswara. "ANALISIS PREVENTIVE MAINTENANCE DENGAN METODE MENGHITUNG MEAN TIME BETWEEN FAILURE (MTBF) DAN MEAN TIME TO REPAIR (MTTR) (STUDI KASUS PT. GAJAH TUNGGAL TBK)." Heuristic 17, no. 2 (2020): 87–94. http://dx.doi.org/10.30996/heuristic.v17i2.4648.

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Mesin beroperasi secara terus menerus menyebabkan menurunnya tingkat kehandalan peralatan serta menyebabkan sering terjadinya breakdown dan downtime yang tinggi pada mesin-mesinnya terutama pada mesin Extruder (ITE). Untuk meminimalisir terjadinya breakdown dan downtime maka perlu adanya sistem penjadwalan perawatan yang baik guna mencegah terjadinya kerusakan mesin. Mean Time Between Failure (MTBF) dan Mean Time to Repair (MTTR) adalah salah satu metode sebagai acuan untuk menetapkan jadwal perawatan yang efektif. Oleh karena itu, diperlukannya tindakan preventive maintenance agar dapat meningkatkan kinerja dari perusahaan, Dari hasil analisa didapatkan nilai Mean Time Between Failure (MTBF) 259,04 menit dan Mean Time to Repair (MTTR) 19.990,1 menit. Perubahan penjadwalan preventive maintenance dapat dilakukan dengan interval waktu 2 minggu sekali untuk aktivitas cleaning ac panel dan cleaning motor blower. Hasil penerapan tindakan preventive maintenance rata-rata 98% sehingga mesin mampu bekerja secara optimal.

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Hery, D. Putra1 Abdullah Afif Siregar2 Nizam Z. Akbar2 Anggia C. Lubis2 T. Bob Haykal2 Harris Hasan2. "CORRELATION BETWEEN VENTRICULAR ACTIVATION TIME FROM 12-LEAD ECG AND LEFT VENTRICULAR SYSTOLIC FUNCTION IN PATIENTS DIAGNOSED WITH HYPERTENSION." INTERNATIONAL JOURNAL OF RESEARCH SCIENCE & MANAGEMENT 7, no. 3 (2020): 20–26. https://doi.org/10.5281/zenodo.3734255.

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Background: Hypertension is a cardiovascular risk factor which could lead pressure overload in left ventricle then causing diastolic and systolic dysfunction. Echocardiography has important role to assess heart structure and function in hypertensive patients, still the myocardial changes actually has occurred before remodelling of left ventricle. Electrical changes of the heart would develop first, which ventricular activation time (VAT) duration from ECG increased in left ventricular hypertrophy. This condition is closely related to course of hypertensive disease. The aim of this study is to investigate correlation between VAT and left ventricular ejection fraction in hypertensive patients. Method: Data were collected from 60 consecutive patients with hypertension whom visiting policlinic in Cardiac Centre Haji Adam Malik General Hospital Medan. Data of VAT (Q-T interval) from ECG and left ventricular ejection fraction (LVEF) form echocardiography were collected and analyzed. Then the duration of VAT and LVEF changed were assessed. Statistical analysis was performed using correlation and comparative test, including scatter-plot graphic. Result: Among 60 hypertensive patients as total subject, divided to 30 subjects with diastolic heart failure and 30 subjects with systolic heart failure. Mean of VAT duration from total subject was 42 miliseconds and mean of LVEF was 45.71%, while mean of LVEF in diastolic heart failure group was 56% and mean of LVEF in systolic heart failure group was 35.43%. Spearman correlation test was used to assess relationship between VAT and LVEF, the result showed there was reverse correlation with p < 0.001 and had strong correlation with coefficient r = - 0.789. Then Mann-Whitney comparative test was performed to compare VAT between diastolic heart failure group and systolic heart failure group, the result showed statistically significant difference between 2 groups. Conclusions: VAT duration from ECG in hypertensive patients and LVEF have reverse correlation, which means the increasing of VAT duration related to the decreasing of LVEF. Besides, there is a significant difference of VAT duration of hypertensive patients between diastolic heart failure and systolic heart failure with mean cut-off value is 44.68 miliseconds.

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O.C.Onuigbo and Edokpia R.O. "Tripping Profile of 11kv Feeders in Benin City, Edo State, Nigeria." Tripping Profile of 11kv Feeders in Benin City, Edo State, Nigeria 8, no. 12 (2023): 5. https://doi.org/10.5281/zenodo.10409799.

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Nigeria’s power supply has been experiencing incessant interruptions due to failures in the distribution system. The maintainability of the power system is important in meeting customers demand. The maintainability of three 11kv feeder in Benin Electricity Distribution Company (BEDC), Edo State Nigeria is evaluated in this study. The failure data which includes; time of failure, time outage was restored, causes of failure, and the failure time were collated and collected from the Injection substations of the three feeders for the year 2020 and 2021. Monthly and Yearly Mean time between failures (MTBF) and failure rate were calculated for the analysis. The analysis results revealed that the year 2021 had an increased failure rates than the year 2020 for the three feeders which implies a better performance. Keywords:- Failure Time, Repair Time, Maintainability, Mean Time to Repair (MTTR), and Repair Rate.

