Reliability Allocation Method Research Articles

Reliability Allocation Method for Lightweight Propulsion System of Electric Aircraft

Reliability Allocation Method for Lightweight Propulsion System of Electric Aircraft

Research on Reliability Allocation Method for Traction Power Supply System of Electrified Railways in Mountainous Areas

Research on Reliability Allocation Method for Traction Power Supply System of Electrified Railways in Mountainous Areas

Reliability allocation method combined with real working conditions under rough probabilistic linguistic environment

Reliability allocation method combined with real working conditions under rough probabilistic linguistic environment

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.

A prioritized decision making method for reliability allocation: In optimistic and pessimistic view

Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.

A reliability allocation method for agricultural machinery based on AHP‐IFM

AbstractIn the product design phase, the available product failure data are limited, and the weight allocation method is often used to assign reliability targets to each unit. The integrated factors method (IFM) can calculate the reliability allocation weights considering multiple influencing factors simultaneously, but it cannot reflect the difference in the importance of each factor and each unit. The analytic hierarchy process (AHP) can calculate the relative importance weights of each factor and each unit. Combining the AHP with the IFM can make the IFM more adaptable to the system and more accurate for reliability allocation. However, the current combination method can cause two problems: the invalidation of the influencing factor weights and the imbalance of the unit weights. To address these two shortcomings, the AHP‐IFM proposed in this paper introduces a weight weakening factor and exponentially corrects the unit weights for units, which can better apply the relative importance weights of each influencing factor and each unit to the reliability allocation. The effectiveness of the AHP‐IFM is verified by comparison with existing methods and data. Finally, an AHP‐IFM applicable to agricultural machinery is proposed, and the reliability allocation of a no‐till seeder is used as a case to verify the feasibility of the AHP‐IFM.

Design and analysis of rocket engine system with electric pump as subsystem

Electric pump feed systems use the high-speed and high-performance motor to replace the traditional turbine as the driving machine of pumps. A new feed system scheme is proposed in which a small-flow electric pump pressurizes hydrogen peroxide to the gas generator. The system keeps the performance of the engine at a high level, while being able to achieve continuous regulation and depth regulation. The balance calculation method and reliability allocation method are used. The results show that, the power of the electric pump for fuel path and oxidizer path is 600.0 W and 1732.6 W, respectively. The total mass of the engine is 69.76 kg, and the mass percentage of the electric pump system is small, less than 3.2% of the overall system mass. The effect of the electric pump system on the engine mass is small, but it improves the engine regulation capability. The reliability of this engine system is calculated to be 0.9802, which is not less than the target value of 0.98 with a certain margin, according to the reliability assigned to each combined part.

Research on reliability allocation strategy for gear transmission system of high-speed train

High-speed train industry is in the stage of rapid development, and the reliability allocation strategy is helpful to improve the reliability of the system and reduce the economic cost of components. In this paper, the reliability allocation of gearbox transmission system of highspeed train is studied. Combining AGREE allocation method and reliability allocation method based on cost function, the reliability allocation of high-speed train gear transmission system is carried out. Considering the quantity, importance, cost and complexity of various parts of high-speed train gear transmission system, the feasibility factor of improving reliability based on the cost function allocation method was improved to acquire the improved cost function, and the reliability optimization allocation model based on the improved cost function was established. Compared with AGREE allocation method and the traditional allocation method based on cost function, the improved optimization allocation strategy proposed in this paper is more suitable for high-speed train gear transmission system.

A New Reliability Allocation Method Based on PSA and AHP for Fusion Reactors

Reasonable and feasible reliability index allocation is significant for improving safety and reducing costs for fusion reactors. Although the reliability index is allocated when designing some key systems, reliability allocation is not implemented from the overall layer to the system and component layers for fusion reactors. In this contribution, fusion reactors are divided into different layers by applying the Analytic Hierarchy Process (AHP); these layers include the overall layer, system layer and component layer, failure mode layer, etc. Combining the Probabilistic Safety Assessment (PSA) model for fusion reactors and AHP, the reliability index is allocated from the overall layer to the system and component layer. Firstly, a new reliability index allocation method based on PSA and AHP for fusion reactors is proposed. Secondly, the PSA model for an in-vessel LOCA accident of fusion reactors is selected as a case study to demonstrate the applications of the proposed method. Lastly, the relationship between PSA, items safety classification and reliability allocation are discussed. The allocation results indicate that the proposed method provides a more systematic reliability allocation scheme and contributes to improving the safety and economy of fusion reactors.

