Template-Type: ReDIF-Article 1.0 Author-Name: Ajay Kumar Author-X-Name-First: Ajay Author-X-Name-Last: Kumar Author-Name: Devender Singh Punia Author-X-Name-First: Devender Singh Author-X-Name-Last: Punia Title: Availability optimisation and selection of performance parameters of complex repairable system using PSO Abstract: This research paper presents a numerical technique for the computation of availability and reliability metrics as well as the Mean Time Between Failures (MTBF), pertaining to a thread rolling machine. Seven repaired sub-systems are studied under this system, namely: motor, hopper feeder, fixed die block, movable die block, drive belt, coolant and lubricant unit, and control panel are arranged in order. The performance of system considered is analysed based on the Markov approach and assumes that the Failure and Repair Rate (FRR) of each sub-system follows a normal distribution. The decision support system is developed for achieving the maximum availability of system. The comparison between particle swarm optimisation and the Markov process is done to achieve optimum availability. The results are compared with other optimisation approaches and the optimised availability using PSO is calculated as 96.24% while it is 95.08% using the Markov method. The particle swarm optimisation algorithm sustains a wide range of different component performance indicators for optimising system availability goals as well as various performance parameters. Journal: Int. J. of Reliability and Safety Pages: 60-82 Issue: 1 Volume: 19 Year: 2025 Keywords: availability; SSA; steady state analysis; particle swarm optimisation; reliability; TSA; transient state analysis; MTBF; mean time between failure; FRR; failure and repair rates. File-URL: http://www.inderscience.com/link.php?id=143763 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:1:p:60-82 Template-Type: ReDIF-Article 1.0 Author-Name: Hui Hui Tay Author-X-Name-First: Hui Hui Author-X-Name-Last: Tay Title: Key factors of near miss reporting behaviour at work and the interaction of safety climate: a review based on reciprocal safety model Abstract: Near misses share with safety accidents their origin but with no or reduced impact, thus providing organisations with the prediction of workplace accidents without experiencing actual cost and harmful consequences. Despite the effort to make near miss reporting a mandatory requirement, the issue of near miss under-reporting remains. Extant literature examines the key factors of near miss reporting behaviour as independent determinants, without considering the interaction of these factors and, more importantly, the interaction of the reporting behaviour and the safety climate at work. In the reciprocal safety culture model, safety behaviour is found to reciprocate with personal and organisational factors. This paper examines the key factors of near miss reporting and its interaction with safety climate through study review, and discusses the reciprocal relationship of near miss reporting behaviour. The study findings will serve as reference for safety researchers and practitioners for effective near miss management system and training development. Journal: Int. J. of Reliability and Safety Pages: 1-21 Issue: 1 Volume: 19 Year: 2025 Keywords: near miss reporting; near miss management; workplace accidents prevention; safety behaviour; reciprocal safety culture; organisational safety climate; psychological safety climate. File-URL: http://www.inderscience.com/link.php?id=143765 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:1:p:1-21 Template-Type: ReDIF-Article 1.0 Author-Name: Mansooreh Moeini Korbekandi Author-X-Name-First: Mansooreh Moeini Author-X-Name-Last: Korbekandi Author-Name: Seyed Hosein Kazemi Author-X-Name-First: Seyed Hosein Author-X-Name-Last: Kazemi Author-Name: Hassan Danaeefard Author-X-Name-First: Hassan Author-X-Name-Last: Danaeefard Title: Enhancing organisational reliability in public organisations: evidence from Iran Abstract: This qualitative study examines methods for improving organisational reliability in Iranian public organisations. Sixteen (16) managers and experts from six (6) crisis-prone public agencies participated in the research, and a purposive sampling method was employed. Thematic analysis was used to analyse the collected data. The study's findings suggest that developing the soft dimensions of organisational reliability, such as cultivating human resources capabilities (including cognitive-psychological capabilities, attitudinal-behavioural capabilities), organisational capabilities (including