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Nikolayenko, V., and T. Mikulik. "PROLEGOMENA OF THE KINETIC THEORY OF RELIABILITY AND DURABILITY OF MACHINES AND DEVICES BY WOLFRID NIKOLAYEVICH TRAYER." Sciences of Europe, no. 141 (May 27, 2024): 103–6. https://doi.org/10.5281/zenodo.11359108.

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Chae, Eunkyung, and Duck-ho Shin. "Analysis of Mean Time Between Failure of Hot-standby Sparing Systems for Railway." Journal of the Korean Society for Railway 22, no. 12 (2019): 951–57. http://dx.doi.org/10.7782/jksr.2019.22.12.951.

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., Suneel Kr Srivastava. "RELIABILITY ANALYSIS & PREDICTION OF MEAN TIME BETWEEN FAILURE OF FLIGHT DATA RECORDER." International Journal of Research in Engineering and Technology 04, no. 22 (2015): 54–57. http://dx.doi.org/10.15623/ijret.2015.0422014.

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Wang, Haiyan, Diantong Kang, and Lei Yan. "On the Generalized Decreasing Mean Time to Failure or Replaced Ordering." Computational Intelligence and Neuroscience 2021 (November 15, 2021): 1–23. http://dx.doi.org/10.1155/2021/7508812.

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In this paper, we establish two new stochastic orders, DMTFR (decreasing mean time to failure or replaced) and GDMTFR (generalized decreasing mean time to failure or replaced), and mainly investigate properties of the GDMTFR order. Some characterizations of the GDMTFR order are given. The implication relationships between the DMTFR and the GDMTFR orders are considered. Also, closure and reversed closure properties of the new order GDMTFR are investigated. Meanwhile, several illustrative examples that meet the GDMTFR order are shown as well.

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KNAFL, G. J., J. A. MORGAN, R. L. FOLLENWEIDER, and R. M. KARCICH. "SOFTWARE FAILURE DATA ANALYSIS USING THE LEAST SQUARES APPROACH AND THE TIME PER FAILURE CONCEPT." International Journal of Reliability, Quality and Safety Engineering 02, no. 02 (1995): 161–76. http://dx.doi.org/10.1142/s0218539395000137.

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We adapt data analytic techniques to the software reliability setting. We develop an evaluation procedure based on scatterplots of transformed data, crossvalidation using the predicted residual sum of squares (PRESS) criterion, residual plots, and normal plots. We analyze a software failure data set collected at Storage Technology Corporation utilizing this evaluation technique. We identify a new model which, for this data set, outperforms several established software reliability models, including the delayed S-shaped, exponential, inverse linear, logarithmic, power, and log power models. The failure intensity, and hence the reliability, for this model at any point in time is a function of the time per failure, that is, the ratio of cumulative time divided by cumulative failures, a quantity that agrees with the mean time between failures for time points at which failures occur.

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Fakher, Sherif, Abdelaziz Khlaifat, and Hashim Nameer. "Improving electric submersible pumps efficiency and mean time between failure using permanent magnet motor." Upstream Oil and Gas Technology 9 (September 2022): 100074. http://dx.doi.org/10.1016/j.upstre.2022.100074.

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Engelhardt, Max, and Lee J. Bain. "On the Mean Time between Failures for Repairable Systems." IEEE Transactions on Reliability 35, no. 4 (1986): 419–22. http://dx.doi.org/10.1109/tr.1986.4335491.

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Wang, Fu-Kwun, and Tao-Peng Chu. "The mean time between failures for an LCD panel." Quality and Reliability Engineering International 27, no. 2 (2011): 203–8. http://dx.doi.org/10.1002/qre.1113.

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ISHA, SANITHA S., and P. A. RAMAKRISHNAN. "DESIGN AND FINITE ELEMENT ANALYSIS TO IMPROVE MTBF OF VARIABLE SPEED CENTRIFUGAL PUMP." IJIERT - International Journal of Innovations in Engineering Research and Technology 5, no. 5 (2018): 73–81. https://doi.org/10.5281/zenodo.1446227.

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Vibration analysis is a technique for analyzing vibration spectrum of individual machine components and identifying its causes and extends of failures. The method of vibration analysis is not only minimizes the need for extensive,but makes it possible to detect developing problems which are out of the range of human sense of touch and hearing. The Objective of this work is to study the problems results in the failure of pump and suggest some better maintenance strategies to improve MTBF (Mean Time between Failures) of the pump and the motor and to reduce maintenance cost by finite element analysis using ANSYS R14.5 software. Results have been discussed and found that parallel misalignment of pump - motor coupling and defect s in pump foundation lead to excess vibration . Required actions were performed and the vibration at the drive end and non - drive end of the motor has been reduced by 30.5 % and 29.4 % respectively. https://www.ijiert.org/paper-details?paper_id=141287

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Wang, Zhi Ming. "Log-Linear Process Modeling of Reliability Assessment for Numerical Control Machine Tools." Advanced Materials Research 542-543 (June 2012): 1200–1203. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1200.

