Reliability Allocation Problem Research Articles

Hybridization in nature inspired algorithms as an approach for problems with multiple goals: An application on reliability–redundancy allocation problems

This paper focuses on approaching reliability–redundancy allocation problems, using hybrid schemes that consist of individual nature inspired algorithms. The aim is to investigate if hybridization is an efficient way to approach problems with multiple goals. Therefore, known algorithms that have been successfully applied to reliability and redundancy allocation problems in literature are implemented as part of hybrid schemes in this study. The idea behind that is to study whether an efficient hybrid scheme is the outcome of the hybridization of (individual) efficient algorithms. The performance of the nine proposed schemes and the individual algorithms is tested on ten well-known artificial and real-world case studies, from the field of reliability engineering. The numerical results are compared to others from literature highlighting the efficiency of the proposed hybrid schemes and consequently, support the hypothesis that hybridization can enhance the performance of optimization methods. The experimental results demonstrate that among the nine hybrid schemes, the one consisting of Bat Algorithm and Firefly Algorithm shows the best performance.

Optimization of Complex System Reliability using Hybrid Grey Wolf Optimizer

Reliability allocation to increase the total reliability has become a successful way to increase the efficiency of the complex industrial system designs. A lot of research in the past have tackled this problem to a great extent. This is evident from the different techniques developed so far to achieve the target. Stochastic metaheuristics like simulated annealing, Tabu search (TS), Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CS), Genetic Algorithm (GA), Grey wolf optimization technique (GWO) etc. have been used in recent years. This paper proposes a framework for implementing a hybrid PSO-GWO algorithm for solving some reliability allocation and optimization problems. A comparison of the results obtained is done with the results of other well-known methods like PSO, GWO, etc. The supremacy/competitiveness of the proposed framework is demonstrated from the numerical experiments. These results with regard to the time taken for the computation and quality of solution outperform the previously obtained results by the other well-known optimization methods.

Use of ARINC Approach method to evaluate the reliability assignment for mixed system

The reduction process, which will permit us to transform a mixed system into a sequential system in order to resolve the problem of reliability allocation for this type of system, will be used in this research to measure the reliability allocation for mixed systems.

Optimization and estimation in system reliability allocation problem

Designing an optimal reliability system with a minimum cost is one of the challenging problems in engineering field over the years. Estimating the subsystem reliability and determining the optimal number of component allocation will give an insight into the adequate performance of the entire system under study. In some scenarios, if a subsystem fails, then the whole system will fail, thus posing a severe threat to the safety of engineers and personnel involved. Hence, the need to optimally determine and allocate the required number of components as well as estimating their reliability so that the system’s safety would be guaranteed. In this paper, two procedures for estimating system reliability function are proposed using the maximum likelihood estimators and uniformly minimum variance unbiased estimators. The reliability functions of some selected lifetime distributions are estimated using the proposed procedures via a simulation study. The study presents a hybrid concept of estimation and optimization theory in reliability allocation problem. The work illustrated through a case study, and an optimization technique used to determine the optimal number of components at a minimum cost. The study would be useful for decision-makers in heavy industries/complex systems to help estimate the reliability of system components, optimize the allocation and manufacturer selection problems.

Research on the Reliability Allocation Method for a Wind Turbine Generator System Based on a Fuzzy Analytic Hierarchy Process Considering Multiple Factors

Given the current reliability allocation problem of wind turbine generator systems, based on the reliability allocation method of series systems, a reliability allocation model based on an improved fuzzy analytic hierarchy process (FAHP) is proposed. A three-scale standard is adopted to comprehensively consider six influencing factors, such as technical level, working environment and importance, by determining the comprehensive allocation weight combined with an improved FAHP and entropy weight method. In this way, the reliability allocation calculation model for a wind turbine generator system is developed for the reliability allocation of the wind turbine generator system. Using the method developed in this study and other methods for the reliability allocation of a wind turbine generator system as examples, the allocation results are compared and analyzed. The results show that this method not only is effective but also obtains lower allocation results than those of other studies, which verifies the rationality of the present method.

System Reliability Allocation and Optimization Based on Generalized Birnbaum Importance Measure

Importance measure can be used to identify the most vulnerable components with respect to system functionality or failure. Traditional importance measures may not be effective to evaluate the contribution of an individual component if its reliability value does not fall in the full range between 0 and 1. Based on the cost–reliability relation, this paper proposes a generalized Birnbaum importance measure (GBIM) to quantify the contribution of individual components to system reliability improvement by considering reliability range, manufacturing complexity, and technology feasibility. Since GBIM possesses several unique features in terms of guiding system reliability optimization, in this paper, we further develop a GBIM-based genetic algorithm to solve a type of optimal reliability allocation problem. The numerical studies show that both the computational efficiency and the near global optimality based on GBIM outperforms the methods using the traditional importance measures.