planning capability, organising and coordinating capability, decision-making and delegation capability, preventive and supervisory capability), knowledge capabilities (including cultural capability, interactive-communicative capability, capability to learn, capability to innovate) and human resources management capabilities (including capability to attract, employ and retain human resources, evaluating and empowering capability), is crucial for enabling organisations to maintain their services during critical situations. The insights gained from this study can be helpful in crisis management in Iranian public organisations. Journal: Int. J. of Reliability and Safety Pages: 83-106 Issue: 1 Volume: 19 Year: 2025 Keywords: organisational reliability; public organisations; qualitative research; crisis management; thematic analysis; soft dimensions. File-URL: http://www.inderscience.com/link.php?id=143772 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:1:p:83-106 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaohong Zhang Author-X-Name-First: Xiaohong Author-X-Name-Last: Zhang Author-Name: Yuxin Li Author-X-Name-First: Yuxin Author-X-Name-Last: Li Author-Name: Jianfei Zhang Author-X-Name-First: Jianfei Author-X-Name-Last: Zhang Author-Name: Jie Gan Author-X-Name-First: Jie Author-X-Name-Last: Gan Author-Name: Yongfei Zhang Author-X-Name-First: Yongfei Author-X-Name-Last: Zhang Author-Name: Juan Shen Author-X-Name-First: Juan Author-X-Name-Last: Shen Title: Joint sequential decision of maintenance and spare parts inventory for multi-unit repairable systems Abstract: Joint decision-making for preventive maintenance and spare parts inventory in multi-component systems is crucial for industrial applications, especially as many expensive, complex equipments can be repaired and reused. This study investigates this joint decision-making using a discrete multi-state degradation model, focusing on the unique characteristics of repairable systems, including their structure and maintenance strategies. First, the operational interactions among production, maintenance, and inventory are analysed to derive state transition probability models for degradation and ordering processes. Subsequently, a sequential decision model is developed to minimise the total system cost, identifying preventive maintenance thresholds, inspection periods, and order batch sequences. To address the problem, a combination of global dynamic programming and genetic algorithms is employed. Numerical experiments with wind turbine spindles validate the decision model, demonstrating its effectiveness in addressing maintenance and inventory optimisation in repairable multi-unit systems while ensuring an optimal dynamic combination of decision variables. Journal: Int. J. of Reliability and Safety Pages: 22-59 Issue: 1 Volume: 19 Year: 2025 Keywords: multi-unit repairable system; discrete multi-state degradation; imperfect maintenance; spare parts inventory; sequential decision; joint optimisation. File-URL: http://www.inderscience.com/link.php?id=143779 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:1:p:22-59 Template-Type: ReDIF-Article 1.0 Author-Name: Jorawar Bura Author-X-Name-First: Jorawar Author-X-Name-Last: Bura Author-Name: M.S. Kadyan Author-X-Name-First: M.S. Author-X-Name-Last: Kadyan Author-Name: Jitender Kumar Author-X-Name-First: Jitender Author-X-Name-Last: Kumar Title: A novel approach based on triangular pendant hesitant fuzzy set for RAM analysis of repairable systems 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 (<em>λ</em>) and repair rate (<em>μ</em>). Thereafter, fuzzy expressions based on TPHFNs are developed for the <em>λ</em> and <em>μ</em> 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. Journal: Int. J. of Reliability and Safety Pages: 132-156 Issue: 2 Volume: 19 Year: 2025 Keywords: triangular pendant hesitant fuzzy numbers; reliability block diagram; reliability; availability; maintainability; RAM-index. File-URL: http://www.inderscience.com/link.php?id=145521 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:2:p:132-156 Template-Type: ReDIF-Article 1.0 Author-Name: Dheyaa A. Khudhur Author-X-Name-First: Dheyaa A. Author-X-Name-Last: Khudhur Author-Name: Tuan Amran Tuan Abdullah Author-X-Name-First: Tuan Amran Tuan Author-X-Name-Last: Abdullah Author-Name: Norafneeza Norazahar Author-X-Name-First: Norafneeza Author-X-Name-Last: Norazahar Title: Risk analysis using object-oriented Bayesian network: a case study of ammonia leakage of refrigeration system 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. Journal: Int. J. of Reliability and Safety Pages: 107-131 Issue: 2 Volume: 19 Year: 2025 Keywords: ammonia; Bayesian network; object-oriented Bayesian network; refrigeration; risk assessment. File-URL: http://www.inderscience.com/link.php?id=145522 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:2:p:107-131 Template-Type: ReDIF-Article 1.0 Author-Name: Huiying Dong Author-X-Name-First: Huiying Author-X-Name-Last: Dong Author-Name: Kun Yan Author-X-Name-First: Kun Author-X-Name-Last: Yan Author-Name: Bo Wu Author-X-Name-First: Bo Author-X-Name-Last: Wu Title: Fault diagnosis model of MMC high-frequency oscillation electromechanical equipment based on adaptive fruit fly optimisation algorithm 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. Journal: Int. J. of Reliability and Safety Pages: 157-173 Issue: 2 Volume: 19 Year: 2025 Keywords: electromechanical equipment; fault diagnosis; MMC; BPNN; AFOA. File-URL: http://www.inderscience.com/link.php?id=145523 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:2:p:157-173 Template-Type: ReDIF-Article 1.0 Author-Name: Jaya Bhadauria Author-X-Name-First: Jaya Author-X-Name-Last: Bhadauria Author-Name: Deepak Kumar Author-X-Name-First: Deepak Author-X-Name-Last: Kumar Title: System reliability estimation based on fuzzy Weibull distribution incorporating hexagonal fuzzy number 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 <em>k</em>-out-of-<em>n</em>: 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. Journal: Int. J. of Reliability and Safety Pages: 174-197 Issue: 2 Volume: 19 Year: 2025 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. File-URL: http://www.inderscience.com/link.php?id=145527 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:2:p:174-197 Template-Type: ReDIF-Article 1.0 Author-Name: Parveen Sihmar Author-X-Name-First: Parveen Author-X-Name-Last: Sihmar Author-Name: Vikas Modgil Author-X-Name-First: Vikas Author-X-Name-Last: Modgil Title: Performance modelling and availability analysis of the boiler furnace system in thermal power plant 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. Journal: Int. J. of Reliability and Safety Pages: 198-212 Issue: 2 Volume: 19 Year: 2025 Keywords: availability analysis; Markov-based simulation; performance modelling; boiler furnace system. File-URL: http://www.inderscience.com/link.php?id=145528 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:2:p:198-212 Template-Type: ReDIF-Article 1.0 Author-Name: Walid Jebrane Author-X-Name-First: Walid Author-X-Name-Last: Jebrane Author-Name: Nabil El Akchioui Author-X-Name-First: Nabil El Author-X-Name-Last: Akchioui Title: Adaptive navigation of mobile robots: synergising attractor dynamics and DDPG reinforcement learning for safe dynamic obstacle avoidance 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 utilises 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. Journal: Int. J. of Reliability and Safety Pages: 244-266 Issue: 3 Volume: 19 Year: 2025 Keywords: deep deterministic policy gradient; attractor dynamics approach; robot navigation; obstacle avoidance; deep reinforcement learning. File-URL: http://www.inderscience.com/link.php?id=147324 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:3:p:244-266 Template-Type: ReDIF-Article 1.0 Author-Name: Sushma Kamlu Author-X-Name-First: Sushma Author-X-Name-Last: Kamlu Author-Name: V. Laxmi Author-X-Name-First: V. Author-X-Name-Last: Laxmi Title: Recital appraisal based on fuzzy reliability for maintenance scheduling of transportation system Abstract: Maintenance is a routine and recurring process of observing a meticulous system in its customary service condition to deliver its predictable performance without any time delay. It also encompasses restraining the downtime of certain equipment as the catastrophe of a component causes service failure. The reliability of a transportation system can be improved by a better maintenance approach, consequently increasing its availability. The physical need for any system can be described through an upgraded information system. It encompasses the failure history; hours spent on maintenance and operating performance of the vehicle, which are monitored over time. In this work, the fuzzy model has been designed to obtain the fuzzy mean time to failure/repair values. The entire process has been carried out on the basis of expert knowledge for optimisation of safety and reliability assessments. This information can be used to make an in-time decision, prolong the life of the equipment, or amend inclusive vehicle reliability. The overall reliability of the