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The point maximum likelihood and interval estimators of the parameters, as well as two reliability indices of the log-linear process model, including cumulative mean time between failures and reliability at given time are given. In tests for failure time trends, both the graphical methods include the mean cumulative function versus time plot and the total-time-on-test plot, and the analytical methods include the Laplace, the military handbook, and the Lewis-Robinson tests are used. A real case of failure dada with time truncation for multiple numerical control (NC) machine tools is given to illustrate the use of the proposed model.

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Vittoria, Gabriele, Antonio Fascì, Matteo Ferrario, and Giovanni Giuliani. "PP126 MEA In Italy: Correlation Between Time To Payment By Result And Time To Off Treatment Curve." International Journal of Technology Assessment in Health Care 33, S1 (2017): 131–32. http://dx.doi.org/10.1017/s0266462317002811.

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INTRODUCTION:Payment by result agreements have been quite widely used in Italy to provide access for high costs oncologic drugs and minimize uncertainties of real life benefits (1). The aim of this analysis was to overview the Roche experience in terms of Payment by Result (Pbr) in oncology and investigate the relation between timing for the evaluation of treatment failures and observed Time to Off Treatment (TTOT) from Phase III clinical trials (2).METHODS:A retrospective analysis of the Roche payment by results schemes in place in Italy was conducted. For each drug included in the analysis it was collected: (i) the negotiated timing to assess the treatment failure for payment by result, (ii) the median time to off treatment curve observed in clinical trials for the experimental drug, (iii) the median time to off treatment observed in clinical trials for the control arm. The mean ratios between timing to assess the treatment failure for payment by result and the time to off treatment observed for the experimental drug or the median time to off treatment observed in the control arm were calculated to identify potential correlations. High level of correlation was expected if ratio was close to 1 (±.2).RESULTS:Roche products or different indications of the same product were identified as candidates for the analysis from 2008 to 2016. The timing for the evaluation of treatment failures for Pbr varies between 2 and 9 months, depending on the type of tumor and line of therapy. The mean Time to Payment By Result (TTPbr) / Control arm Time To Off Treatment (cTTOT) ratio was 1.16 (±.37) while the mean Time to Payment By Result (TTPbr) / Experimental arm Time To Off Treatment (eTTOT) ratio was .71 (±.13). Data analysis according to different time periods shows that the mean TTPbr/cTTOT and TTPbr/eTTOT for drugs negotiated from 2008 to 2015 were respectively 1.07 and 1.39 whereas for drugs negotiated in 2016 were respectively and .63 and 1.CONCLUSIONS:Good level of correlation between TTPbr and cTTOT was found. This finding is in line with the methodology used by Italian Medicines Agency so far, leveraging the cTTOT as the most appropriate proxy to assess any incremental effect of a new drug compared to the previous Standard of Care. The analysis over time of TTPbr shows that in the first years of payment by result negotiation TTPbr is more correlated to the cTTOT whereas in the last years is moving closer to the experimental one.

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Biehichev, S. V., H. S. Ishutina, L. A. Chumak, and A. P. Hoichuk. "Assessing the reliability of a surveying and geodetic network based on a Markov model." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 6 (December 30, 2024): 21–27. https://doi.org/10.33271/nvngu/2024-6/021.

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Purpose. To build a graph of states and transitions of the surveying-geodetic network (SGN), which includes 16 points. To study the functioning of constructed discrete-continuous stochastic Markov models of the surveying-geodetic network with full and current recovery. To perform a numerical calculation of reliability, safety and efficiency indicators: readiness ratio, limit probability states, mean time to failure, mean time between failures. Methodology. A model of SGN functioning is built in the form of a graph of states and transitions with current and full recovery. Based on the model in the Mathcad software, the availability factor, mean time to failure, mean time between failures are calculated. The following graphs are built: readiness functions, probabilities of operation until the first failure, and frequency of getting into an emergency situation. Findings. Constructed discrete-continuous stochastic Markov reliability models of the boundary probability states, mean time between failures, mean time to the first failure have been analyzed. The probability of fault-free operation is presented graphically in the form of a transition graph, which describes the logic of the operation of the SGN. Based on the graph of states and transitions (graphical model) according to the Kolmogorov-Chapman algorithm, an analytical model of the reliability behavior of the surveying-geodetic network was built. A system of linear Kolmogorov-Chapman differential equations was compiled and solved. The distribution of probabilities of being in each state of the surveying-geodetic network has been obtained. Originality. For the first time in surveying practice, a reasonable choice of a discrete-continuous stochastic model of the functioning of a surveying-geodetic network based on the application of the state space method has been made. This model most fully describes the process of functioning (behavior) of the dynamic system. Dependencies between reliability indicators and safety indicators are established. It is recommended to use a model with ongoing network recovery, which allows you to maintain a given level of reliability through timely maintenance (recovery). Practical value. The most expedient time for restoration of geodetic points with certain failure intensity parameters has been determined. It has been done in order to maintain the SGN in an operational state with a given level of reliability. Current network recovery makes it possible to maintain reliability at the desired level. In the case of complete restoration of the SGN, the readiness factor will be lower, but such a system will be significantly cheaper.

