International Journal of Reliability and Safety (6 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