Subsystem Reliability Research Articles

RELIABILITY ANALYSIS OF SWITCH’S CONTROL SCHEMES

Purpose. The purpose of this article is to conduct an analysis of the reliability of the control schemes of the electric arrow drive with the aim of optimizing and modernizing them to increase the reliability indicators. To show an approach to optimizing the control circuits of an electric turnout that is advantageous from an operational point of view, the implementation of fewer control circuits will minimize the number of failures. To demonstrate a principled circuit solution for optimizing the control circuit of an electric turner with the use of separate redundancy with always-on redundancy and integer multiplicity. Methods. During the research, methods of comparative analysis, synthesis, probability theory, and reliability theory were used. Findings. The paper analyzes the types of re-reservation as a way to increase the reliability of the arrow control scheme. A comparative study of the reliability of various options for reserving the turnout control scheme was carried out in comparison with the classic situation on the railways of Ukraine - the absence of a reserve. It has been proven that the use of separate redundancy with always-on reserve and integer multiplicity provides the maximum increase in reliability, but the significant amount of necessary equipment significantly reduces the economic attractiveness of this method. On the other hand, the use of separate redundancy with substitution and fractional multiplicity (sliding redundancy) gives a positive result only if one redundancy unit serves no more than 15 turnout electric drives, otherwise the overall reliability of the subsystem may decrease. The optimization of the arrow control subsystem at the station is proposed, which requires the use of only six arrow control schemes, one of which is a sliding reserve. The influence of different types of redundancy on the reliability indicators of the arrow control scheme is considered. The most effective option for optimizing the arrow control subsystem has been determined. Scientific novelty. The scientific novelty of the work consists in the well-founded sufficiency of using only six arrow control schemes in combination with the use of sliding redundancy of the arrow control scheme for the control of arrows when disbanding warehouses on the sorting slide. The proposed method makes it possible to increase the reliability of the arrow control subsystem while maintaining the operational parameters of the station. Practical significance. The practical significance of the results lies in the fact that when using the proposed optimization, the resource use of hill automation devices is improved, the maintenance process is simplified, and the total cost of equipment and maintenance costs are reduced.

Bayesian estimation of the mean time between failures of subsystems with different causes using interval‐censored system maintenance data

AbstractEnsuring an acceptable level of reliability stands as a primary imperative for any mission‐focused operation since it serves as a critical determinant of success. Inadequate reliability can lead to severe repercussions, including substantial expenses for repairs and replacements, missed opportunities, service disruptions, and in the worst cases, safety violations and human casualties. Within national defense organizations such as the USAF, the precise assessment and maintenance of system reliability play a pivotal role in ensuring the success of mission‐critical operations. In this research, our primary objective is to model the reliability of repairable subsystems within the framework of competing and complementary risks. Subsequently, we construct the overall reliability of the entire repairable system, utilizing day‐to‐day group‐censored maintenance data from two identical aircraft systems. Assuming that the lifetimes of subsystems follow non‐identical exponential distributions, it is theoretically justified that the system reliability can be modeled by homogeneous Poisson processes even though the number of subsystems of any particular type is unknown and the temporal order of multiple subsystem failures within a given time interval is uncertain due to interval censoring. Using the proposed model, we formulate the likelihood function for the mean time between failures of subsystems with different causes, and subsequently establish an inferential procedure for the model parameters. Given a considerable number of parameters to estimate, we explore the efficacy of a Bayesian approach, treating the contractor‐supplied estimates as the hyperparameters of prior distributions. This approach mitigates potential model uncertainty as well as the practical limitation of a frequentist‐based approach. It also facilitates continuous updates of the estimates as new maintenance data become available. Finally, the entire inferential procedures were implemented in Microsoft Excel so that it is easy for any reliability practitioner to use without the need to learn sophisticated programming languages. Thus, this research supports an ongoing, real‐time assessment of the overall mission reliability and helps early detection of any subsystem whose reliability is below the threshold level.