Reliability allocation method of comprehensive weight computer numerical control machine tool based on failure correlation and factor correlation

AbstractAccording to the shortage of independent hypothesis allocation models between influence factors and subsystems, a reliability allocation method considering influence factor correlation and subsystem failure correlation is proposed. The CNC (Computer Numerical Control) machine tool is taken as the research object. Using Copula function to analyze failure correlation analysis between subsystems, establish subsystem complete reliability model and integrated importance measure model under failure correlation. The four factors of influencing reliability allocation are subsystem complexity, integrated importance measure of subsystem based on failure correlation, failure frequency, and specific gravity ratio of failure downtime. The correlation analysis among the influencing factors was carried out by using gray correlation theory, and the subjective weight of the subsystem was determined. The IEW‐VIKOR (Information Entropy Weight‐Vlsekriterijumska Optimizacija I Kompromisno Resenje) method is used to determine the objective weights of subsystems. The comprehensive weight of the subsystem is also obtained through combinatorial empowerment. The reliability allocation of the CNC machine tool subsystem was carried out according to the failure correlation reliability model, and the results of failure independence and failure correlation hypothesis allocation were compared and analyzed. When the reliability index is the same, the reliability allocation method proposed in this paper can assign lower reliability to each subsystem, which is of great significance to improve the reliability of CNC machine tools and reduce the difficulty of reliability design

A new reliability allocation method for machine tools based on ITrFNs and AHP-GRA

A new reliability allocation method for machine tools based on ITrFNs and AHP-GRA

Reliability allocation method based on linguistic neutrosophic numbers weight Muirhead mean operator

This article presents a reliability allocation method based on Linguistic Neutrosophic Numbers Weight Muirhead mean operator. In order to solve the problem of insufficient consideration of influencing factors in traditional reliability allocation methods, six influencing factors are proposed in the proposed method. Using Linguistic Neutrosophic Numbers, the fuzzy information in the process of reliability allocation can be evaluated completely. The Linguistic Neutrosophic Numbers Weight Muirhead mean operator proposed by this article can process the scoring results by considering the correlation and weight of influencing factors. With the introduction of the safety factor, the exact values of the allocation results can be transformed into interval values. Finally, an example is given to verify the superiority of the proposed method.

Reliability assignment of a heavy-duty CNC machine tool spindle system based on fault tree analysis

Research on the distribution of machine tool reliability indexes is of great significance to improve the reliability of machine tools in the design and manufacture stages. Owing to the complex structure of heavy-duty CNC machine tools, multi-source and heterogeneous failure causes, etc., the traditional single method cannot get accurate results. In this paper, based on the FTA method, a three-level machine tool fault tree model is established to carry out research on reliability index assignment. Then, as the levels progress, the distribution of reliability indicators is based on probability importance analysis, reliability redistribution method, and AHP respectively. Finally, the top-down reliability assignment results are obtained. After analysis, the structure obtained by combining multiple reliability allocation methods is more in line with the actual situation. According to the results, the weak parts of the machine tool are designed and improved, thereby improving the reliability of the machine tool.

Application of integrated factor evaluation–analytic hierarchy process–T-S fuzzy fault tree analysis in reliability allocation of industrial robot systems

Aiming at the defects (only two kinds of state, i.e., normal or fault) of existed reliability allocation methods without considering the intermediate degradation process, a methodology named integrated factor evaluation–analytic hierarchy process–T-S fuzzy fault tree analysis (IFE-AHP-T-S fuzzy FTA) is proposed to allocate the reliability index of industrial robot systems (IRSs) which have multiple fault states. Firstly, the reliability model of IRSs is established and the allocation principle of reliability index is discussed. Secondly, two-layer IFE model is established considering the degradation of mechanical structure and multi-state fault of IRSs to evaluate the technical merit of different subsystems. The hesitant fuzzy language set is adopted to reduce the subjectivity of expert evaluation process, which have the ability of dealing with uncertain information. Then, the AHP is proposed to allocate different weights for influence factors, and the T-S fuzzy FTA is presented to calculate fault probability and mean time between failures (MTBF) in the process of weight allocation of reliability index for IRSs and six subsystems. Finally, multi-state reliability index allocation of IRSs is completed. This investigation has a significance for reducing the fault probability and unsafe factors, and provides a theoretical basis for the whole life cycle design of IRSs.

A two-stage reliability allocation method for remanufactured machine tools integrating neural networks and remanufacturing coefficient

Reliability allocation is an important task that needs to be done in the design phase of machine tool remanufacturing to ensure that remanufactured machine tools meet the reliability target. However, unlike new machine tool products, remanufactured machine tools have high uncertainty and small samples, and traditional reliability methods are not suitable for remanufactured machine tools. This paper aims to propose an improved reliability allocation method for remanufactured machine tools integrating neural networks and remanufacturing coefficient. With the fault tree analysis (FTA) model constructed, the fault of remanufactured machine tools can be divided into three levels: system-level, subsystem-level, and part-level. The three-layer feedforward artificial neural network is adopted to allocate system reliability to subsystem-level. When reliability is allocated from subsystem-level to part-level, the remanufacturing comprehensive evaluation system and a remanufacturing coefficient that takes into account the characteristics of remanufactured components are introduced. Finally, the proposed method is illustrated in a case of reliability allocation for remanufactured NC gear hobbing machines. Moreover, the results show that the reliability target can be achieved and the growth of reliability can be guaranteed through the proposed method.