transportation system has been appraised based on the reliability of individual vehicles. Journal: Int. J. of Reliability and Safety Pages: 267-281 Issue: 3 Volume: 19 Year: 2025 Keywords: fuzzy reliability; MMTF; maintenance mean time failure; MTTR; mean time to repair; recital appraisal; transportation system. File-URL: http://www.inderscience.com/link.php?id=147326 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:3:p:267-281 Template-Type: ReDIF-Article 1.0 Author-Name: Salman Khursheed Author-X-Name-First: Salman Author-X-Name-Last: Khursheed Author-Name: Sanika Upasani Author-X-Name-First: Sanika Author-X-Name-Last: Upasani Author-Name: Virendra Kumar Paul Author-X-Name-First: Virendra Kumar Author-X-Name-Last: Paul Title: Risk assessment model for the pre-construction phase of redevelopment housing projects Abstract: This research presents a comprehensive framework to address the multifaceted risks associated with government-led housing redevelopment projects in Delhi, India. By employing a rigorous methodology involving literature review, stakeholder engagement and statistical analysis, the study identifies and prioritises critical pre-construction risks such as regulatory hurdles, community displacement and financial constraints using both the Risk Priority Number (RPN) and Analytic Hierarchy Process (AHP) methodologies. The developed risk assessment model integrates case study findings and stakeholder preferences to provide a holistic understanding of project vulnerabilities. The research proposes effective mitigation strategies informed by best practices and expert consultations, with a focus on preventative measures and rapid response capabilities. The study's findings offer valuable insights for policymakers, urban planners and project managers, contributing to the successful implementation of resilient and sustainable redevelopment projects in Delhi. Key recommendations include early and continuous stakeholder engagement, rigorous adherence to legal and regulatory requirements, flexible planning approaches and comprehensive mitigation plans for identified risks. Journal: Int. J. of Reliability and Safety Pages: 282-306 Issue: 3 Volume: 19 Year: 2025 Keywords: public housing redevelopment projects; risk identification and quantification; risk analysis; risk assessment model; risk matrix; AHP; analytic hierarchical process. File-URL: http://www.inderscience.com/link.php?id=147328 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:3:p:282-306 Template-Type: ReDIF-Article 1.0 Author-Name: Ajay Kumar Author-X-Name-First: Ajay Author-X-Name-Last: Kumar Author-Name: Devender Singh Punia Author-X-Name-First: Devender Singh Author-X-Name-Last: Punia Title: Modelling and availability optimisation of zinc plating process by using particle swarm optimisation Abstract: The main aim of this paper is to increase the productivity and reduce the maintenance cost of systems in process industries. Markov modelling is used for mathematical modelling, and steady state as well as transition state availability of various subsystems is analysed for finding the critical subsystem in a production process. The zinc plating process within the screw manufacturing industry is considered as a case study for optimising the availability of the system. The considered system comprises repairable subsystems organised in mixed configurations, assuming their performance parameters like failure and repair rates follow exponential distributions. To solve these equations, a numerical method, specifically the Runge-Kutta fourth-order method, is employed and MATLAB software is utilised for numerical computations. To optimise the results, a Particle Swarm Optimisation technique is used for optimising the availability of the system for various performance parameters and the results are helpful for planning the maintenance policy of the plant. Journal: Int. J. of Reliability and Safety Pages: 213-243 Issue: 3 Volume: 19 Year: 2025 Keywords: availability; SSA; steady state analysis; particle swarm optimisation; reliability; TSA; transient state analysis; MTBF; mean time between failure; FRR; failure and repair rates. File-URL: http://www.inderscience.com/link.php?id=147348 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:3:p:213-243 Template-Type: ReDIF-Article 1.0 Author-Name: Alabhya Sharma Author-X-Name-First: Alabhya Author-X-Name-Last: Sharma Author-Name: Shiv Dayal Bharti Author-X-Name-First: Shiv Dayal Author-X-Name-Last: Bharti Author-Name: Mahendra Kumar Shrimali Author-X-Name-First: Mahendra Kumar Author-X-Name-Last: Shrimali Author-Name: Tushar