International Journal of Reliability, Risk and Safety: Theory and Application
Volume:5 Issue: 1, Jun 2022

This paper studies a discrete fix-up limit policy for two systems. Because sometimes, a failed system cannot be completely fixed at the optimal fix-up limit time due to some logistic issues. This paper provides a chance to complete fixing up a failed system within a discrete fix-up limit time LT (L=1,2,3…) for a fixed T. The explicit expression of the expected long-term cost per unit time is derived for the two systems based on the assumptions of the systems. Finally, a numerical example is given to illustrate the theoretical results of the proposed model.

Spare parts provision is a complex problem and requires an accurate model to analyze all factors that may affect the required number of spare parts. The number of spare parts required for an item can be effectively estimated based on its reliability. The reliability characteristics of an item are influenced by different factors such as the operational environment, maintenance policy, operator skill, etc. However, in most reliability-based spare parts provision (RSPP) studies, the effect of these influence factors has not been considered. Hence, the statistical approach selected for reliability performance analysis must be able to handle the effect of these factors. One of the important models for reliability analysis by considering risk factors is the proportional hazard model (PHM), which has received less attention in the field of spare parts provisioning. Thus, this paper aims to demonstrate the application of the available reliability models with covariates in the field of spare part predictions using a case study. The proposed approach was evaluated with data from the system of fleet loading of the Jajarm Bauxite mine in Iran. The outputs represent a significant difference in spare parts forecasting and inventory management when considering covariates.

Wear damage is a common failure in engine bearing shells. Wear failure induces changes in the bearing geometry and affects the oil film pressure and the durability of bearing shells. In this paper, wear failure in journalpin (main) bearings of a reciprocating engine is studied. Using a dynamic model, forces and torques in the journalpin bearings have been calculated and used in the analysis. To calculate the lubricating characteristics of the bearing, such as minimum oil film thickness and maximum oil film pressure, the Elasto-HydroDynamic (EHD) model that incorporate mass conservation algorithms is utilized. Wear failure in journalpin bearings of a reciprocating engine is assessed and the results are presented. Archard’s model is used as a wear model of journalpin-bearing material. The asperity interaction of two rough surfaces is considered by the boundary lubrication model. The results show that the wear rate at the initial stage of engine running is high. The results indicate that the main reason for wear in the journalpin bearings is the applied torque on the bearing, leading to edge wear. In a V-12 or 6Inline engine, journalpin bearing number 4 has the highest amount of torque applied and therefore has the highest amount of wear.

Gas pressure reduction stations play a key role in the timely and safe supply of natural gas (NG) to residential, commercial, and industrial customers. Accordingly, system reliability analysis should be performed to prevent potential failures and establish resilient operations. This research proposed a reliability assessment approach to natural gas pressure-reducing stations using historical data, statistical analysis, and Monte Carlo simulation (MCS). Historical data are employed to establish the probability distributions of the system and subsystems in gas stations. Then the Kolmogorov-Smirnov test is conducted to assess the goodness-of-fit for the developed distributions. Bayesian network (BN) is utilized to develop a system failure causality model. Finally, we performed MCS to precisely predict the failure rate and reliability of stations and all subsystems, such as the regulator, separator and dry gas filters, shut-off valves, and regulator. This research provided numerical findings on the reliability indicators of pressure reduction stations which can be used to improve system performance and, subsequently, the resilience of NG pipelines.

In the use of metals, due to industrial advances and the application of more dynamic loads, it is necessary to pay more attention to the fatigue issue. Structural health monitoring (SHM) system is a method of evaluating and monitoring structural health. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes, improving structural reliability and life cycle management. Non-destructive inspection methods are used to condition and health monitoring structures at the time of production and even during the service life of parts. Among non-destructive methods, the acoustic emission method has become a standard and reliable method in recent years. The stimulated internal energy of the structure is received in this acoustic emission technique as health monitoring features. A dominating attribute of the acoustic emission technique is its application ability in its loading condition. Therefore, it provides instant damage information within a short period of time. Thus, acoustic emission monitoring tests are often performed in the operating conditions of the structure. Acoustic emissions can inform us of the changes that occur before the final failure and prevent much financial and human damage. In this project, the characteristics of acoustic emission in the fatigue crack growth of aluminum alloy 2025 for online structural monitoring have been investigated and determined. Acoustic emission tests have been performed in two parts: bending fatigue test with the aim of initiation of fatigue cracks in aluminum alloy 2025 specimens and following tensile tests with the aim of growth of fatigue cracks. The acoustic emission signals and parameters sent by the acoustic emission sensor during both tests were received and recorded by the acoustic emission software. According to the received acoustic emission information, various diagrams are plotted. Analyzing the results from online acoustic emission monitoring showed the acoustic emission method can be considered a suitable and reliable technique for detecting crack initiation and crack growth in aluminum alloy 2025.

Nowadays, the utilization of software engineering in various areas of technology is remarkably increased. As a matter of fact, it is used in many critical applications such as eye surgery, autopilot systems of airplanes, centralized traffic control (CTC), and so on. Therefore, the reliability of software is very important, and it plays an essential role in the lifetime of the software. Software reliability is one of the main characteristics of software quality. Moreover, the rapid assessment of the reliability of the application is essential during the software life cycle. In this paper, Iuse the neuro-fuzzy methods to assess the software's reliability in order to cope with uncertainties in measuring the actual parameters of the software. By designing neuro-fuzzy inference systems and applying four parameters of the ISO/IEC 9126quality model(i.e., the maturity of software, fault-tolerant, recoverability, and reliability compliance) and finding the parameters of a fuzzy system by exploiting approximation techniques from neural networks, Ipresent an integrated assessment model for evaluation of software reliability. The case study used in this paper to evaluate the proposed method is the software income tax calculator. By applying the input parameters, Iobserve that the software reliability is 0.65. software reliability in our proposed method is more exact than software reliability in the fuzzy multi-criteria and fuzzy method because The weights of the input parameters have been set by experts and software developers, and simulations are carried out using MATLAB tool (ANFIS). Simulations confirm that the proposed method provides acceptable results.