The Problem of Reliability Allocation in the Subassemblies of Rail Vehicles

Abstract The following paper concerns an application of reliability allocation as a method for achieving the desired level of reliability for a selected subassembly of a type 6Dg diesel locomotive. On the basis of real operational data for the investigated vehicle, a decision model was developed to solve the allocation problem. It was demonstrated that the locomotive’s reliability may be improved by replacing the individual components in the braking and pneumatic system with components of higher reliability or by using additional equivalent parallel components in the reliability-wise configuration.

Improved shuffled frog leaping algorithm on system reliability analysis

With the increase in system complexity, the intelligent heuristic optimization methods have received more and more attention on system reliability analysis. However, the objective functions and constraint conditions of system reliability are nonlinear. Thereby, a hybrid optimization method was proposed, based on the shuffled frog leaping algorithm and bacterial foraging algorithm, to solve the problem of system reliability and redundancy allocation. First, random grouping strategy was added to maintain the diversity of the population. Then, the Levy flight update strategy was used to increase the global search ability. Finally, the method of migration operation was introduced to escape from local optimums. The proposed methodology, a new version of the SFLA algorithm, was then applied to the mathematical test and the operation of the system reliability model, respectively. Results show that compared to the common methods, it can obtain the best solution, with the maximum value of the system reliability.

Multi-objective optimization in redundant system considering load sharing

Reliability allocation problem (RAP) deals with the dilemma between reliability (or availability) increase and some undesirable consequences, as an increase in cost. Therefore, new installations or maintenance investments should be optimally allocated to maximize the reliability (or availability), considering all restrictions. This paper proposes a solution for the RAP problem, taking into account failure dependency among redundant components. Because of that, a stochastic approach, based on Markov Chain, is applied. The multi-objective problem is solved with NSGA-II (Non-Dominated Sorting Genetic Algorithm II), assuming availability and overall costs as objective functions. Two examples are tested with the proposed approach. The first case is a hypothetical system with 5 subsystems in series. The second example is a real industrial application. In both cases, a Pareto front is obtained, allowing an analysis of viable solutions to be adopted. Additionally, the failure dependency effect is also present in the optimization results. Therefore, it is possible to investigate the influence on the system availability and final cost.

Reliability allocation model and algorithm for phased mission systems with uncertain component parameters based on importance measure

This paper presents a model to deal with reliability allocation problem of phased mission systems (PMS), especially for PMS with uncertainty in components’ parameters due to inaccurate information and different phase environments. In practice, real value of the reliability of a component may become lower than its designed value due to such uncertainty, thus making the whole system fail to meet the required reliability level. Therefore, in this paper, we present a model that incorporates the component uncertainty in the system reliability allocation process and then propose a variance-based global importance hybrid heuristic algorithm for its solution. The variance-based global importance measure is used to evaluate the importance of a component to the mission reliability of PMS while the reliabilities of all components vary randomly. The main procedures of the proposed algorithm include: (1) generate feasible solutions by roulette wheel selection method based on a global importance index; (2) improve solutions by adjusting reliability parameter values of components according to their global importance; and (3) improve solutions by crossover and mutation operations of genetic algorithm (GA). To illustrate the effectiveness of the proposed model and algorithm, two examples of PMS are presented and the allocation solutions are validated through Monte–Carlo simulation method. Finally, we compare the proposed model with a general allocation model that does not consider component uncertainty, and additionally with a cost-based heuristic algorithm and a particle swarm optimization (PSO) algorithm. Our results show that component uncertainty has significant influence on the confidence level that an allocation solution satisfies the required system reliability. Hence, it is essential to consider component uncertainty in reliability allocation process. In comparison with the cost heuristic algorithm and the PSO algorithm, the proposed algorithm is more effective in reliability allocation of PMS with uncertainty in components’ parameters.