Kanti Datta Author-X-Name-First: Tushar Kanti Author-X-Name-Last: Datta Title: Seismic safety evaluation of dams using a cloud model 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 utilised 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 the normal range, showcasing the effectiveness of the three indicators in assessing dam safety. Journal: Int. J. of Reliability and Safety Pages: 307-324 Issue: 4 Volume: 19 Year: 2025 Keywords: cloud model; dam seismic safety assessment; Koyna dams; a correlation coefficient method; risk assessment. File-URL: http://www.inderscience.com/link.php?id=149313 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:4:p:307-324 Template-Type: ReDIF-Article 1.0 Author-Name: Guozheng Song Author-X-Name-First: Guozheng Author-X-Name-Last: Song Author-Name: Xiaopeng Li Author-X-Name-First: Xiaopeng Author-X-Name-Last: Li Title: Testing scenario generation and selection for autonomous vehicles using an integrated approach based on real-world accident data Abstract: The safety and reliability of Autonomous Vehicles (AVs) are a core concern, which should be validated before application. The critical testing scenarios extracted from historical accidents of AVs can help achieve the efficient safety and reliability testing of AVs. This paper presents an integrated approach that combines a data-driven method with a Bayesian Network (BN). The information including states, states' occurrence likelihoods and quantitative relationships of variables related to scenarios are learned from an AV accident database of California Department of Motor Vehicles (DMV), which is applied to establish a BN. Then, the scenarios are generated and assessed with the BN and a severity matrix. The testing scenarios are selected based on their weighted consequence severity and risk. In this way, this work achieved critical testing scenarios for the Automated Driving Systems (ADSs) and Perception Systems (PSs) of AVs based on the AV accident database. Journal: Int. J. of Reliability and Safety Pages: 356-379 Issue: 4 Volume: 19 Year: 2025 Keywords: autonomous vehicle; Bayesian network; testing scenario generation and selection. File-URL: http://www.inderscience.com/link.php?id=149317 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:4:p:356-379 Template-Type: ReDIF-Article 1.0 Author-Name: Taufiq Ihsan Author-X-Name-First: Taufiq Author-X-Name-Last: Ihsan Author-Name: Vioni Derosya Author-X-Name-First: Vioni Author-X-Name-Last: Derosya Title: Fatigue in the Indonesian palm oil industry: a critical review Abstract: The palm oil industry in Indonesia is a major contributor to global oil and fat production, employing millions of workers. Despite its vast workforce, there is a significant lack of information regarding worker fatigue. This review highlights critical fatigue-related issues in Indonesian palm oil plantations. We conducted a comprehensive literature review, gathering publications addressing fatigue risk factors, short-term and long-term health and safety consequences, and various fatigue mitigation strategies. Working in oil palm plantations exposes individuals to multiple fatigue-inducing factors. These factors not only lead to immediate effects like reduced cognitive function and accidents but also contribute to chronic illnesses through autonomic, immunological and metabolic pathways. Given the frequency and severity of worker fatigue, it is crucial to evaluate the effectiveness of existing legislation and industry practices while optimising working, living and sleeping conditions. Considering the current workplace conditions, a thorough assessment of potential preventive measures, including fatigue prediction tools and personalised fatigue management systems, is recommended. Journal: Int. J. of Reliability and Safety Pages: 380-393 Issue: 4 Volume: 19 Year: 2025 Keywords: mitigation strategies; palm oil; risk factors; worker fatigue. File-URL: http://www.inderscience.com/link.php?id=149320 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:4:p:380-393 Template-Type: ReDIF-Article 1.0 Author-Name: Kaikai Wang Author-X-Name-First: Kaikai Author-X-Name-Last: Wang Author-Name: Ruiliang Yang Author-X-Name-First: Ruiliang Author-X-Name-Last: Yang Author-Name: Libin Yang Author-X-Name-First: Libin Author-X-Name-Last: Yang Title: Improving the accuracy of drowning detection based on improved YOLOv5 Abstract: Drowning stands as a primary cause of unintentional deaths globally. This paper presents an improved YOLOv5 algorithm tailored for drowning detection, aiming to effectively mitigate drowning incidents. The