DISCRETE-CONTINUOUS PROCESSES AS THE MATHEMATICAL BASIS OF THE RELIABILITY OF THE BEHAVIOR OF SUBSYSTEMS OF THE "DRIVER-VEHICLE-ROAD-ENVIRONMENT" SYSTEM

The work is devoted to the study of the reliability of the behavior of subsystems of the driver-car-road-environment system. According to the definition of a number of researchers, traffic safety is a complex and system of rules, measures and means that ensure safe traffic conditions, which are aimed at protecting and preserving the life and health of active and passive road users, as well as protecting and preserving the environment and property. Therefore, the question of studying all aspects of the operation of the "Driver-car-road-environment" system becomes acute. The general approach to the formation of reliability models of the B-A-D-S system consists in the fact that this model is described in a formalized form from the standpoint of the reliability of the interaction of subsystems in the process of functioning and reflects the degree of influence of the reliability of individual subsystems on the reliability of the system as a whole. Usually, reliability indicators of system elements (failure intensity) are determined on the basis of the laws of distribution of time of failure-free operation, and the concept of "failure" is clearly defined for each subsystem. Reliability models formed in terms of element failures are the main type of system reliability models. It follows that the set of combinations of possible states of elements determines the set of possible states of the system in general, which is called the space of system states (control theory). When writing the work, the research of domestic and foreign authors on the issues of the basics of reliability and risk assessment was studied. The purpose of the publication is to study approaches to ensuring the reliability of complex systems. It was determined that for all mechanical elements (car parts, road elements) the most suitable failure model is the DM-distribution, while the estimation of the coefficient of variation can be in the range from 0.3 to 0.7

Review of Concepts and Determinants of Grid Electricity Reliability

The reliability of the electricity supply is important since any interruption to the supply has direct and indirect consequences for its users. A reliable electricity supply requires a reliable electrical grid system to transmit and distribute the power from the generating plants to the consumers. This study reviewed the literature to find out how the reliability concept has been understood with a special focus on grid electricity reliability, what factors influence grid electricity reliability, what measures have been used to measure grid electricity reliability, which theories and methodologies have been applied to study grid electricity reliability and what are the likely research gaps that require future address. This review found that the literature documents four categories of factors that influence grid electricity reliability, and these are environmental, security, organizational and technical. The biggest influencers of grid electricity reliability were the technical-related factors followed by the environmental-related factors. In addition, we found that sixty studies focused on one subsystem, eleven on two subsystems while seven studies considered three subsystems. Most studies were found to address the distribution of subsystem reliability. As per the methodology adopted, this review found that eleven studies used a qualitative approach, forty-five studies used a quantitative approach, while eleven studies used a case study approach to study the concept of grid electricity reliability. In addition, we found that thirty-seven studies used the duration and frequency of power outages to measure grid electricity reliability.

Reliability Assessment for a Spacecraft Landing Buffer Mechanism Based on Small Sample Data

The landing buffer mechanism (LBM) is a crucial component of aerospace landing explorations, determining the success of the entire mission. Reliability demonstration tests (RDTs) are required to ensure the LBM’s performance meets the design index. However, the RDTs of the LBM often encounter limited samples and zero-failure data, making traditional binominal test programs and reliability assessment methods based on the maximum likelihood theory unsuitable. This paper introduces a novel small-sample test verification method for the LBM, which transforms traditional binominal tests into more informative metrological tests by measuring the buffer strokes of the LBM’s subsystems. Furthermore, a confidence limit theory for the product of subsystem reliability is developed in conjunction with the reliability series model of the LBM. This theory can use the measurement data of subsystems to assess the confidence limit of the LBM’s reliability. An actual engineering application demonstrates that the proposed method can effectively handle zero-failure data and verifies that the LBM’s reliability exceeds 0.9999 with a confidence of 0.9.

SEASNAKE: Impact - Marine operations modelling for evidence-based results detailing the impact of using a new fully dynamic cable design for ocean energy devices.