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Wang, Hong De. "Study on Failure Process Deterioration and its Amelioration of Mine Ventilation System." Advanced Materials Research 634-638 (January 2013): 3502–5. http://dx.doi.org/10.4028/www.scientific.net/amr.634-638.3502.

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Mine ventilation system is a repairable system, with the characters of time-varied and randomness. It made us encounter some difficulties when we discussed the system failure evolution process and its operational reliability, as well as when we sought the system reliability parameters developing trends following with ventilation system operation time variation and air adjustment. Firstly, according to the reliability theory, the failure process characteristic values, which affect the ventilation system, were defined. And then, by mean of the analysis of the failure process deterioration of mine ventilation system, the deterioration and its amelioration discriminants are given basing on two parameters’ Weibull process. Finally, on the basis of adaptive neural network technology, the ventilation system failure processes were simulated, the failure process characteristic parameters were determined, and the failure curves were drawn accordingly. The results show that the failure process of the experiment mine ventilation system is a Non-homogeneous Poisson Process; the mean time between failures of the ventilation system is between 160h and 170h; the failure ratio curves present the trends of concave or convex variation when the system failure process deterioration or amelioration.

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Lee, Jimin, Robert Yearout, and Donna Parsons. "Systematic Routine for Setting Confidence Levels for Mean Time to Failure (MTTF)." Industrial and Systems Engineering Review 2, no. 1 (2014): 62–69. http://dx.doi.org/10.37266/iser.2014v2i1.pp62-69.

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There are circumstances where an item is intentionally tested to destruction. The purpose of this technique is to determine the failure rate (λ) of a tested item. For these items, the quality attribute is defined as how long the item will last until failure. Once the failure rate is determined from the number of survivors and total time of all items tested the mean time to failure (MTTF) which is a typical statistic for survival data analysis issues. MTTF is calculated by dividing one by failure rate (λ). From this one obtains the reliability function R(t) = e-λt where t is time. This allows the cumulative density function F(t) = 1- e-λt to be determined. This density function, f(t) = λe-λt is a negative exponential with a standard deviation (σ) = 1/λ. Thus setting a warranty policy for the tested item is difficult for the practitioner. An important property of the exponential distribution is that it is memory less. This means its conditional probability follows P(T > s + t |T > s)=P(T > t) for all s, t ≥0. The exponential distribution can be used to describe the interval lengths between any two consecutive arrival times in a homogeneous Poisson process. The purpose of this research paper is to present a simple technique to determine a realistic confidence level. Using the same technique the warranty level for the tested item can be predicted.

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Syed Zegham Taj and Syed Mohammed Rizwan. "Comparative Analysis Between Three Reliability Models of a Two-Unit Complex Industrial System." Journal of Advanced Research in Applied Sciences and Engineering Technology 30, no. 2 (2023): 243–54. http://dx.doi.org/10.37934/araset.30.2.243254.

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This paper presents the reliability modelling and analysis of a complex industrial system with two units operating in parallel. To facilitate the study, real failure-maintenance data of the system arecollected. Data depicts that a unit is repaired upon failure by a single repairman. Reliability indices of the system such as mean time between failures, availability, expected number of repairs, and expected busy period of the repairman are estimated using semi-Markov processes and regenerative processes. Finally, a comparative analysis between the reliability indices of three reliability models for the system is presented.

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Rekab, Kamel. "Bayesian estimation of the difference between two mean times to failure." Stochastic Analysis and Applications 10, no. 3 (1992): 343–50. http://dx.doi.org/10.1080/07362999208809273.

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Vintr, Zdenek, and Michal Vintr. "Contribution to Rolling Bearing Reliability Modeling." Applied Mechanics and Materials 110-116 (October 2011): 2497–503. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.2497.

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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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Fan, Lihong, Rui Tu, Zengji Zheng, et al. "Evaluation of Signal-in-Space Continuity and Availability for BeiDou Satellite Considering Failures." Journal of Navigation 73, no. 2 (2019): 312–23. http://dx.doi.org/10.1017/s0373463319000602.

