Reliability Measures Of System Research Articles

Merging multi-level evidential observations for dynamic reliability assessment of hierarchical multi-state systems: A dynamic Bayesian network approach

Dynamic reliability assessment has offered a new paradigm for engineered systems to integrate multi-level observations to update the reliability measures of a specific running system. The existent work on dynamic reliability assessment can only leverage precise observations and cannot be straightforwardly implemented in scenarios where observations are imprecise. However, the observations are inevitably imprecise owing to the limited accuracy of inspection techniques and vague judgments of the system state. In engineering scenarios, multi-state systems (MSSs) with a hierarchical structure are commonly existent, and the imprecise observations can be collected across multiple physical levels of the system. In this article, the uncertainty associated with imprecise observations is characterized by the evidence theory, and it can be therefore regarded as an evidential form. A dynamic Bayesian network (DBN) model is utilized to evaluate the reliability of hierarchical MSSs with multi-level evidential observations. Subsequently, the evidence theory is implemented to quantify epistemic uncertainties associated with imprecise observations. These observations, sourced from multiple physical levels, are merged by the DBN model using the Dempster rule of combination (DRC) to update the reliability of a specific running system in a dynamic fashion. The feasibility and correctness of the proposed method have been demonstrated through a numerical case and a real engineering case of a kerosene filling control system (KFCS), and the result indicates that the proposed DBN-based algorithm methods have high applicability and generalizability.

A novel method of refining the performance of rail systems: an evaluation of system dynamics using discrete event simulation

PurposeThis paper aims to trial a novel method of improving the performance of rail systems. Accordingly, an evaluation of rail system dynamics (SD) using discrete event simulation (DES) will be undertaken. Globally, cities and their transportation systems face ongoing challenges with many of these resulting from complicated rail SD. To evaluate these challenges, this study utilized DES as the basis of the analysis of Melbourne Metro Rail's SD. The transportation SD processes including efficiency and reliability were also developed.Design/methodology/approachUsing DES, this research examines and determines the Melbourne Metro Rail's SD. Although the Melbourne Metro Rail is still in progress, the DES developed in this research examined the system requirements of functionality, performance and integration. As the basis of this examination, the Melbourne Metro Rail's optimization was simulated using the developed DES. As the basis of the experiment, a total of 50 trials were simulated. This included 25 samples for each of efficiency and reliability. The simulation not only scrutinized the SD but also underlined some of its shortfalls.FindingsThis study found that information and communication technology (ICT) was the pinnacle of system application. The DES development highlighted that both efficiency and reliability rates are the essential SD and thus fundamental for Melbourne Metro Rail system functionality. Specifically, the three elements of SD, capacity, continuity and integration are considered critical in improving the system functionality of Melbourne Metro Rail.Research limitations/implicationsThis particular mega rail infrastructure system was carefully analyzed, and subsequently, the DES was developed. However, since the DES is at its inception, the results are relatively limited without inclusive system calibration or validation process. Nonetheless, with some modifications, such as using different KPIs to evaluate additional systems variables and setting appropriate parameters to test the system reliability measures at different intensities, the developed DES can be modified to examine and evaluate other rail systems. However, if a broader system analysis is required, the DES model subsequently needs to be modified to specific system parameters.Practical implicationsThrough evaluation of Melbourne's Metro Rail in the manner described above, this research has shown the developed DES is a useful platform to understand and evaluate system efficiency and reliability. Such an evaluation is considered important when implementing new transport systems, particularly when they are being integrated into existing networks.Social implicationsEfficient rail networks are critical for modern cities and such systems, while inherently complex, aid local economies and societal cohesion through predictable and reliable movement of people. Through improved system functionality and greater efficiencies, plus improved passenger safety, security and comfort, the traveling public will benefit from the enhanced reliability of the transportation network that results from research as that provided in this paper.Originality/valueThis research paper is the first of its kind specifically focusing on the application of DES on the Melbourne Metro Rail System. The developed model aligns with the efficiency optimization framework, which is central to rail systems. The model shows the relationship between increased efficiency and optimizing system reliability. In comparison with more advanced mathematical modeling, the DES presented in this research provides robust, but yet rapid and uncomplicated system enhancements. These findings can better prepare rail professionals to adequately plan and devise appropriate system measures.