improved YOLOv5 incorporates the Ghost-CBAM-C3 (GCC) module, which comprises Ghost-bottleneck modules and the CBAM module, and the learning rate decay of Cosine Annealing. To gauge the algorithm's efficacy, four self-made data sets were curated utilising a DJI mini3pro drone over both swimming pools and natural water bodies. Experimental findings underscore the heightened performance of the improved YOLOv5 over the original YOLOv5s. This enhancement manifests in a precision boost from 92.8 to 97.1%, and the values for mean average precision (mAP@0.5), weights and the Frames-Per-Second (FPS) are 93.2, 14.1 and 23.70, respectively, affirming its applicability in real-time scenarios. Furthermore, results indicate superior performance of the swimming pool data set compared to those from natural water bodies. Journal: Int. J. of Reliability and Safety Pages: 339-355 Issue: 4 Volume: 19 Year: 2025 Keywords: drowning detection; improved YOLOv5; self-made data sets; CBAM; safety; drone; labelImg software; k-means; SPPF; Ghost module. File-URL: http://www.inderscience.com/link.php?id=149321 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:4:p:339-355 Template-Type: ReDIF-Article 1.0 Author-Name: Ho Y. Hiep Author-X-Name-First: Ho Y. Author-X-Name-Last: Hiep Author-Name: Nguyen Ngoc Hien Author-X-Name-First: Nguyen Ngoc Author-X-Name-Last: Hien Title: Examining the antecedents of deep safety compliance and surface safety compliance: an expanding of technology acceptance model Abstract: This study examines the antecedents of deep safety compliance and surface safety compliance among garment and footwear workers in Vietnam. The study expands on the technology acceptance model by incorporating social cognitive theory to investigate the influence of participative management and co-worker support on perceived usefulness, perceived ease of use and self-efficacy, ultimately impacting deep safety compliance and surface safety compliance. Data from a survey of 549 workers in five garment and footwear enterprises in Vietnam was analysed using partial least squares structural equation modelling. Findings revealed that both participative management and co-worker support significantly enhance perceived usefulness, perceived ease of use of safety procedures and worker self-efficacy. These perceptions, in turn, positively influence deep safety compliance and negatively impact surface safety compliance. This research adds a novel finding to the technology acceptance model by demonstrating the significant influence of participative management and co-worker support on safety compliance, expanding its applicability in the safety domain. Other literature contributions and practical implications for enhancing workplace safety are also discussed. Journal: Int. J. of Reliability and Safety Pages: 394-416 Issue: 4 Volume: 19 Year: 2025 Keywords: deep safety compliance; surface safety compliance; self-efficacy; participative management; co-worker support. File-URL: http://www.inderscience.com/link.php?id=149323 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:4:p:394-416 Template-Type: ReDIF-Article 1.0 Author-Name: M. Architha Author-X-Name-First: M. Author-X-Name-Last: Architha Author-Name: Parameshwar V. Pandit Author-X-Name-First: Parameshwar V. Author-X-Name-Last: Pandit Title: Estimation of conditional stress strength reliability using ranked set sampling: exponential case Abstract: This study focuses on estimating conditional stress strength reliability of a system using ranked set sampling, when stress and strength variables follow independent exponential distributions. Two estimation methods are used, namely Maximum Likelihood Estimation (MLE) and bootstrap estimation. The asymptotic confidence interval is constructed based on a maximum likelihood estimator and the Boot-P confidence interval is constructed. A simulation study is carried out to determine the Mean Square Error (MSE) and length of the confidence interval. This study uses MSE and the length of the confidence interval to compare the estimator based on ranked set sampling to that based on simple random sampling in the context of exponential distribution. Journal: Int. J. of Reliability and Safety Pages: 325-338 Issue: 4 Volume: 19 Year: 2025 Keywords: exponential distribution; simple random sampling; ranked set sampling; stress-strength model; conditional stress-strength model; maximum likelihood estimator; bootstrap estimation; confidence interval. File-URL: http://www.inderscience.com/link.php?id=149324 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijrsaf:v:19:y:2025:i:4:p:325-338