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Signal-in-space (SIS) continuity and availability are important indicators of performance assessment for Global Navigation Satellite Systems (GNSSs). The BeiDou Navigation Satellite System (BDS) Open Service Performance Standard (BDS-OS-PS-1.0) has been released, and the corresponding public performance indicators have been provided, but the actual SIS performance is uncertain to users. SIS continuity and availability are primarily related to unscheduled outages (failures). Therefore, based on the existing failure classification system and actual operation modes, four types of failure modes are first analysed: long-term failure related to satellite service period, maintenance failure related to satellite manoeuvring, short-term failure associated with random repairable anomalies and equivalent failure corresponding to a combination of the above three types of failures. Second, based on the failure classification and selected precise and broadcast ephemerides from 2015–2016, the Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR) of each failure type are obtained using appropriate detection methods. Finally, using a corresponding assessment model, the SIS continuity and availability of BeiDou are calculated for individual and equivalent failure cases, and these are compared with the provided index in the BDS Open Service Performance Standard.

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Li, Heqing, and Qing Tan. "Mean Time Between Failures Forecasting Method Based on Neural Network." Advanced Science Letters 11, no. 1 (2012): 622–26. http://dx.doi.org/10.1166/asl.2012.2931.

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Prasad, Dr R. Satya, S. Murali Mohan, and G. Krishna Mohan. "Exponential two step approach for Time Domain based Software Process Control." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 8, no. 2 (2013): 777–86. http://dx.doi.org/10.24297/ijct.v8i2.3385.

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Software Reliability Growth Model is a mathematical model of how the software reliability improves as faults are detected and repaired. In this paper we propose a control mechanism based on the cumulative quantity between observations of time domain failure data using mean value function of Goel-Okumoto model, which is based on Non Homogenous Poisson Process. The model parameters are estimated by a two step approach. Software reliability process can be monitored efficiently by using Statistical Process Control. Control charts are widely used for process monitoring. It assists the software development team to identify failures and actions to be taken during software failure process and hence, assures better software reliability.Â

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Birdawod, Hawkar Q., Dlshad M. Saleh, Dashty I. Jamil, and AbdulRahim K. Rahi. "Adopting Discrete Wavelet Transformation with Mean Time Between Failure to Design a New Quality Control Chart." Cihan University-Erbil Scientific Journal 9, no. 1 (2025): 47–51. https://doi.org/10.24086/cuesj.v9n1y2025.pp47-51.

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This study’s goal was to design a new individual observation chart for quality control by utilizing the discrete wavelet transformation (DWT) approach to calculate the mean time between reliability failures. The new chart’s effectiveness was demonstrated by comparing it to a classical chart. This aspect is crucial in addition to the conclusion that the production process is under control for both charts, with the new chart exhibiting a reduced standard deviation. The study’s main focus was on a new area for device monitoring and defect detection, which involves halting production and eliminating any potential causes of defects. One of the main elements that aid in achieving the goals of predictive maintenance is the individual control chart based on the mean time between failures with DWT of the operating time between failures.

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Matocha, Kevin, and Richard Beaupre. "Time-Dependent Dielectric Breakdown of Thermal Oxides on 4H-SiC." Materials Science Forum 556-557 (September 2007): 675–78. http://dx.doi.org/10.4028/www.scientific.net/msf.556-557.675.

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Thermal oxides on 4H-SiC are characterized using time-dependent dielectric breakdown techniques at electric fields between 6 and 10 MV/cm. At 250°C, oxides thermally-grown using N2O with NO annealing achieve a mean time to failure (MTTF) of 2300 hours at 6 MV/cm. Oxides grown in steam with NO annealing show approximately four times longer MTTF than N2O-grown oxides. At electric fields greater than 8 MV/cm, Fowler-Nordheim tunneling significantly reduces the expected failure times. For this reason, extrapolation of mean-time to failure at low fields must be performed by datapoints measured at lower electric fields.

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Wang, Zhi-Ming, and Xia Yu. "Log-linear process modeling for repairable systems with time trends and its applications in reliability assessment of numerically controlled machine tools." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 227, no. 1 (2012): 55–65. http://dx.doi.org/10.1177/1748006x12460633.

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Two non-homogeneous Poisson processes including the power law process and the log-linear process with reliability improvement or deterioration are analyzed. Based on Akaike information criterion and Bayesian information criterion, the best model of failure data is presented. The point maximum likelihood and interval estimators of the parameters, as well as seven reliability indices of the log-linear process model, such as cumulative mean time between failures, cumulative number of failures, reliability at a given time, and warranty time given reliability are given. In tests for failure time trends, both the graphical methods, including the cumulative failures versus time plot and the total-time-on-test plot, and the analytical methods including the Laplace, the Military Handbook, and the Lewis–Robinson tests are used. Three real cases for failure data with failure truncation and time truncation of multiple numerically controlled machine tools are given to illustrate the use of the proposed models.

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Prakoso, Agung, Bima Candra Gautama Adi Setyo, Denny Dermawan, Cyrilus Sukaca Budiono, Indro Lukito, and Riski Kurniawan. "Analisa kegagalan sistem beta pesawat Grob G 120TP-A dengan menggunakan metode Mean Time Between Failure." Jumantara Jurnal Manajemen dan Teknologi Rekayasa 3, no. 2 (2024): 113. http://dx.doi.org/10.28989/jumantara.v3i2.2378.