Optimal Design Based on Surrogate Reliability Measures for Water Distribution Systems

Optimal Design Based on Surrogate Reliability Measures for Water Distribution Systems

A literature review and future research agenda on fault detection and diagnosis studies in marine machinery systems

Fault detection and diagnostics (FDD) have great potential to enable safety, efficiency, and reliability measures of critical machinery systems. However, it is clear that there is a lack of systematic literature review to identify and classify the FDD studies conducted within the scope of marine engineering. This paper offers a systematic review of FDD models particular to marine machinery and systems. The numbers of 72 core articles were highlighted through a comprehensive literature review conducted in the 2002–2022 period. The studies are classified based on the mostly utilized methods such as data-driven, model-based, knowledge-based, and new generation-hybrid. In addition, new generation and hybrid methods are discussed in detail. The experimental environment (i.e. shipboard, labs, simulator) and technical details of the conducted studies are extensively discussed. While 56.94% of the examined studies are related to the main engine, 43.06% of them are related to auxiliary engines. In addition, the main and auxiliary engine studies are also divided into subject headings and examined in detail. Given the recent developments in green and smart maritime concepts, a future research agenda of the FDD studies on marine machinery systems is then pinpointed. Consequently, the study stimulates scholars interested in FDD while it enables innovative ideas for marine engineers, technology providers, ship operators, and maritime entrepreneurs.

Stochastic analysis of a non-identical three units repairable system with operational priority to simultaneously working of identical units

PurposeThe purpose of present study is to carry out stochastic analysis of some important reliability measures of a three-unit system where there are two types of units called type-I and type-II. In type-II, two identical units work simultaneously to meet the system requirements while in type-I, a single unit is kept in spare and can be used to work whenever required at the failure of either of the units of type-II. The system starts its operation with type-II units and thus priority is given to the operation of type-II units. The type II units are different to type-I unit but can perform the same task. There is a single server who handles repair activities of both type of units and the units are assumed to be in pristine condition after every repair. Failures of both types of units are independent and constant. The system can fail at the failure of either of the type-II units and type-I unit.Design/methodology/approachSemi-Markov process and regenerative point technique are used to study the behaviour of different reliability measures of the system.FindingsIn this paper, a three-unit non-identical repairable system is analysed stochastically and its reliability characteristics such as transition probabilities (TP), mean sojourn time (MST), MTSF, steady state availability, expected number of repairs of units, expected number of visits of the repairman and expected busy period of repairman are derived to carry out profit analysis.Research limitations/implicationsThe direct application of the present study can be seen is case of a power distribution system where solar panels may be considered as type-II units and transformer as the type-I unit. Here, the case study is carried out by using approximate data from some old studies; however, a study with accurate data would be more preferable.Originality/valueThis paper is one of the few reliability studies conducted on a system with simultaneous working units. Also, the comparative study of the profit of the present system model has been done with that of the model Kadyan et al. (2020a).

Evaluation of Unreliable Retrial G-queue Using Fuzzy ARAS Method

A Regular busy server crashes due to negative customer traffic, and holiday interruption is being considered. If the orbit empties at the end of a positive customer service, the server worked Going on vacation. A working vacation (WV) server at a low service rate works. If there are clients on the computer at the end of each holiday, the server the probability that a new visitor is inactive and on vacation is p (single WV) or with probability q (multiple WVs). Substantial variable technique, constant state probability for the system and its orbit we found the generating function. System performance measures, reliability measures and random decay law are discussed. Finally, Some numerical examples and cost optimization analysis provided. Alternative: Single-Server Review G- Sequence, Incredible Review G-Series, Volume Visit Review G-Series. Evaluation Preference: Working vacation, Bernoulli feedback, Random vacations, single vacation. Unreliable retrial G-queue, Batch arrival Retrial G-queue, single server iteration is taken as a G-sequence alternative and working vacations, random vacations, single vacation, and Bernoulli vacation is taken evaluation parameters. In this from analysis Fuzzy ARAS method the best solution determines the solution with the shortest distance and the longest distance from the negative-best solution, but comparison of these distances is not considered significant. As a result it seems unreliable retrial G-queue got the first rank where as is the Batch arrival Retrial G-queue is having the lowest rank.