The SEASNAKE project - an OceanERA-NET project – is aiming for developing fully dynamic cables for ocean energy. Through new design and application of novel coatings the project is designing a dynamic cable that better suits the conditions and user requirements. In order to fully understand the benefits, the Wave Venture TEMPEST™ techno-economic analysis software will be used to simulate the performance of a proposed wave energy farm with a special focus on the contribution of the dynamic cable subsystem. The results obtained from the simulations will not only provide a deep understanding of the reliability and cost-risk areas regarding the use of dynamic cables, but will also allow a comparison with a baseline scenario consisting of a more traditional cabling system. The latter will be key to identify the advantages of the SEASNAKE project and its commercial viability. KPIs (Key Performance Indicators) will include farm availability and power production downtime as a direct result of cable related issues. The reliability, maintainability and survivability of the cabling subsystem will be tested and the KPIs will give clear indication on the performance benefits and ultimately the impact on the LCOE will be of greatest consideration.

Assessment of sustainable agricultural development based on the water-energy-food nexus framework in the middle and upper reaches of the Yellow River, China.

Water, energy and food are inextricably linked in agricultural system. Social and environmental issues arising from socio-economic development pose new challenges for sustainable agricultural development. Achieving sustainable agriculture from the perspective of water, energy and food resource conservation is of critical importance to the national strategy for high-quality development of the Yellow River Basin in China. In this study, the mass productivity and economic productivity of water and energy in agricultural system were considered, and an integrated assessment index system for agricultural system based on the Water-Energy-Food Nexus (WEFN) was proposed in three dimensions: reliability, coordination and resilience. Based on these indicators, the agricultural water-energy-food nexus index (AWEFNI) and integrated risk index (IRI) were performed to assess the current status of agricultural development in the middle and upper reaches of the Yellow River. Results indicate that the AWEFNI in the middle and upper reaches of the Yellow River is increasing year by year, and the level of sustainable agricultural development is improving, but the overall level is lower. The AWEFNI values vary widely among provinces. The reliability of single subsystem in the study area accounts for more than 1/3 of the AWEFNI, with poor water endowment， rich food and energy resource endowments, the coordination of the AWEFN is weakening. The resilience of the third subsystem is gradually declining. The contradiction in water and energy supply and demand in Ningxia is the most prominent among the five provinces, and the level of AWEFN development is the lowest, so the regulation policies should be implemented as soon as possible to promote the synergistic development of AWEFN around the region.

Optimizing and reliability analysis by firefly and genetic algorithms for a quadcopter

Our study aims to obtain the highest level of reliability for a quadcopter, taking financial and mass limitations into account, to achieve the highest level of reliability with the lowest mass and cost. For this purpose, we first calculated the reliability and the relationships that govern it, and based on these relationships, we determined the reliability of the quadcopter subsystems. In order to achieve the highest level of reliability, we utilized optimization algorithms. It is possible to increase the reliability of a system through several methods, such as enhancing the quality of parts and components, using surplus components, improving the quality of parts and components by always using surplus components, and redesigning the system. This study examines the possibility of increasing quadcopter reliability by using additional parts and optimizing it using the firefly algorithm. Lastly, in order to validate the results obtained from the firefly algorithm, we implemented the problem once again using the genetic algorithm and compared the results obtained from both algorithms. After 20 times of running the algorithms, the optimal reliability values were 0.99925 for the firefly algorithm and 0.99999 for the genetic algorithm.

Multi-Degree-of-Freedom Load Reproduction by Electrohydraulic Digital-Servo Loading for Wind Turbine Drivetrain

Many drivetrain testing facilities have been built to reproduce multi-degree-of-freedom loads, thus simulating real wind conditions for evaluations of the reliability and durability of turbine subsystems. In this paper, the electrohydraulic schemes for the non-torque loading of a wind turbine’s drivetrain test benches are first analyzed. To deal with the control inaccuracy caused by the drastically increasing loading force, along with the rapid development of large-scale wind turbines, a multi-cylinder electrohydraulic digital-servo loading (MEDSL) technology is proposed. A novel electrohydraulic digital-servo cylinders group is designed. The proposed MEDSL can provide continuous and accurate load recurrence under wider wind conditions by varying the operational area of the cylinders group. Moreover, a sliding mode controller (SMC) is designed to realize the large dynamic loading of the MEDSL system. By comparing the SMC to a traditional PID controller in a servo-valve controlled cylinder, both simulation and experiment results proved the advantage of the proposed SMC. Accordingly, extensive experiments with a 4-cylinder case were carried out on a real full-loading bench using the SMC-based MEDSL device. The excellent tracking performance under complicated signals that represent the real wind loads demonstrated the feasibility and effectiveness of the proposed MEDSL technology and the SMC method.