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Ivanov, D. A. "Analysis of the reasons for low mean time between failures of pumping equipment at a high-viscosity permo-carbon oil deposit." Nauka Innovatsii Tekhnologii, no. 3 (2024): 157–79. https://doi.org/10.37493/2308-4758.2024.3.8.

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Sucker-rod pumping unit in operation after huff and puff cyclic steam injection operates in a wide range of rheological properties of fluids and medium temperatures. During the initial stage after steam injection, hot liquid fluids are extracted with a temperature of about 200°C and a viscosity of several tens of cP. During this period, all injected water is also pumped out of the reservoir, which entered the reservoir in the form of steam during steam injection phase. After several months of operation, after the bottom-hole zone cools down, the viscosity of the oil increases to several hundred cP. The influence of stable emulsions on the properties of fluids also increases. These changes lead to increased loads and torque on pumping equipment during operation, which leads to premature failures. The challenge to secure long-term operations with a high mean time between failures of pumping units is critical and demanding. The analysis of the main causes and trends of low mean time between failure using a large array of information and data was performed. Certain big data analysis approaches have been developed and presented and used to formulated qualitative and quantitative conclusions and recommendations. The field uses the same type of pumping equipment with only a change in the diameter of the plunger depending on the flow rate. Based on the results of the analysis, the area of the field was identified where it is necessary to make significant changes in the pump parameters due to the increased viscosity of the oil. In such conditions according to world practice longer stroke sucker-rod pumping unit is used reducing the number of strokes, increasing mean time between failure. Experience in similar fields in other regions of the world also indicates the need to use machine learning to improve pump performance.

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Suresh Kumar Sahani. "Performance and Assessment of Jaw Crusher in a Cement Manufacturing Plant." Communications on Applied Nonlinear Analysis 32, no. 3 (2025): 904–9. https://doi.org/10.52783/cana.v32.4855.

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Jaw crushers are essential apparatus in cement production facilities, principally utilized for pulverizing raw materials such as limestone, clay, and other minerals. The dependability of jaw crushers strongly influences production efficiency and maintenance expenses. This research examines the repair and failure rates of jaw crushers in a cement factory, assessing prevalent failure types, their underlying causes, and maintenance solutions to enhance equipment uptime. Data was gathered from maintenance logs over a two-year duration, and statistical analysis was conducted to ascertain Mean Time between Failures (MTBF) and Mean Time to Repair (MTTR). The results indicate that wear-related failures, such as jaw plate wear and bearing failures, constitute more than 60% of breakdowns, whereas lubrication problems contribute to 25% of failures. The use of predictive maintenance and the utilization of premium replacement parts can substantially save downtime and operating expenses.

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Lee, Lester, Sharon Low, David Low, Lee Ping Ng, Colum Nolan, and Wan Tew Seow. "Late pediatric ventriculoperitoneal shunt failures: a Singapore tertiary institution's experience." Neurosurgical Focus 41, no. 5 (2016): E7. http://dx.doi.org/10.3171/2016.8.focus16277.

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OBJECTIVE The introduction of ventriculoperitoneal shunts changed the way hydrocephalus was treated. Whereas much is known about the causes of shunt failure in the first few years, there is a paucity of data in the literature regarding the cause of late shunt failures. The authors conducted a study to find out the different causes of late shunt failures in their institution. METHODS A 10-year retrospective study of all the patients who were treated in the authors' hospital between 2006 and 2015 was conducted. Late shunt failures included those in patients who had to undergo shunt revision more than 5 years after their initial shunt insertion. The patient's notes and scans were reviewed to obtain the age and sex of the patient, the time it took for the shunt to fail, the reason for failure, and the patient's follow-up. RESULTS Forty-six patients in the authors' institution experienced 48 late shunt failures in the last 10 years. Their ages ranged from 7 to 26 years (12.23 ± 4.459 years [mean ± SD]). The time it took for the shunts to fail was between 6 and 24 years (mean 10.25 ± 3.77 years). Reasons for failure resulting in shunt revision include shunt fracture in 24 patients (50%), shunt blockage in 14 patients (29.2%), tract fibrosis in 6 patients (12.5%), shunt dislodgement in 2 patients (4.2%), and shunt erosion in 2 patients (4.2%). Postoperative follow-up for the patients ranged from 6 to 138 months (mean 45.15 ± 33.26 months). CONCLUSIONS Late shunt failure is caused by the effects of aging on the shunt, and the complications are different from early shunt failure. A large proportion are complications associated with shunt calcification. The authors advocate a long follow-up for pediatric patients with shunts in situ to monitor them for various causes of late shunt failure.