Developing an economical model for reliability allocation of an electro-optical system by considering reliability improvement difficulty, criticality, and subsystems dependency

The nature of electro-optical equipment in various industries and the pursuit of the goal of reducing costs demand high reliability on the part of electro-optical systems. In this respect, reliability improvement could be addressed through a reliability allocation problem. Subsystem reliability must be increased such that the requirements as well as defined requisite functions are ensured in accordance with the designers’ opinion. This study is an attempt to develop a multi-objective model by maximizing system reliability and minimizing costs in order to investigate design phase costs as well as production phase costs. To investigate reliability improvement feasibility in the design phase, effective feasibility factors in the system are used and the sigma level index is incorporated in the production phase as the reliability improvement difficulty factor. Thus, subsystem reliability improvement priorities are taken into consideration. Subsystem dependency degree is investigated through the design structure matrix and incorporated into the model’s limitation together with modified criticality. The primary model is converted into a single-objective model through goal programming. This model is implemented on electro-optical systems, and the results are analyzed. In this method, reliability allocation follows two steps. First, based on the allocation weights, a range is determined for the reliability of subsystems. Afterward, improvement is initiated based upon the costs and priorities of subsystem reliability improvement.

A reliability optimization allocation method for the hydraulic system of CNC honing machine considering the operating condition information

In recent years, reliability optimization allocation has drawn a broad spectrum of attentions, especially for complex systems consisting of a large number of subsystems and components. Hydraulic system, deemed as a complex system, plays a great role in reliability increment of the CNC honing machine. In order to realize the CNC honing machine tool’s balanced operating performance, the crucial hydraulic system is designed to obtain the optimal and well-balanced allocation solution under the constrains of cost and reliability. Meanwhile, the quantified operating factor that influences the allocation solution is rarely considered adequately when operating samples are insufficient. So, if hydraulic systems are used in a new required longer operating mission duration or a new severer operating environment, the dissatisfied reliability could not be better reallocated to adapt to this environment with appropriate methods. Aimed at overcoming the abovementioned shortcomings and optimizing the dissatisfied reliability for existing hydraulic systems, this paper proposes a reliability optimization allocation method considering operating the condition information. From the standpoint of the complex system, this method firstly builds a three-level reliability optimization allocation model based on the analytic target cascading for the specific hydraulic system of CNC honing machine 2MK2263 × 200. It transforms the complex reliability allocation problem to a set of smaller and coordinated optimization sub-problems. Secondly, through studying the operating reliability problems of small samples in the new operating scene, the reliability prediction results based on the operating condition information are applied to build the initial reliability targets, which are regarded as the initial constrains for the optimization. With the help of analytic target cascading model and initial target reliability, the optimal reliability for the complex hydraulic system would be obtained. It is also shown to provide an innovative route for the reliability redesign of the related complex systems for this new required operating scene.

A comprehensive reliability allocation method for series systems based on failure mode and effects analysis transformed functions

In order to address the reliability allocation problem of the series system, a comprehensive reliability allocation method based on a transformed function of the failure mode and effects analysis is introduced. First, considering multiple factors that affect the reliability allocation, an allocation matrix is established by employing significance factors. Subsequently, to overcome the limitations of the conventional failure mode and effects analysis–based allocation method, non-linear transform laws of failure severity and occurrence, known as transformed functions, are established. The reliability allocation results could be adjusted appropriately by choosing transform coefficients according to the desired allocation results of the system. Then, the transformed failure mode and effects analysis and the comprehensive allocation matrix are combined to give an allocation vector. Finally, a computerized numerical controlled lathe and a spindle system are used as examples. The allocation results of the transformed method, the conventional failure mode and effects analysis method and those in the correlated references are compared to emphasize the significance of the proposed allocation method in engineering practice.

Complex System Reliability Optimisation: Further Assessment of a Multicriteria Approach

Optimal allocation of reliability to components of a system is one of the several ways of ensuring high system reliability in design. The problem which is typically formulated as single criterion optimisation encounters difficulty when the analytic system reliability expression is intractable usually as a result of complex system configuration. The current work re-examines a novel approach previously developed by the authors which takes a multicriteria view of the problem on the basis of the minimum cut sets of a system, and thus avoids finding the top level system reliability before optimisation. The model and methodology was applied to two complex system reliability allocation problems: a classical one and one associated with electricity transmission. The results were consistent with previously obtained ones by the authors and with the reliability importance of some notable components.

Method for Choosing a Balanced Set of Fault Tolerance Techniques for Distributed Computer Cystems

In the paper we consider a method for a reliability allocation problem (RAP) of distributed computer systems (DCS) under cost constraints. In this problem we maximize reliability of DCS under constraints of system cost. The article describes considered fault tolerance mechanisms. The mathematical formulation of RAP is provided. RAP is widely discussed in the literature. A detailed description of the method is ensured. The applied method is an evolutionary algorithm with an adaptive logic control procedure. The adaptive logic control procedure analyzes the results of evolutionary algorithm work in each generation and, based on this information, adjusts parameters. The key feature of the proposed method is the use of an adaptive hybrid genetic algorithm. The results of experiments with the implemented method are presented. This method was implemented as a pilot system which works in cooperation with DYANA simulation environment. Finally, future plans for the development of the presented method and tools are briefly described.