Analysis of a Stochastic Model with Rework System

The demand in the present global industrial system, requires the challenge to meet the growing consumer capabilities and requirements constantly. So, there is always a need to improve different parameters, one of them being different types of failures involved in the working of different engineering systems related to communication systems, manufacturing goods, nuclear and hydro power plants, automobiles and many others. Human error occurring in the working of various systems has always been the challenge to the researchers and is being constantly worked upon by the researchers in the analysis and improvement of reliability and availability of different complex and multistate systems. In the present paper, there is a three-unit system consisting of the unit A with two subunits in parallel and other units B and C are connected in series with A. The authors have investigated and analysed different reliability measures like availability, MTTF and sensitivity taking into account the human failure and carrying out rework system. This research work aims at the study of reliability and availability measures of a multi-state system incorporating human error so as to increase the efficiency of industrial systems by taking maintenance and rework measures to enhance the availability factors. This would help to understand and estimate the reliability measures of any such systems in the field of telecommunication, any electronic devices like that in small power plants, robot systems and such others. Also, a comparison has been made between the availability and reliability estimates in the presence and in the absence of human error. The techniques used are Markov process, Laplace transformation and supplementary variable technique.

Performance Assessment and Sensitivity Analysis of a Computer Lab Network Through Copula Repair with Catastrophic Failure

The advent of copula distribution by Gumhel-Hougaard family spurred a new direction of research in multi-state complex engineering systems and is widely applied in various series-parallel systems. Considering this aspect, in this paper we study various reliability measures of a complex system consisting of eight identical computer labs as star topology working under 5-out-of-8: G policy, two different centralized data base servers working under 1-out-of-2: G policy, and a switch in series configuration. Failure rates of all the units are assumed to be constant and follow exponential distribution, while repair supports general distribution and copula distribution. The objective of this paper is to evaluate availability of the system, reliability of the system, mean time to failure and expected profit analysis by choosing arbitrary values of the parameters in a way that numerical solutions can be obtained systematically in a reasonable computational time. The problem is modelled using supplementary variable technique, Laplace transform and copula repair. We highlight the use of copula repair, while identifying the factors for improvement and future directions of work.

Stochastic analysis of k-out-of-n: G type of repairable system in combination of subsystems with controllers and multi repair approach

This paper describes the investigation of different reliability measures of a complex system consisting of two subsystems with controllers in a series configuration, which is a useful opportunity for specific design problems. Subsystem-1 consisting n units functioning under the policy k-out-of-n: G; policy, and subsystem-2 has m units and operating under r-out-of-m: G; policy. The system failure rates of both subsystems are constant and assumed to obey an exponential distribution; two types of distribution are allowed to repair: general distribution and Gumbel-Hougaard family copula distribution. The system's partially failed states/ completely failed states are repaired using General/ copula distribution. After repair, the units in both the subsystems are good as new. The controller control both subsystems and the failure of controllers brings the subsystem in the complete failed state. The operator may fail the system deliberately if not satisfied with the organization. The system is analyzed employing the supplementary variable technique, and Laplace transforms implications and traditional system reliability measures, such as the system's availability, system reliability, and profit analysis, have been computed for particular values of failure and repair parameters.

Generalized reliability measures of a complex non-series parallel system (CNSPS) with Rayleigh failure laws

Generalized reliability measures of a complex non-series parallel system (CNSPS) with Rayleigh failure laws

Dynamic reliability modeling for general standby systems

General standby systems with component lifetimes following independent and nonidentical phase-type (PH) distributions are presented in a state-space model using state transition block matrices. The model is constructed by identifying a block matrix representing each system state and a block matrix that causes a transition from one system state to another. This general model is applicable to hot, warm, or cold standby and any combination of them in K-out-of-N general standby structures. The resulting model becomes a PH representation of the system lifetime distribution and is thus useful for exact dynamic system reliability analysis. The advantage is that many functional system reliability measures, such as the reliability, hazard, and mean residual life functions, can be obtained by simple matrix algebra. These functions are shown to be useful for determining optimal component ordering. Comparisons with other methods from previous publications are presented.