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Izadi, Muhyiddin, Maryam Sharafi, and Baha-Eldin Khaledi. "New nonparametric classes of distributions in terms of mean time to failure in age replacement." Journal of Applied Probability 55, no. 4 (2018): 1238–48. http://dx.doi.org/10.1017/jpr.2018.82.

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Abstract The mean time to failure (MTTF) function in age replacement is used to evaluate the performance and effectiveness of the age replacement policy. In this paper, based on the MTTF function, we introduce two new nonparametric classes of lifetime distributions with nonmonotonic mean time to failure in age replacement; increasing then decreasing MTTF (IDMTTF) and decreasing then increasing MTTF (DIMTTF). The implications between these classes of distributions and some existing classes of nonmonotonic ageing classes are studied. The characterizations of IDMTTF and DIMTTF in terms of the scaled total time on test transform are also obtained.

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Hällgren, Bengt. "Availability compliance testing of systems with long mean time between failures." Reliability Engineering 15, no. 2 (1986): 83–94. http://dx.doi.org/10.1016/0143-8174(86)90074-0.

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Nikitchuk, A. V. "Impact of Electronic Components Thermal Resilience on the Reliability of Radio-Electronic Equipment." Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, no. 98 (December 30, 2024): 38–45. https://doi.org/10.20535/radap.2024.98.38-45.

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The article focuses on the impact of temperature on the reliability of electronic components, as in non-redundant radio-electronic equipment, the failure of any component typically leads to the failure of the entire device. The methods and approaches used to analyze the electronics reliability, predict operational lifespans, and to enhance it are considered. Thermal effects are among the most significant factors influencing reliability indicators of electronics, such as the probability of failure-free operation and mean time to failure. The sequence of accounting for thermal factors during the calculations of operational failure rate, mean time to failure, and the probability of failure-free operation according to the recommendations of Ukrainian State Standards is analyzed. The primary focus is on calculating the mean time to failure for various groups of resistors, capacitors, integrated circuits, and semiconductor components. Modern approaches to reliability assessment are used in the study, particularly a combination of failure physics and computer modeling. It was determined that the difference in the mean time to failure between the most and least thermally resilient electronic components of radio-electronic equipment can be very significant and only increases with rising temperatures.

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Alexander, Dennis, Sarini Abdullah, and Adam Fahsyah Nurzaman. "Bayesian Accelerated Failure Time Model for Risk Pregnancy Detection." Engineering, MAthematics and Computer Science Journal (EMACS) 5, no. 3 (2023): 181–87. http://dx.doi.org/10.21512/emacsjournal.v5i3.10540.

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Preeclampsia (PE) also known as a hypertension during third trisemester of pregnancy. PE, is one of the most feared complications of pregnancy because it can potentially become serious complications in the future, including mother and fetus’s death. The goal of this study is other than to have a bettter undestanding about risk factor in pregnancy by modelling the relationship between several factors and the time until deliveries under the PE condition. Data on 924 patients at obstetric and gynecology department in Jakarta were used in the analysis. Accelerated Failure Time (AFT) model was proposed to indentify some risk factors that influenced the condition. Model parameters were estimated using Bayesian method. Due to imbalance data, undersampling method will be used as a pre-procesing stage. Ratio between PE and non-PE data will be 60:40. Flat prior and posterior sample will be used using MCMC simulation with 12,000 iterations (including 2,000 iterations as a burnin stage) to get a convergen result. The iteration was repeated for 100 times so that the chosen data from undersampling was not error and biased. A consistent result for credible interval of the mean result was considered as the factors that affect PE condition consistently. From this study, there are two factors that have consistent Credible Interval result, Body Mass Index (BMI) and Mean Arterial Pressure (MAP).

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Florea, Vlad Alexandru, Dragos Pasculescu, and Vlad Mihai Pasculescu. "Reliability and maintainability of scraper conveyor used in coal mining in the Jiu Valley." Mining of Mineral Deposits 15, no. 3 (2021): 16–21. http://dx.doi.org/10.33271/mining15.03.016.

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Purpose.The aim of the study is to determine and analyse causes of faults in the operation of TR-7A scraper conveyor and to estimate the required time for their remediation and select the methods of their prevention and elimination. Methods. The characteristic of a system, such as the scraper conveyor, intended to fulfil its specified function in time and operation conditions, can be studied, theoretically, by determining its operational reliability. This implies the existence of a framework that incorporates several interconnected components of technical, operational, commercial and management nature. The quantitative expression of reliability was based on elements of mathematical probability theory and statistics (exponential distribution law), failure and repair mechanism not being subject to certain laws. Findings. The following TR-7A subassemblies, if defective, could have been the cause of a failure: chains, hydraulic couplings, chain lifters, drive, return drums, some electrical equipment. After 28 months of monitoring the TR-7A operation, we have established the number of failures (defects) ni, the operating time between failures ti, frequency of failures fc, time to repair tri, weight repair time pr, mean time between failures (MTBF), mean time to repair (MTR). Originality.Data collection and processing involves the adoption of specific procedures to allow the correct highlighting of the causes and frequency of failures. The accomplishment of this approach allowed finding the solutions for increasing reliability of some subassemblies of TR-7A conveyor (i.e., those subjected to abrasive wear). Practical implications.One solution was to use materials with compositional and functional gradient in the case of worn surfaces of some subassemblies. It was successfully applied for the chain lifters where a significant increase in the mean time between failures was obtained. The field of application of these materials can be extended to the metal subassemblies of machines and equipment with abrasion wear that occurs both in underground mines and in quarries.

