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.
  
  
• Adaptive navigation of mobile robots: synergising attractor dynamics and DDPG reinforcement learning for safe dynamic obstacle avoidance  
  by Walid Jebrane, El Akchioui Nabil 
  Abstract: Robot navigation in complex and dynamic environments remains a challenging problem, requiring methods that can efficiently adapt to unforeseen obstacles and goal-oriented tasks. This paper presents a novel approach that combines the biologically-inspired Attractor Dynamics Approach with the Deep Deterministic Policy Gradient (DDPG) algorithm to enable a mobile robot, specifically the e-puck robot, to navigate through cluttered spaces while avoiding collisions with moving obstacles effectively. The Attractor Dynamics Approach utilizes attractors as goals and repulsive forces to avoid obstacles, offering robust and goal-oriented navigation even with very low-level sensory information. In parallel, the DDPG-based reinforcement learning component fine-tunes the robot's motion controls based on range sensor readings, ensuring precise and adaptive obstacle avoidance. The integration of these two techniques empowers the robot to autonomously explore its environment, dynamically adjust its trajectory, and reach predefined targets successfully and safely.
  Keywords: deep deterministic policy gradient; attractor dynamics approach; robot navigation; obstacle avoidance; deep reinforcement learning.
  DOI: 10.1504/IJRS.2024.10068880
   
  
• Recital appraisal based on fuzzy reliability for maintenance scheduling of transportation system  
  by Sushma Kamlu, Vijaya Laxmi 
  Abstract: Maintenance is a routine and recurring process of observing a meticulous system in its customary service condition to deliver its predictable performance with no time delay. Maintenance encompasses restraining the downtime of certain equipment as the catastrophe of a component causes service failure. The reliability of a transportation system can be enhanced through a better maintenance approach, enhancing the system's availability. The upgraded information system encompasses the failure history, hours spent on maintenance, and operating performance of the vehicle monitored. The work presents the fuzzy model designed to get the fuzzy meantime for failure/repair values. The complete process was carried out using professional knowledge to optimize safety and reliability assessments. This data can be used to make an immediate decision, extend the life of equipment, or improve overall vehicle reliability. The overall reliability of the transportation system has been appraised based on the reliability of individual vehicles.
  Keywords: fuzzy reliability; maintenance mean time failure; mean time to repair; recital appraisal; transportation system.
  DOI: 10.1504/IJRS.2024.10068946
   
  
• Risk assessment model for the pre-construction phase of redevelopment housing projects  
  by Salman Khursheed, Sanika Upasani, Virendra Kumar Paul 
  Abstract: This paper explores the complexities of government-led housing redevelopment in Delhi, India, with a focus on risk assessment and mitigation strategies. It identifies pre-construction risks such as regulatory hurdles and community displacement, aiming to enhance project resilience. The research employs a multi-stage methodology: data collection through literature review and stakeholder surveys, risk identification via workshops and expert interviews, and risk prioritization using statistical analysis and Multi-Criteria Decision Analysis (MCDA). A comprehensive risk assessment model is developed, integrating case study findings and stakeholder preferences. Mitigation strategies are refined through best practice reviews and expert consultations, with impact quantified through scenario analysis. An expert panel validates the methodology and findings, ensuring robustness. By identifying challenges, analyzing risks, and proposing mitigation measures, this study provides valuable insights for policymakers, urban planners, and project managers, enhancing the resilience and success of redevelopment projects in Delhi.
  Keywords: public housing redevelopment projects; risk identification and quantification; risk analysis; risk assessment model; risk matrix; analytic hierarchical process.
  DOI: 10.1504/IJRS.2024.10069100
   