Reliability Allocation Method Based on 2-Tuple Linguistic Weighted Muirhead Mean Operator and 2-Tuple Linguistic Best-Worst Method

Reliability allocation is a significant link in product design. To solve the problems of poor rationality of data use, considerable difficulty of calculation using existing methods, low accuracy of results, and weak ability of experts to express and process fuzzy information, this article proposes a reliability allocation method for the initial stage of product design based on the 2-tuple linguistic weighted Muirhead mean (2TLWMM) operator and 2-tuple linguistic best-worst method (2TLBWM). The 2TLBWM introduces 2-tuple linguistic to enhance the experts’ ability to express fuzzy information. The 2TLWMM operator is used to judge the reliability index ranking of each subsystem, thereby improving the rationality of scoring data, providing a basis for experts to establish the comparison vector table, and reducing the influence of experts’ subjective factors. Experts use 2TLBWM, refer to the ranking results of subsystem reliability index, only need to establish a contrast vector table, and can calculate the weight of the subsystem, thereby reducing the number of comparisons between elements and computational complexity. The advantages of the proposed method are illustrated by a specific case.

Reliability Analysis of Failure-Dependent System Based on Bayesian Network and Fuzzy Inference Model

With the rapid development of information and automation technology, the manufacturing system is evolving towards more complexity and integration. The system components will inevitably suffer from degeneration, and the impact of component-level failure on the system reliability is a valuable issue to be studied, especially when failure dependence exists among the components. Thus, it is vital to construct a system reliability evaluation mechanism that helps to characterize the healthy status of the system and facilitate wise decision making. In this paper, a reliability analysis framework for a failure-dependent system is proposed, in which copula functions with optimized parameters are used for the description of different failure correlations, and a fuzzy inference model is constructed to derive the subsystem reliability based on the component-level failure correlation. Finally, a Bayesian network is applied to infer the system reliability based on the system structure combined with the impact of failure correlation inside. Simulation results of the proposed method show that the inference results of system reliability are reasonable and effective in different cases. Compared with the copula Bayesian network method, the proposed method shows better adaptability to failure-dependent systems to varying degrees. This work can provide theoretical guidance for evaluating the reliability of manufacturing systems of different types.

Development of a semantic map for an unmanned vehicle using a simultaneous localisation and mapping method

Introduction: The field of unmanned technologies is rapidly developing and a lot of research is being conducted on the practical application of artificial intelligence algorithms to solve complex problems on the road. The difficulties in the perception of the surrounding world by the machine led to the appearance of special High definition maps. These maps are used to simplify and improve the quality and reliability of other subsystems from the stack of autonomous technologies, such as localization, prediction, navigation and planning modules. In modern literature, there are mainly works on the practical application of such maps, and the process of developing a map remains outside the scope of consideration.The aim of the work is to create a methodology for designing semantic maps for autonomous vehicles with a detailed description of each of the development stages.Materials and methods: The article describes the methodology for creation of HD maps, which includes the stages of data collection using SLAM (Simultaneous localization and mapping) approach, its further processing and the development of the semantics of the road network. The described algorithm is applied in practice to develop the semantic map of Innopolis city area using SLAM approach with LIDAR inertial odometry via smoothing and mapping (LIO-SAM).Results: The main stages of the methodology for creating HD maps for autonomous vehicles have been proposed and investigated. Authors implemented the proposed concept in practice and described in detail the process of creating a semantic map for the Innopolis city area.Conclusions: The proposed methodology can be used for any type of autonomous robots (ground vehicles, unmanned aerial vehicle, water transport) and can be implemented in different road conditions (city, off-road), depending on the information the map should provide for the implementation of the goals and objectives set for the autonomous vehicle.

