International Journal of Reliability and Safety (11 papers in press)

Regular Issues

• Pre-chamber spark ignition: a reliability analysis of pre-chamber valve functions  
  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  
  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
   
  
• Research on crack propagation of aircraft engine blades based on multi-physics field coupling and modal frequencies  
  by Junxi Bi, Xinyu Ge, Zenglin Hu, Jinfeng Li, Shaonan Yang, Hongwei Gao, Min Wu 
  Abstract: With the continuous development of the aviation industry, crack propagation in aircraft engine blades has become an undeniable factor affecting aviation safety. In this study, a method based on multi-physics coupling and modal frequencies is proposed to investigate the characteristics and mechanisms of crack propagation in aircraft engine blades. Firstly, a numerical model based on finite element analysis and the extended finite element method (XFEM) is established to describe the multi-physics response and crack propagation behavior of engine blades. Secondly, the proposed numerical model and analysis methods are utilized to conduct in-depth research on the characteristics and mechanisms of crack propagation in aircraft engine blades. Furthermore, modal frequency analysis is introduced to analyze the dynamic response and crack propagation mechanisms of the blades under different modes. Finally, the main achievements and contributions of the study on crack propagation of aircraft engine blades based on multi-physics coupling and modal frequency analysis are summarized, and future research directions are discussed.
  Keywords: engine blades; fatigue crack; natural frequency; fluid-structure coupling.
  DOI: 10.1504/IJRS.2024.10062868
   
  
• Condition-based maintenance plan for multi-state systems using reinforcement learning  
  by Shuyuan Gan, Nooshin Yousefi, David Coit 
  Abstract: In this paper, a dynamic maintenance model is presented for a degrading system. The system uses a critical machine with multiple production states, which are estimated and obtained by some measurable indicators. In the maintenance policy, considering the production state alone might not provide a comprehensive representation of the actual machine condition, both the production state and machine virtual age are taken into account during the maintenance-decision process. The system is inspected at periodic times, and at each inspection, an action is selected from those that are available regarding spare parts and maintenance. The problem is formulated by using a Markov decision process and we solved it by Q-learning algorithm. Numerical examples show how the optimal maintenance actions can be found for a degrading production system considering spares parts ordering and imperfect maintenance. Also, the results indicate that the proposed method is more time-saving and cost-efficient than traditional methods.
  Keywords: dynamic maintenance; Markov decision process; Q-learning; spare parts; virtual age.
  DOI: 10.1504/IJRS.2024.10062882
   
  
• Railway track fault detection using optimised convolution neural network  
  by R. Chitra, Anusha Bamini, Brindha D, Chenthil T.M. Jegan, Stewart Kirubakaran 
  Abstract: Railway accidents are an under-scrutinized cause of death in India Train accidents are caused by various consequences of collisions, derailments, signal errors, and so on Furthermore, when train derailments become disastrous, they can have tremendous repercussions It is difficult to identify the cause of the derailment efficiently within a limited period of time In recent years, we have been making progress to reduce derailments, but even if not deadly, identifying faulty tracks can waste a lot of time and money And doing this error-free is a pressing matter, as tracks always continue to experience wear and tear with more usage Here is where neural networks can pitch in their solution We can train a model to look at train tracks and identify any issues This paper goes into the methodology of achieving this and optimizing a neural network to predict problems in the track with the best possible accuracy.
  Keywords: railway track; neural network; optimization; VGG; Xception; defective; mobilenet; dense; deep learning.
  DOI: 10.1504/IJRS.2024.10063223
   
  
• Influence of safety culture on Chinese oversea hydropower project workers safety performance: a case study in Cameroon  
  by Bouba Oumarou Aboubakar, Hongxia Li 
  Abstract: This paper attempts to evaluate the influence of safety culture on the safety performance of Chinese international hydropower projects in Cameroon. It addresses the intrinsic influence of external hazards management, National culture, workers safety knowledge and attitudes, Chinese managers’ commitment on safety behaviors and motivation using a Structural model analyzed by Lisrel. The data were collected via questionnaires from 566 workers in hydropower projects in Cameroon. The results revealed that (1) External hazards management positively influence safety motivation of both Chinese and local workers, but does not have a significant influence on their safety behaviors;(2)National culture sharing positively influences safety behaviors and safety motivation of workers;(3)It was established that workers safety knowledge slightly positively influences safety behavior but not the safety motivation of workers;(4)Workers safety attitude positively influences safety behaviors;(5)higher safety commitment from Chinese management were associated with higher positive safety behavior and safety motivation of workers. In the end, theoretical as well as useful implications were proposed and suggestions for future work were also given based on the results in this study.
  Keywords: safety culture; safety performance; hydropower projects; structural equation modelling; Chinese contractors.
  DOI: 10.1504/IJRS.2024.10063286
   
  
• An NPV analysis of opportunity-based age replacement model  
  by Jing Wu, Cunhua Qian, Tadashi Dohi, Okamura Hiroyuki 
  Abstract: This paper generalizes the existing opportunity-based age replacement policies by introducing the net present value (NPV) of the expect total costs, where two cases are considered. First, we reformulate two basic opportunity-based age replacement models with replacement first and last disciplines, where the failure time and the arrival time of a replacement opportunity are statistically independent. Next, we take place the NPV analysis for the failure-correlated opportunity-based age replacement models with replacement first and last disciplines. Since the NPV method is useful to estimate more accurate maintenance cost over a long-time planning in an unstable economic environment, we obtain the expected total discounted costs over an infinite time horizon and derive the optimal preventive replacement policies by minimizing them in both cases. Numerical examples with the Farlie-Gumbel-Morgenstern bivariate copula are presented to investigate the dependence of correlation between the failure time and the opportunistic replacement.
  Keywords: net present value; age replacement; opportunity; correlation; bivariate distribution; replacement first; replacement last.
  DOI: 10.1504/IJRS.2024.10063333
   
  
• A study on step stress partially accelerated life test under adaptive type-II progressive hybrid censoring for inverse Lomax distribution  
  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  
  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  
  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  
  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