  
• Seismic safety evaluation of dam using cloud model  
  by Alabhya Sharma, Shiv Dayal Bharti, Mahendra Kumar Shrimali, Tushar Kanti Datta 
  Abstract: For the preliminary estimate of the seismic safety of the dam, expert opinions are often relied upon. However, expert opinions, when expressed linguistically, are associated with uncertainty and fuzziness. To address this inadequacy, cloud models have been utilized in numerous studies. In the present investigation, a cloud model is employed to predict the seismic safety of a concrete gravity dam. Experts evaluate seismic safety factors of dams, focusing on seismic damage potential, hazard, and structural strength. Each factor has key sub-indicators rated on a five-point scale. Through qualitative-to-quantitative conversion, cloud points are generated for analysis. The coefficient of variation method identifies sub-indicator influences on each factor. Comparing these cloud models to standard ones visually depicts dam safety. Illustrated with Koyna dam, this approach reveals its seismic safety below normal range, showcasing the effectiveness of the three indicators in assessing dam safety.
  Keywords: cloud model; dam seismic safety assessment; Koyna dam; correlation coefficient method; risk assessment.
  DOI: 10.1504/IJRS.2025.10069925
   
  
• Modelling and availability optimisation of zinc plating process by using particle swarm optimisation  
  by Ajay Kumar, Devender Singh Punia 
  Abstract: The main aim of this paper is to increase the productivity and reducing the maintenance cost of system of process industry. The Markov modelling is used for mathematical modelling and steady state as well as transition state availability of various subsystem is analysed for finding the critical subsystem in production process. The Zinc plating process within the screw manufacturing industry is considered as a case study for optimized the availability of system. The considered system comprises of repairable subsystem organized in mixed configurations assuming their performance parameters like failure and repair rates follows exponential distributions. To solve these equations, a numerical method, specifically the Runge-Kutta fourth-order method, is employed and MATLAB software is utilized for numerical computations. To optimize the results, a Particle Swarm Optimization technique is used for optimizing the availability of system for various performance parameters and the results are helpful for planning the maintenance policy of plant.
  Keywords: availability; SSA; steady state analysis; particle swarm optimisation; reliability; TSA; transient state analysis; MTBF; mean time between failure; FRR; failure & repair rates.
  DOI: 10.1504/IJRS.2024.10070101
   
  
• Risk analysis using object-oriented Bayesian network: a case study of ammonia leakage of refrigeration system  
  by Dheyaa A. Khudhur, Tuan Amran Tuan Abdullah, Norafneeza Norazahar 
  Abstract: The increasing complexity of refrigeration systems has introduced major concerns into industrial safety and assets. This paper aims to develop a risk analysis framework for an ammonia refrigeration system using Object-Oriented Bayesian Network (OOBN). The failure causes of ammonia leakage are identified through a historical review of past accidents over a ten-year period and the Fault Tree (FT) is then constructed. Failure probabilities are quantified using objective data sources (plant-specific accident records) for known failure rates and subjective data sources (expert judgments and fuzzy set theory) for uncertain ones. The OOBN model is employed to analyse and evaluate the leakage risk. The results revealed that valve seal failures and flange breakages are critical factors in ammonia leakage, necessitating top priority in risk management. Moreover, the developed framework provides the decision-makers a robust tool for implementing safety measures to prevent and mitigate ammonia leakage incidents effectively.
  Keywords: ammonia; Bayesian network; object-oriented Bayesian network; refrigeration; risk assessment.
  DOI: 10.1504/IJRS.2024.10068389
   
  
• A novel approach based on triangular pendant hesitant fuzzy set for RAM analysis of repairable systems  
  by Jorawar Bura, M.S. Kadyan, Jitender Kumar 
  Abstract: The current study presents a new approach based on Triangular Pendant Hesitant Fuzzy Set (TPHFS) for Reliability, Availability and Maintainability (RAM) analysis of repairable systems. For this purpose, the definition of TPHFS and the arithmetic operations between two triangular pendant hesitant fuzzy numbers (TPHFNs) are introduced. The proposed approach is divided into two phases. In the first phase, TPHFNs are used to identify and represent uncertainties in the data related to components' failure rate (λ) and repair rate (μ). Thereafter, fuzzy expressions based on TPHFNs are developed for the λ and μ of systems connected in series and parallel configurations. In the second phase, reliability, availability and maintainability of repairable systems are obtained for system analysis. Also, to identify the most critical component of the system, a RAM-index based on TPHFNs is developed. For illustration purposes, the turbine generator system of a thermal power plant has been taken.
  Keywords: triangular pendant hesitant fuzzy numbers; reliability block diagram; reliability; availability; maintainability; RAM-index.
  DOI: 10.1504/IJRS.2024.10068360
   