Reliability and economic‐driven switchable capacitor placement in distribution network

In this study, reliability and economic-driven capacitor allocation problem in electrical distribution system is investigated for a definite planning horizon considering several technical and economic aspects. Also, the system reliability modelling is performed based on a new approach, which is considering values of reactive component of currents flowing through branches of the feeder and applying different feeder's failure rate models. The aim of this study is minimising total cost of the system including system power loss cost, system risk cost, investment cost and maintenance cost. Herein, in order to achieve practical outcomes, inflation and interest rates as the economic factors considered in the planning, and yearly load growth, hourly and daily varying load, and customers’ load types are applied in the modelling, and also load model-based power flow is run rather than simple power flow. In this study, it is demonstrated that considering unreal model for the system load types or ignoring dependence of system reliability on the reactive component of current can significantly affect the results of the capacitor placement problem and also it can impose extra cost to the local distribution company.

Comparing Two Meta-Heuristic Approaches for Solving Complex System Reliability Optimization

Using meta-heuristic approaches to solve reliability and redundancy allocation problems (RRAP) has become attractive for researchers in recent years. In this paper, an optimization model is presented to maximize system reliability and minimize system cost simultaneously for multi-state weighted k-out-of-n systems. The model tends to optimize system design and maintenance activities over functioning periods that provides a dynamic modeling. A recently developed meta-heuristic approach imperialist competitive algorithm (ICA) and genetic algorithm (GA) are used to solve the model. The computational results have been compared to find out which approach is more appropriate for solving complex system reliability optimization models. It is shown that GA can find the better solution while ICA is a faster approach. In addition, an investigation is done on different parameters of the ICA.

A new method for reliability allocation of avionics connected via an airborne network

Avionics are connected via an airborne network, and the realization of their functions depends on successful data transmission through the network. Once the system reliability goal has been defined, reliability allocation must be performed to the subsystems and components. However, the widely used reliability allocation methods are not capable of dealing with complex connections between avionic subsystems. In this paper, an improved Advisory Group on the Reliability of Electronic Equipment (AGREE) allocation method is proposed for multi-mission networked avionics. In the proposed procedure, both the complexity and the importance of components are explicitly considered. Analytic algorithms and Monte Carlo simulation are applied to calculate the reliability of such a complex network structure. To determine the reliability allocation values, a heuristic algorithm is proposed, and an allocation adjustment procedure is provided to avoid inconsistent allocations caused by the same category of components involved in multiple missions of avionics. Our numerical study on A380 avionics, whose data are transmitted through Avionics Full Duplex Switched Ethernet (AFDX), shows that the proposed method is practical and quite efficient in handling such complex reliability allocation problems.

A Weapon System Reliability Allocation Based on Direct Searching Method

In this paper, through the analysis on the basic idea, characteristics of direct searching method, optimization calculation steps and constraint conditions have been concluded, and direct searching method was applied to the research on the reliability allocation problem in a complex weapon system to prove its feasibility. This paper is of great significance to the study of reliability distribution of weapon system.

Reliability optimization of binary state non-repairable systems: A state of the art survey

Article history: Received September 22 2013 Received in Revised Format April 6 2014 Accepted May 18 2014 Available online May 25 2014 The purpose of this paper is to discuss the state of the art on models and methods for reliability optimization problems (ROPs) including reliability allocation, redundancy allocation and reliability-redundancy allocation. There are literally few surveys for reviewing the literature of the ROPs. Tillman et al. (1980) classified the related papers by system structure, problem type, and solution methods, separately. In another work, Tzafestas (1980) reviewed system reliability optimization models and the optimization techniques. Yearout (1986) reviewed the literature related to standby redundancy. Kuo (2000) studied the system reliability optimization based on system structure and solution methods. Kuo and Prasad (2004) overviewed system reliability optimization methods. Later, Kuo (2007) reviewed recent advances in optimal reliability allocation problems. The present study adds to the previous literature surveys and focuses mainly on papers after year 2000 but with a quick review on the previous works so that the readers become familiar with the existing approaches. This research investigates the literature from system structure, system performance, uncertainty state and solution approach standpoints, simultaneously.