The concept of diagonal approximated signature: new surrogate modeling approach for continuous-state systems in the context of resilience optimization

The increasing size and complexity of modern systems presents engineers with the inevitable challenge of developing more efficient yet comprehensive computational tools that enable sound analyses and ensure stable system operation. The previously introduced resilience framework for complex and sub-structured systems provides a solid foundation for comprehensive stakeholder decision-making, taking into account limited resources. In their work, a survival function approach based on the concept of survival signature models the reliability of system components and subsystems. However, it is limited to a binary component and system state consideration. This limitation needs to be overcome to ensure comprehensive resilience analyses of real world systems. An extension is needed that guarantees both maintaining the existing advantages of the original resilience framework, yet enables continuous performance consideration. This work introduces the continuous-state survival function and concept of the Diagonal Approximated Signature (DAS) as a corresponding surrogate model. The proposed concept is based on combinatorial decomposition adapted from the concept of survival signature. This allows for the advantageous property of separating topological and probabilistic information. Potentially high-dimensional coherent structure functions are the foundation. A stochastic process models the time-dependent degradation of the continuous-state components. The proposed approach enables direct computation of the continuous-state survival function by means of an explicit formula and a stored DAS, avoiding costly online Monte Carlos Simulation (MCS) and overcoming the limitation of a binary component and system state consideration during resilience optimization for sub-structured systems. A proof of concept is provided for multi-dimensional systems and an arbitrary infrastructure system.

Reliability Analysis of the Cactus-Based Networks Based on Subsystem

Abstract Multiprocessor systems play a significant role in big data era. As the probability of presence of processor failures in a multiprocessor system raises with the increase of the system scale, the effect of processor failure is worthy of quantifying. The subsystem reliability of a multiprocessor system is the probability that a fault-free subsystem of certain size still operate with the rise of individual faults. In this work, we employ the probabilistic fault model and the Principle of Inclusion-Exclusion (PIE) to establish the approximation and upper bound on the subsystem reliability of the cactus-based networks through decomposition into $(n-1)$-dimensional subsystems by fixing one position-pair. Numerical simulations show that the upper bound derived in this way is close to the approximation of the accurate subsystem reliability.

Application of the reliability analysis for modifications in maintenance scheduling

The preliminary examination of the reliability of specific workstations of milk powder and curd production lines in a dairy plant was conducted to improve its availability under actual working conditions. The current study makes use of field failure and repair data, as well as Weibull++ software and the finest fitness indexes. The time between failure (TBF) and time to repair (TTR) data are given as input to the software. The reliability and availability of subsystems at different intervals of time have been estimated. The maintenance schedule can be optimized based on reliability analysis and can be revised for the subsystem having more failures. Recommended maintenance schedule appears to be beneficial from the performance point of view as well as to maintain the quality of dairy products. The present work's reliability analysis indices are beneficial for identifying the essential subsystems of milk powder and curd production lines, as well as their influence on the system's performance and product quality. On the basis of analysis, maintenance policies can be decided for various subsystems.

Techniques to Improve Write and Retention Reliability of STT-MRAM Memory Subsystem

Spin transfer torque magneto-resistive random-access memory (STT-MRAM) has many advantages, such as scalability, persistence, practically infinite endurance, and fast access speed, that make it a promising and emerging technology for memory. However, this technology has multiple reliability issues, such as read and write reliability, higher write power, and long write latency, etc. At elevated temperatures, these issues exacerbate further. As the temperature increases massively in the latest compute nodes, we need to study and understand the effect of temperature on STT-MRAM memory writes and reliability. In this article, we propose the temperature-aware memory controller (MC) and device architecture techniques specific to STT-MRAM technology, which can improve write reliability, retention reliability, and memory power without sacrificing the performance. Our simulation results show that the proposed techniques cumulatively improve the write bit error rate (BER) on an average by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$603\times $ </tex-math></inline-formula> , increase retention reliability by 65%, along with 27% power reduction and 5.8% improved system performance over the baseline STT-MRAM-based memory subsystem.