A Prioritized Decision Making Method for Reliability Allocation: in Optimistic and Pessimistic View

Reliability allocation is a very important problem during early design and development phases of a system. There are several reliability allocation techniques which are used to achieve the target reliability. The feasibility of objectives (FOO) technique is one of them that is widely used to perform system reliability allocation. But this technique has two fundamental shortcomings. The first is the measurement scale and the second is that it does not consider the order weight of the reliability allocation factors. The prioritization of the factors is also an important topic in decision making. Practically, all factors in multi-criteria decision making (MCDM) are not in the same priority level. Hence, in decision making situation, it is usual for decision makers to consider different priority factors. So, considering the prioritization of the factors, a reliability allocation method is proposed here to overcome the shortcomings of the FOO technique. Also, a case study on reliability allocation in airborne radar system is considered here to verify the efficiency of the proposed approach. Finally, the results are calculated in different optimistic and pessimistic view point and compared with the FOO technique. This comparison exhibits the advantages and supremacy of the proposed approach.

Research on the Reliability Allocation Method of Smart Meters Based on DEA and DBN

Reliability allocation can reasonably determine the reliability index of each unit in the system to ensure product quality in design, manufacturing, testing and acceptance. In the design process of the smart meter, the preliminary reliability allocation results may be unreasonable, so in the middle and later stages of the design stage, the reliability needs to be reallocated. The traditional allocation method has some limitations, such as strong subjectivity, large amount of calculation and too much reliance on expert judgment. In order to solve these problems, this paper presents a multi-method fusion method of reliability allocation. First, this paper uses the goal-oriented methodology (GO methodology) to integrate dynamic Bayesian networks (DBNs) to predict the reliability of smart meters. Second, a data envelopment analysis (DEA) reliability allocation model is established, the posterior probability obtained by DBN reasoning together with the failure rate and structural complexity of each unit are used as the output indicators of this model. Finally, the reliability allocation weight is calculated by using the efficiency value obtained from the DEA reliability allocation model. The validity and accuracy of this method is verified by an accelerated life test. This provides a new idea for reliability reallocation of smart meters.

Research on the reliability allocation calculation method of a wind turbine generator set based on a vine copula correlation model

AbstractTo consider the failure correlation among key subsystems, based on the reliability allocation method of the series system, a wind turbine reliability allocation calculation method based on the vine copula correlation model is proposed. The reliability modeling method of the series system is adopted to model the reliability of each subsystem, combined with the copula function to model the correlation between the variables, and then, the multidimensional variable problem is converted into the two‐dimensional variable problem through the vine copula function. The reliability calculation model of the copula function model, under the influence of factors such as the complexity, importance, and failure hazard of each subsystem, allocates the reliability of the key component systems of the wind turbine generator set. Finally, through three allocation methods based on the independent, multivariate copula function and vine copula function and other distribution methods, the calculation and analysis of the wind turbine generator set are performed. The results show that the allocated control system has the lowest reliability, and the tower has the highest reliability; compared with the assumption of the independent allocation method, the allocation result of this paper's method is lower; compared with the allocation method of the multidimensional copula function, the allocated failure rate is increased by more than 20%. This paper verifies that the proposed method is not only effective and reasonable but also more consistent with the actual situation.

A new reliability allocation method for machine tools using the intuitionistic trapezoidal fuzzy numbers and TOPSIS

The reliability allocation of machine tools which is a multi-attribute decision-making problem has great significance in designment of machine tools. This paper integrates the intuitionistic trapezoidal fuzzy numbers and performance sorting technique based on similar ideal solutions to achieve the flexible allocation of machine tools reliability. Firstly, intuitionistic trapezoidal fuzzy numbers are employed to integrate decisions made by multiple decision-makers and fuzzy information of their preferences. Then, intuitionistic trapezoid fuzzy numbers’ expectations are treated as the weights of criteria. Finally, performance sorting technique based on similar ideal solutions is used to obtain the reliability allocation weight of every subsystem. To investigate the efficacy and simplicity of the provided approach, reliability distribution in a CNC machine tool is introduced as an example to explain its specific contents. It can be concluded that the provided method is more precise and convenient by comparing the results of this approach with those obtained by analytic hierarchy process method.

An information fusion reliability allocation method considering limited sample size circumstances

AbstractAs an essential part in product reliability design procedure, reliability allocation can connect the reliability index between the overall product and its multiple subsystems. To obtain a reasonable reliability allocation scheme, especially for limited sample size circumstances commonly encountered in aeronautic and astronautic fields, an information fusion allocation method is constructed in the current study. Grey relational analysis (GRA) is incorporated to analyze objective data, while analytic hierarchy process (AHP) is introduced to implement subjective data analysis. Then a final allocation scheme is derived by fusion of the binary information sources. A real application regarding an aeronautic product reliability allocation is given. The sensitivity of allocation result to limited life information circumstances and comparative analysis with reference methods are implemented to demonstrate the reasonability and effectiveness.