A novel approach for analyzing the behavior of industrial systems using weakest t-norm and intuitionistic fuzzy set theory

The present work investigates the various reliability parameters of industrial systems in terms of membership and non-membership functions by using α-cut and the weakest t-norm based arithmetic operations on triangular intuitionistic fuzzy sets. As the available information about the constituent components of the system is most of the time imprecise, incomplete, vague and conflicting, the management decisions are based on experience. Thus, the objective of this paper is to quantify the uncertainties that make the decisions realistic, generic and extensible for the application domain. Sensitivity of system performance has also been analyzed for showing the effect of taking wrong combinations of reliability parameters. The obtained results computed by the proposed approach are compared with the existing methodologies. The approach has been illustrated through a case study for supremacy.     

Prediction of system reliability using failure types of components based on Weibull lifetime distribution

Modern products are complicated and standards of reliability are higher than ever before. Therefore, prediction of system reliability is essential, especially as the time available for developing products has decreased. Most of the previous studies assumed that the causes of failure are random. That is, the failure rates of components follow exponential distributions. To reflect various types of failure such as initial, random, or wear-out failure, we developed a novel procedure for estimating system reliability based on the Weibull distribution. We analyzed the effect of component selection on the types of system failure. Finally, we verified the proposed method by analyzing warranty data on actual Korean products.     

The weakest t-norm based intuitionistic fuzzy fault-tree analysis to evaluate system reliability

In this paper, a new approach of intuitionistic fuzzy fault-tree analysis is proposed to evaluate system reliability and to find the most critical system component that affects the system reliability. Here weakest t-norm based intuitionistic fuzzy fault tree analysis is presented to calculate fault interval of system components from integrating expert's knowledge and experience in terms of providing the possibility of failure of bottom events. It applies fault-tree analysis, α-cut of intuitionistic fuzzy set and T(ω) (the weakest t-norm) based arithmetic operations on triangular intuitionistic fuzzy sets to obtain fault interval and reliability interval of the system. This paper also modifies Tanaka et al.'s fuzzy fault-tree definition. In numerical verification, a malfunction of weapon system "automatic gun" is presented as a numerical example. The result of the proposed method is compared with the listing approaches of reliability analysis methods.     

机械系统模糊可靠度的估计模型

对机械系统组成单元的含义作了新的定义,建立单元模糊可靠度及其置信区间的估计模型;建立了机械领域常见系统的模糊可靠度估计模型;通过对单元模糊可靠度的直接估计,利用所建立的估计模型可以快速方便地预测出系统的模糊可靠度.实例分析给出了估计模型的使用方法,并显示模型的有效性.     

A novel approach for remanufacturing process planning considering uncertain and fuzzy information

Frontiers of Mechanical Engineering - Remanufacturing, as one of the optimal disposals of end-of-life products, can bring tremendous economic and ecological benefits. Remanufacturing process...     

液压系统可靠性模糊设计与评价方法

液压系统的可靠性是保证设备整机工作可靠的关键因素,液压系统可靠性模糊设计比常规可靠性设计更科学更合理.以工程机械典型液压系统为例,基于模糊数学理论和方法,分析了常规可靠性设计的不足,提出了液压系统可靠性模糊设计的思想和方法,运用模糊理论对液压系统进行描述并计算出系统的模糊可靠度,给出了系统模糊可靠度预测与分配的方法,建立了系统可靠性的模糊评价模型.     

