Forthcoming and Online First Articles

International Journal of Reliability and Safety

International Journal of Reliability and Safety (IJRS)

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International Journal of Reliability and Safety (6 papers in press)

Regular Issues

  • Pre-chamber spark ignition: a reliability analysis of pre-chamber valve functions   Order a copy of this article
    by Faraz Akbar, Sarah Zaki 
    Abstract: A pre-chamber ignition allows spark-ignition engines to operate in lean air-fuel settings. It improves fuel efficiency and reduces emissions. In this study, a reliability analysis of a single GE Jenbacher J620 natural gas engine was done. It was operational on continuous load in the power generation sector in Karachi, Pakistan. A bathtub curve of the GE J620 pre-chamber gas valve (PCV) was generated. The three-year industrial data comprised PCV failures that occurred between two overhauls. During infant mortality, the curve revealed 7 failures during 1000 hours. This decreased to a failure for the next two cycles of thousand hours each. There was a 40% decrease in reliability after 1500 hours. Exponential distribution revealed that the mean time-to-failure (MTTF) was 545.5 hours. This study was the first of its kind in the facility. Previously, much time was lost in breakdown maintenance. Thus, it helped to increase the systems reliability.
    Keywords: bathtub curve; exponential distribution; failure rate; fuel injection; gas engine; pre-chamber combustion; pre-chamber spark ignition; pre-chamber valve; probability density function; reliability.

  • A comparative study of M5P, ANN, and RENB models for prediction of vulnerable road accident frequency   Order a copy of this article
    by Saurabh Jaglan, Praveen Aggarwal, Sunita Kumari 
    Abstract: The present investigation aims to evaluate the performance of different models to calculate the vulnerable road user accident frequency (VRUAF). Nine different road stretches were chosen to measure the road geometry and other similar characteristics. Field studies were conducted to gather information about road geometry, traffic surveys, and accident characteristics. A total 17 number of input parameters were collected for accident frequency analysis, and three prediction approaches were applied: Fixed/Random Effect Negative Binomial (FENB/RENB) regression models, Artificial Neural Network (ANN), and M5P model tree. The variation in models' performance was observed in terms of the coefficient of correlation (0.943-0.981), root mean square error (2.274-1.655), and mean absolute error (1.746-1.351). The result suggests that the ANN model is the most accurate model where values of CC, MAE, and RMSE vary from 0.981,1.351 and 1.655, respectively. Thus, this model can predict VRUAF without accident data under similar geometric conditions synthetically.
    Keywords: vulnerable road user; accident frequency; artificial neural network; random effect negative binomial model; M5P model tree.
    DOI: 10.1504/IJRS.2024.10061554
  • A study on step stress partially accelerated life test under adaptive type-II progressive hybrid censoring for inverse Lomax distribution   Order a copy of this article
    by Intekhab Alam, Mustafa Kamal, Ahmadur Rahman, Nayabuddin 
    Abstract: Using traditional life tests in testing and reliability theory may result in extremely few failures by the completion of the experiment, leading to poorer estimations. To get the required failure as rapidly as possible for better estimation, products are exposed to higher stress levels, and this process is known as accelerated life testing. This paper develops a step stress partially accelerated life test that employs adaptive type-II progressive hybrid censoring scheme and assumes that the lifespan of test items follows a two-parameter inverted Lomax distribution. The likelihood and log-likelihood functions were created for adaptive type-II progressive hybrid censoring scheme data in order to get the point and interval of the model parameters using the maximum-likelihood estimation approach. Furthermore, using a Monte Carlo simulation analysis, the biases and mean square errors of the maximum-likelihood estimators are estimated to examine their performances in the presence of censoring introduced in this work.
    Keywords: partially accelerated life test; inverse Lomax distribution; Newton Raphson; adaptive type-II progressive hybrid censoring; simulation study.
    DOI: 10.1504/IJRS.2024.10062067
  • Performance analysis of client-server distributed system using Gumbel-Hougaard family Copula   Order a copy of this article
    by Ibrahim Yusuf, Abdullahi Sanusi, Alhassan Ibrahim 
    Abstract: The current paper compares the performance of two distinct client-server distributed system architectures using the capabilities of the Gumbel-Hougaard Family Copula. Using the Gumbel-Hougaard Family Copula, this paper presents a comprehensive comparative analysis of the performance of two distinct client-server distributed system architectures. The first architecture consists of three identical clients, a load balancer and three identical servers, whereas the second employs a three-component warm standby system with imperfect switching. The failure and repair patterns in both systems are exponential. The analysis entails using supplementary variable technique and Laplace transforms to solve first-order differential equations derived from transition diagrams for each system. While failures are distributed exponentially, repair times are represented by the versatile Gumbel-Hougaard Family Copula and a general distribution. The study considers various parametric values to evaluate various reliability metrics such as system availability, system reliability, Mean Time To Failure (MTTF), MTTF sensitivity and cost function. The findings are presented in the form of tables and figures, which provide a clear visual representation of the obtained insights.
    Keywords: architecture; client-server; distributed system; Gumbel-Hougaard; performance; reliability.
    DOI: 10.1504/IJRS.2023.10061478
  • Recent advances in structural health monitoring: techniques, applications and future directions   Order a copy of this article
    by Najmadeen Mohammed Saeed 
    Abstract: Structural Health Monitoring (SHM) ensures structure safety, reliability, and durability in many sectors. SHM methods have improved structural evaluation and maintenance efficiency to meet sustainable infrastructure and lower maintenance expenses. This article discusses current SHM achievements, their benefits, and future research in this rapidly growing field. Basic SHM procedures start with manual monitoring and visual inspections. Advanced sensors, data analytics and machine learning algorithms have transformed SHM. Industrial, aerospace, energy and civil infrastructure use SHM. SHM optimises processes and quality control, improving product reliability and waste reduction. It covers smart materials, low-cost, lightweight, energy-efficient sensor technologies and advanced data analytics for better decision-making. Advanced sensors, data analytics and machine learning algorithms enable real-time monitoring, anomaly detection and preventative maintenance using SHM. Advanced sensor technologies and SHM integration with cutting-edge technology will shape this industry and improve SHM and maintenance.
    Keywords: SHM; structural health monitoring; sensor; data analytics; machine learning; durability; safety; maintenance; reliability.
    DOI: 10.1504/IJRS.2023.10061436
  • Growth model for detection and removal of faults having different severity with single change point and imperfect debugging   Order a copy of this article
    by Asheesh Tiwari, Ashish Sharma 
    Abstract: Throughout the last decades, researchers have modelled a variety of software reliability growth models for estimating measures of reliability. In the present paper, we have classied faults into four divergent types as per their easiness and hardness in detection and removal. Also, variations in fault detection and correction rates can be because of the testing strategy, changing testing environment, motivation, proficiency and organisation of the debugging and testing teams, etc. In the present paper, a change point has been applied to four types of faults along with imperfect debugging during the correction of faults. This paper comprises two proposed software reliability growth models, which are compared on the basis of rate of detection as well as correction. All the model parameters are evaluated by the method of least squares. These models are assessed using various comparison measures like SSE, MSE, RMSE, Bias, variance and RMSPE.
    Keywords: software reliability; software reliability growth model; change point; fault detection process; non-homogeneous Poisson process; sum of squared error; mean squared error; root mean square error; root mean square prediction error.
    DOI: 10.1504/IJRS.2023.10061631