The emergence of accidents in industrial and aerospace environments has increased with the increase of activities in this field and the use of machinery. In traditional systems, after accidents and irreparable damage occur, research is done to investigate the defects and their causes. But today, due to the existence of different methods of hazard identification and risk assessment, before the occurrence of accidents, it is possible to identify accident hotspots and critical areas and to prevent and control them. Reviewing the analysis of failure modes and their effects (FMEA) is one of the industry's common risk assessment methods. Its purpose is to analyze the failure to obtain a comprehensive repair program that leads to the continuation of the operation of physical assets. In this study, with the help of the FMEA method, the risk priority number of the Ilyushin-76 aircraft hydraulic system was calculated, and its critical parts were identified. Due to the shortcomings of the usual risk priority number in the FMEA method, side methods of aggregation of ideas and Schaefer evidence theory were used to calculate the risk priority number. Using these methods, involving probabilities in the expression of opinion, the results of determining critical components became closer to reality. From the results obtained from the study and evaluation of critical components by the two usual RPN methods and Schaefer evidence theory, nine highly critical components are obtained jointly.

Expansion of aviation is not achievable without regulating and improving air safety worldwide. Air safety in aviation has always been associated with approving and implementing national and international laws, regulations and standards. The international aviation community has approved uniform safety regulations under treaties, bilateral agreements, and internationally required standards. The international civil aviation organization (ICAO) is continuously updating standards following the development of aviation technologies. However, implementing international air safety standards involves compliance with and implementation of the regulations by the states in their air transportation. With the adoption and updating of international air standards of ICAO, do the member states comply with them? Member States are not in the same status regarding the development of the aviation industry. Various political, economic, and technical factors impede countries' correct and appropriate implementation of standards. Hence, the member countries should obtain a legal method so that the international technical air standards in their aviation industry become mandatory. However, they should adopt these standards under national law and harmonize them with international air standards. Formulating them under national law is the preferred way to comply with these uniform international safety standards. To accomplish this, the relevant national legal and regulatory infrastructure for air regulations should be established in all states. The author first explains the theoretical and practical basis of developing comprehensive international aviation safety standards and then describes the mechanism and process of approving these standards in the framework of the national code.

Tail risk analysis plays a central strategic role in risk management and focuses on the problem of risk measurement in the tail regions of extreme risks. As one crucial task in tail risk analysis for risk management, the measurement of tail risk variability is less addressed in the literature. Neither the theoretical results nor inference methods are fully developed, which results in the difficulty of modeling implementation. Practitioners are then short of measurement methods to understand and evaluate tail risks, even when they have large amounts of valuable data in hand. In this paper, some nonparametric methods of estimation for the class of variability measures among proportional hazards models based on progressively Type-II censored data are derived. We showed some properties of these estimators. Simulation studies have been performed to see the effectiveness of the proposed methods, and a real data set has been analyzed for illustrative purposes. Some well-known variability measures, such as the Gini mean difference, the Wang right tail deviation and the cumulative residual entropy, are, up to a scale factor, in this class.

Maintenance planning has been widely applied in manufacturing systems to improve production efficiency. In some real cases, job processing times may change over time, but they are mostly assumed to be constant in the scheduling literature. Hence, in this article, a mixed integer model is developed to optimize scheduling jobs on unrelated parallel machines with reliability-based maintenance and job deteriorating effects. The proposed model considers a reliability-based maintenance system and multi-stage quality cost and starts a time-dependent deteriorating effect. Based on the assumptions, if machines work in undesirable conditions, quality reduction and quality cost increment would occur. According to the start time-dependent deteriorating effect, the processing time of each job is a function of its start time. The problem is modeled by an integer linear programming method. Computational experiments are performed on various numerical instances to show the model’s effectiveness.

This paper concerns vibration control and attitude stabilization of a flexible spacecraft with faulty actuators. The PID-based sliding mode fault-tolerant scheme is developed to preserve the system against bounded external disturbances, rigid-flexible body interactions, and partial actuator failures. The proposed control law, which combines the advantages of the PID and SMC, is proposed to enhance the robustness and reduce the steady state errors while reducing complexity and the computational burden and preserving the great properties of the SMC controller. It has been shown that the SMC controller is effective in accommodating different actuator fault scenarios and behaves healthily. Additionally, an active vibration control (AVC) law utilizing a strain rate feedback (SRF) algorithm and piezoelectric (PZT) sensors/actuators is activated during the maneuver to compensate for residual vibrations resulting from attitude dynamics and actuator failures. Numerical simulations demonstrate the proposed schemes' superiority in fault tolerance and robustness compared to conventional approaches.

This paper presents a new competitive approach to provide reliability for distribution system customers. The model is based on the Cournot game and utilizes the Nash equilibrium concept to find the output of the problem. Reliability in the proposed framework is an ancillary service and the customers who participated in the program must pay for reliability provision. The proposed model also considers regulatory concerns of reliability insuring the average reliability of the system is not incurred. Based on the proposed model, customers will compete for their reliability enhancement considering all the constraints related to the network, regulator and each customer. The expected outage time for each customer is considered the reliability index in this paper. The model is investigated in a sample case study and the results show how a customer would behave if they participated in the reliability improvement program of distribution systems. Our results also show that there would exist a high motivation for both parties (utility and customers) to implement the proposed model for the reliability enhancement of the distribution system.