  
• Fault diagnosis model of MMC high-frequency oscillation electromechanical equipment based on adaptive fruit fly optimisation algorithm  
  by Huiying Dong, Kun Yan, Bo Wu 
  Abstract: Electromechanical equipment plays a pivotal role in improving manufacturing efficiency and driving the national economy. However, with the increase of its usage, various failures are more frequent. Efficient diagnostic methods are necessary to enhance equipment operation and reduce time and cost. This study focuses on diagnosing faults in high-frequency oscillation electromechanical equipment, specifically in the Modular Multilevel Converter (MMC). Therefore, a novel fault diagnosis system model is proposed, combining Back Propagation Neural Network (BPNN) with Adaptive Fruit Fly Optimisation Algorithm (AFOA). This model consists of modules for information acquisition, fault monitoring and equipment control. The study utilises the access, aggregation and core layers to establish the overall structural model. Through simulation experiments, the proposed method demonstrated high localisation accuracy (>0.94) and fault diagnosis accuracy (>97%) within 60 minutes. Compared with other algorithms, it exhibits superior accuracy, stability and practical value in electromechanical equipment fault diagnosis.
  Keywords: electromechanical equipment; fault diagnosis; MMC; BPNN; AFOA.
  DOI: 10.1504/IJRS.2024.10068467
   
  
• System reliability estimation based on fuzzy Weibull distribution incorporating hexagonal fuzzy number  
  by Jaya Bhadauria, Deepak Kumar 
  Abstract: In this study, we used fuzzy Weibull distribution in a hexagonal fuzzy environment to assess the fuzzy reliability function, fuzzy hazard function and fuzzy mean time to failure of distinct configurations and systems. Firstly, we evaluated the system reliability, where the lifetime of components is represented by a Weibull distribution with fuzzy parameters in the form of hexagonal fuzzy number and secondly, this research focuses on fuzzy reliability evaluation for linear and circular consecutive k-out-of-n: F systems as well as series and parallel systems. Additionally, numerical examples are also given to show how fuzzy survival function and fuzzy hazard function vary with respect to time along with the tables and graphs. This research also presents a novel approach to determine system reliability by utilising a fuzzy number with six parameters.
  Keywords: fuzzy Weibull distribution; series and parallel configuration; linear and circular consecutive (k-out-of-n: F) system; fuzzy reliability function; fuzzy hazard function; fuzzy mean time to failure.
  DOI: 10.1504/IJRS.2024.10068857
   
  
• Performance modelling and availability analysis of the boiler furnace system in thermal power plant  
  by Parveen Sihmar, Vikas Modgil 
  Abstract: The present study focused on analysing the availability of the boiler furnace system for the thermal power plant with Markov-based simulation. The boiler furnace has a substantial impact on the efficiency of the plant. The system comprises four subsystems: Boiler drum, Superheater, Economiser and Reheater. The study focuses on establishing an inclusive understanding of the boiler furnace system, including its design, operational parameters and historic performance records. In the analysis, many factors affecting availability are considered, such as maintenance practices, equipment failure and operations interruptions. The study quantifies the system's availability which is recorded in matrix tabulation form. The outcomes of the present study reveal that the boiler drum subsystem has the greatest influence on system availability.
  Keywords: availability analysis; Markov-based simulation; performance modelling; boiler furnace system.
  DOI: 10.1504/IJRS.2024.10068917