고장수목분석(FTA) 기법을 이용한 무인잠수정 건전성 진단

As an autonomous underwater vehicle (AUV) operates over a long period of time in the sea, continuous online monitoring of the vehicle is crucial. By monitoring the health status of the AUV, it is possible not only to avoid a serious damage or even loss of the vehicle, but also to effectively manage the missions being carried out. This paper presents an online health monitoring technique for AUVs using Fault Tree Analysis (FTA). The use of both information about the reliability and performance of subsystems can be highlighted as the main contribution from this work. The whole system is divided into several subsystems for which a fault tree is designed. Then, the system health is evaluated using the given fault tree by considering not only the performance of each component, but also the weighting factors, reliability, and fault status of various parts in each subsystem. In order to determine the health status of the AUV in real-time, the fault tree is structurally analyzed using the information mentioned above. The effectiveness of the proposed method is demonstrated using a set of simulations.

Improving CubeSat reliability: Subsystem redundancy or improved testing?

The objective of this paper is to investigate which approach would lead to more reliable CubeSats: full subsystem redundancy or improved testing. Based on data from surveys, the reliability of satellites and subsystems is estimated using a Kaplan–Meier estimator. Subsequently, a variety of reliability models is defined and their maximum likelihood estimates are compared. A product of a Lognormal distribution addressing immaturity failure and a Gompertz distribution addressing wear-out is found to best represent CubeSat reliability. Bayesian inference is used to find realistic wear-out parameters by using failure data of small satellites. Subsystem reliability estimates are subsequently found using a similar approach. A reliability model for CubeSats with redundant subsystems is established, verified and applied in a Monte Carlo simulation. The results are compared with a model for reduced immaturity failure. Allocating resources to reduction of immaturity failures through improved testing is considered to be superior to allocating these resources to the implementation of subsystem redundancy.

Robustness of subsystem reliability of $k$-ary $n$-cube networks under probabilistic fault model

With the emergence of the Big Data era, as multiprocessor systems consisting of multiple processors play a vital role in big data analytics, we are prompted to explore the qualitative and quantitative metric to characterize the reliability of the systems. As the size of the multiprocessor systems grows, the probability of the occurrence of failing processors increases. One metric of the macroscopic reliability of a system is the measure of the collective effect when its subsystems are out of function. The subsystem reliability of a system is the quantitative metric that a fault-free subsystem of specific size is operational as before with the occurrence of individual faults. Although some networks have the same order and similar topologies, there are differences in their subsystem reliabilities. In this work, we focus on the comparison of two distinct topologies of <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-ary <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-cube networks with the same order and calculate the robustness of reliability bounds of <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-ary <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-cube networks. We analytically show that the subsystem reliability is negatively correlated with the dimension <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>, even if two subsystems of <inline-formula><tex-math notation="LaTeX">$Q_{n}^{k}$</tex-math></inline-formula> are of the same order. That is, the smaller <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is, the larger subsystem reliability of <inline-formula><tex-math notation="LaTeX">$Q_{n}^{k}$</tex-math></inline-formula> will be. This work provides a theoretical methodology to choose the more dependable topology of <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-ary <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>-cube networks with the same order. Finally, we apply some numerical simulations to validate the results we established.

The reliability of automotive subsystems influence on the motor vehicles fuel economy

The reliability theory consistently regards all phases of vehicle construction and operation. The properties determining the vehicle reliability, which are also called potential objectives, are precisely formulated from early design and manufacturing phases and accomplished in the production process. The analysis of reliability from the perspective of potential properties allows us to identify certain categories of potential properties. One refers to potential properties that depend on the deterioration of operating functions. In this category, we can find the resistance to breakage and deformation, stability of operating processes, stability of the physical-mechanical properties of the construction materials and of the working environment. Secondly, the potential properties required to accomplish the required level of production and reduce the manufacturing costs, such as manufacturing technology, the corresponding volume of production, simplicity of manufacture and failure-free manufacturing. Thirdly, there are potential properties needed to maintain the reliability at a high level during service, such as developing the quality of diagnoses, technical maintenance, reducing all types of costs and increasing productivity. Here we find the technology of the diagnosis and the totality of the external expenses and the adaptability to the automation of diagnosing tools. Operating reliability is the result of the full accomplishing of the potential reliability of components. The reliability of automotives treated as a subsystem can successfully be evaluated by defining certain operating indicators and characteristics, the economic characteristic being of great interest and importance.