Stochastic Analysis of a Priority Standby System under Preventive Maintenance

In this paper, we propose a system of two dissimilar units: one unit prioritizes operation (priority unit), and the other unit is kept as a cold standby (ordinary unit). In this system, we assume that the failures, repairs, and preventive maintenance (PM) times follow arbitrary distributions for both units, except for the fact that the repair time of the ordinary unit follows an exponential distribution. The priority unit has normal, partial failure or total failure modes, while the ordinary unit has normal or total failure modes. The PM of the system can be started after time t when (i) the priority unit is in the normal or partial failure modes up to time t and (ii) the standby unit is available up to time t. PM can be achieved in two types: the costlier type with probability p and the cheaper type with probability (1−p). Under these assumptions, we investigate the reliability measures of the system using the regenerative point technique. Finally, we show a numerical example to illustrate the theoretical findings and show the effect of preventive maintenance in the reliability measures of the proposed system.

Discrete time dynamic reliability modeling for systems with multistate components

This study proposes modeling techniques for the exact dynamic reliability analyses of systems with the lifetimes of all components following independent and nonidentical discrete phase-type (DPH) distributions. The systems may have series, parallel, standby, K-out-of-N, and bridge structures with any combinations of them. The models produce numerical formulas and algorithms for generating system reliability and hazard functions; thus, they are applicable to the dynamic reliability analysis of systems, including networks. The approach is by showing that the system lifetime follows a DPH distribution. For network reliability analysis, the DPH distribution is generalized into a matrix-geometric (MG) distribution. The use of the DPH distribution makes the models suitable for systems with multistate components and simplifies the calculations of the system reliability measures. Its effectiveness is illustrated using results from complex structure systems.

Fault Tree Analysis With Interval Uncertainty: A Case Study of the Aircraft Flap Mechanism

This article proposes an uncertainty analysis method for evaluating the reliability of a system and calculating the relative importance of the system inputs when the probabilities of basic events are characterized by intervals. The reliability requirement or the safety criterion is first considered in the system reliability assessment. A nonprobabilistic reliability index, called R-index, is defined to evaluate the reliability of the system. Two importance measure indices, called location effect and size effect, are introduced for estimating the influence of the probability uncertainties of basic events on the R-index, thus identifying influential and noninfluential basic events and comparing their relative importance. Then, the proposed method is applied to an illustrative fault tree example and the fault tree analysis of unilateral asymmetric movement of an aircraft flap mechanism, thereby explaining the significance of this method. The results show that the proposed method provides a viable tool for system reliability and importance measure analysis when probability intervals are involved.

Reliability modeling for a repairable (k1, k2)-out-of-n: G system with phase-type vacation time

This paper proposes a novel mathematical model for reliability dealing with a (k1, k2)-out-of-n: G repairable system consisting of two different types of components. It is assumed that the working times of two different types of components are distributed exponentially with different parameters. In the case of failures occurring in components, a repairman is assigned to repair them. The repair time of each failed component is governed by the same exponential distribution. On the other hand, the repairman’s vacation time follows a phase-type distribution. The system operates if and only if at least k1 type 1 components and k2 type 2 components function simultaneously. The system reliability measures are analyzed using Markov process theory and matrix analytical method. An illustrative example related to the solar power generation system is provided to examine the effectiveness and the applicability of the proposed model.

Stochastic Analysis of a Computer System with Unit Wise Cold Standby Redundancy and Priority to Hardware Repair Subject to Failure of Service Facility

The use of semi-Markov process and regenerative point has been made for determining reliability measures of a computer system. The stochastic model is developed by considering the ideas of unit wise redundancy and failure of service facility. The treatment to the failed service facility is given in order to resume the jobs with full efficiency. The system is analyzed at different time points in the steady state. The profit of the system model has been obtained under the following two policies: In first policy, the profit is evaluated by taking cost per unit time for busy period of the service facility and cost per unit time treatment of the service facility. In second policy, the profit is evaluated by taking cost per unit hardware repair, per unit time software up-gradation and cost per unit time treatment of the service facility. The behavior of some reliability measures, such as MTSF, availability and profit function, has been shown graphically for arbitrary values of the parameters.