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Venkatesan, Ramasamy, Narayanaswamy Vedachalam, Karakunnel Jossia Joseph, and Gopalakrishnan Vengatesan. "Data Returns and Reliability Metrics From the Indian Deep Ocean Wave Measurement Buoys." Marine Technology Society Journal 53, no. 6 (2019): 6–20. http://dx.doi.org/10.4031/mtsj.53.6.1.

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AbstractReliable performance is the key requirement for deep ocean wave measurement buoys as failures lead to loss of data and expensive reinstallations. From more than 0.37 million demanding offshore wave measurement buoy-hours, the data returns from the buoys operating in the Bay of Bengal and the Arabian Sea were 88% and 95%, respectively. The mean time between failures of the buoys was 1.8 years in the Bay of Bengal and 3.8 years in the Arabian Sea, and the mean time to restore was 90 and 68 days, respectively. The offshore failure events, the technical developments for improving the performance, and the strategies adopted to mitigate the failures are presented in detail. The significance of the technical features incorporated for improving the reliability of the wave measurement buoy subsystems is quantitatively represented through fault tree modeling and simulations based on standards and the field failure data.

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Kibria, Ahmed, Krystel K. Castillo-Villar, and Harry Millwater. "Minimizing the Discrepancy between Simulated and Historical Failures in Turbine Engines: A Simulation-Based Optimization Method." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/813565.

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The reliability modeling of a module in a turbine engine requires knowledge of its failure rate, which can be estimated by identifying statistical distributions describing the percentage of failure per component within the turbine module. The correct definition of the failure statistical behavior per component is highly dependent on the engineer skills and may present significant discrepancies with respect to the historical data. There is no formal methodology to approach this problem and a large number of labor hours are spent trying to reduce the discrepancy by manually adjusting the distribution’s parameters. This paper addresses this problem and provides a simulation-based optimization method for the minimization of the discrepancy between the simulated and the historical percentage of failures for turbine engine components. The proposed methodology optimizes the parameter values of the component’s failure statistical distributions within the component’s likelihood confidence bounds. A complete testing of the proposed method is performed on a turbine engine case study. The method can be considered as a decision-making tool for maintenance, repair, and overhaul companies and will potentially reduce the cost of labor associated to finding the appropriate value of the distribution parameters for each component/failure mode in the model and increase the accuracy in the prediction of the mean time to failures (MTTF).

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Piegdoń, Izabela. "The Use of Statistical Inference in the Water Supply Network Managing Operation Process." Journal of KONBiN 49, no. 4 (2019): 221–44. http://dx.doi.org/10.2478/jok-2019-0084.

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Abstract Based on operational data concerning the dates of failure of the water supply network, a mean time to failure was performed. The calculations were performed for the main network, distribution network and water supply connections. The hypothesis about exponential working time between failures was verified using the Pearson test (χ2). The presented analyses provide an attitude of further analyses related to modelling the work of renovation and repair teams, associated with the selection of their appropriate number, and also to ensure the required level of safety and reliability of water supply to the consumers.

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Pietrucha-Urbanik, Katarzyna, Barbara Tchórzewska-Cieślak, and Mohamed Eid. "Water Network-Failure Data Assessment." Energies 13, no. 11 (2020): 2990. http://dx.doi.org/10.3390/en13112990.

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The water-supply system is one of the basic and most important critical infrastructures. Water supply service disruption (water quality or quantity) may have serious consequences in modern societies. Water supply service is subject to various failure modes. Failure modes are specified by their degradation mechanisms, criticality, occurrence frequency and intensity. These failure modes have a random nature that impacts on the network disruption indicators, such as disruption frequency, network downtime, network repair time and network back-to-service time, i.e., the network resilience. This paper focuses on the water leakage failure mode. The water leakage failure mode assessment considers the unavoidable annual real water losses and the infrastructure leakage index recommended by the International Water Association’s Water Loss Task Force specialist group. Probabilistic statistical modelling was implemented to assess the seasonal index, the failure rates and the expectation value of the “mean time between failures.” The assessment is based on real operational data of the network. Specific attention is paid to the sensitivity of failures to seasonal variations. The presented methodology of the analysis of the water leakage failure mode is extendable to other failure modes and can help in developing new strategies in the management of the water-supply system in normal operation and crisis situations.

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Journal articles on the topic 'Mean time between failure'

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