An efficient Kriging based method for time-dependent reliability based robust design optimization via evolutionary algorithm

Uncertainty inadvertently exists in various stages of engineering system design, development, and operating conditions. During the system design and development stages, a design engineer encounters the reliability and robustness measures of a dynamic uncertain system. Due to the existence of dynamic uncertainties, incorporating the time-dependent reliability of an engineering system in reliability based robust design optimization (RBRDO) is crucial. However, the time-dependent and highly non-linear performance functions present a new challenge to the RBRDO problem. This paper presents a multiobjective integrated framework and corresponding algorithms to handle a time-dependent RBRDO problem. The mean and coefficient of variation of the cost function are taken as a multiobjective problem that needs to be optimized to maximize the robustness without destabilizing the system performance. An evolutionary algorithm is employed to find the optimal design points. The performance functions used to estimate the time-dependent reliability are taken as dynamic probabilistic constraints. The dynamic probabilistic constraints are then converted into deterministic constraints by predicting the corresponding time-dependent reliability. A transfer learning based method integrated with the Kriging surrogate models is proposed to predict the time-dependent reliability for a given time interval. Various examples are used to demonstrate the effectiveness of the proposed approach.

Reliability Comparison of Two Deterministic Criteria for Planning High Voltage Auto-Transformer Stations

This paper describes a reliability study that has been performed at Hydro One to compare the reliability of two deterministic criteria used in the planning of high voltage auto-transformer stations. One criterion calls for designing the station to withstand the loss of one unit transformer (single contingency criterion) while the other calls for designing it to withstand the loss of two units (double contingency criterion). Two system reliability measures are used in the comparison namely the system availability index and the loss of energy index. The study proposed a number of Markov models to evaluate the probability of system failures under each criterion. Examples are provided to illustrate these models and see how the two deterministic planning criteria are compared from the reliability point of view.

Stochastic Analysis of Complex System with Auto Changeover Switch and Advert Environment Employing Copula Approach

This paper studies the reliability measures of a system consisting of two subsystems in a series configuration for different types of failure and two types of repair. The subsystem-1 has four identical units in a parallel configuration operating under 3-out-of-4: G policy and this has connected to subsystem-2 which has three identical units arranged in a parallel configuration and working under 2-out- of-3: F, scheme. The units of subsystem-1 are controlled by a controller for preventing failure effect and safety purposes. It is assumed that units of each subsystem have different types of failure and repair rates. The unsuitability of the environmental conditions such as overheating as a well-known natural cause of failure of any system and also weather conditions like heavy rain, thunderstorm, and catastrophic shakeups, etc. have treated as a complete failure of the system. This study considers the environmental causes of failure in the proposed repairable system as complete failure by which the system stops functioning. Human failure in the system is trickled as complete failure and repair employing copula (Gumbel- Hougaard family copula distribution) like another complete failed states of subsystems. To analyze the proposed system, the supplementary variable technique are used and some measures of system reliability like availability, reliability; MTTF and incurred profit function for different values of parameters are derived. Some particular cases for different values of failure rates that have explicit are also studied.

Cost Benefit Analysis of a k-out-of-n: G Type Warm Standby Series System Under Catastrophic Failure Using Copula Linguistics

This paper deals with the study of reliability measures of a complex engineering system consisting three subsystems namely L, M, and N in series configuration. The subsystem-L has three units working under 1-out-of-3: G; policy, the subsystem-M has two units working under 1-out-of-2: G policy and the subsystem-N has one unit working under 1-out-of-1: G; policy. Moreover, the system may face catastrophic failure at any time t. The failure rates of units of all subsystems are constant and assumed to follow the exponential distribution however, their repair supports two types of distribution namely general distribution and Gumbel-Hougaard family copula distribution. The system is analyzed by using the supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula to derive the differential equations and to obtain important reliability characteristics such as availability of the system, reliability of the system, MTTF, and profit analysis. The numerical results for reliability, availability, MTTF, and profit function are obtained by taking particular values of various parameters and repair cost using maple. Tables and figures demonstrate the computed results and conclude that copula repair is more effective repair policy for better performance of repairable systems. It gives a new aspect to scientific community to adopt multi-dimension repair in form of copula. Furthermore, the results of the model are beneficial for system engineers and designers, reliability and maintenance managers.