两液压泵贮备系统模糊可靠性仿真研究

针对常规可靠性理论的局限性,采用模糊可靠性理论来分析液压系统可靠性问题。首先,建立了两部件贮备系统最为通用的模型——考虑优先权问题与开关不完全可靠两部件温贮备可修系统模糊可靠性模型,用以分析两液压泵贮备系统模糊可靠性,通过分析得到系统模型的Markov链以及状态转移矩阵。然后,运用模糊数学基本原理、Laplace变换等,推导得到该系统模型模糊可靠性指标的计算公式。最后,进行了计算机仿真试验,仿真试验结果表明:利用模糊可靠性理论分析液压系统模糊可靠性更为严谨,同时进行了参数灵敏度仿真分析,为液压系统可靠性评价与设计提供一定借鉴。     

A novel segmentation approach for noisy medical images using Intuitionistic fuzzy divergence with neighbourhood‐based membership function

Medical image segmentation demands higher segmentation accuracy especially when the images are affected by noise. This paper proposes a novel technique to segment medical images efficiently using an intuitionistic fuzzy divergence–based thresholding. A neighbourhood‐based membership function is defined here. The intuitionistic fuzzy divergence–based image thresholding technique using the neighbourhood‐based membership functions yield lesser degradation of segmentation performance in noisy environment. Its ability in handling noisy images has been validated. The algorithm is independent of any parameter selection. Moreover, it provides robustness to both additive and multiplicative noise. The proposed scheme has been applied on three types of medical image datasets in order to establish its novelty and generality. The performance of the proposed algorithm has been compared with other standard algorithms viz. Otsu's method, fuzzy C‐means clustering, and fuzzy divergence–based thresholding with respect to (1) noise‐free images and (2) ground truth images labelled by experts/clinicians. Experiments show that the proposed methodology is effective, more accurate and efficient for segmenting noisy images.     

基于模糊评价法的CNC系统的可靠性分析

这里针对CNC系统模糊综合评价的典型模型，从可靠性指标、可靠性考核等方面阐述了评价过程中的模糊因素，给出了考核指标体系及选取原则，建立了考核模型，并给出了隶属函数及权重的确定方法。文中给出了模糊综合评价实例，为CNC系统的可靠性设计提供了依据。     

A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method

Plant location selection, the process of finding a suitable location for plant of a project has a strong influence on the success of industrial venture with the goal to minimize cost and maximize the use of resources. Thus, plant location selection problem is a multicriteria decision-making problem involving several conflicting criteria on which decision makers' knowledge is vague and imprecise. Therefore, in this study, the elimination and choice translating reality (ELECTRE) method is proposed with intuitionistic fuzzy sets for selection of appropriate plant location in group decision-making environment to tackle uncertainty of the information provided by decision makers and a plant location selection problem is considered to illustrate the proposed intuitionistic fuzzy-ELECTRE method. The ratings of alternatives with respect to each criterion and the weights of each criterion are taken as linguistic terms further characterized by triangular intuitionistic fuzzy sets.     

A fuzzy integrated decision-making support system for scheduling of FMS using simulation

In the complex environment of an automated manufacturing system, decision-making is one of the most important and difficult tasks of a manager in general or a scheduler in particular. Flexible Manufacturing Systems (FMSs) are highly automated and expensive systems. The high investment cost of a FMS justifies the use of computer simulation support. This paper investigates the operational problems of FMSs through simulation, and different combinations of scheduling rules are evaluated by a fuzzy integrated decision-making support system.     

基于模糊数学的接触网零部件可靠度计算模型

铁路接触网零部件的可靠性是铁路安全运行的重要因素,然而传统的可靠度计算模型不能很好的与实际相符.将模糊数学的理论应用于对接触网零部件可靠度计算上,建立了应力和强度均为正态分布、不同隶属函数下的模糊可靠度计算模型,为接触网零部件可靠度的计算提供了理论依据.通过抱箍类零件可靠度的计算,对比分析了模糊可靠度计算模型的正确性.     

A fuzzy hybrid group decision support system approach for the supplier evaluation process

The quality and delivery performance of a typical company depends largely on the capability of its suppliers. It is therefore important for a company to evaluate the performance of its existing suppliers. However, the problem of supplier evaluation is rather complex when a group of decision makers responsible for these suppliers are geographically dispersed. Evaluating decisions requiring the elicitation of vague and imprecise linguistic information expressed in fuzzy terms. For this purpose, a hybrid fuzzy group decision-making approach for supplier evaluation is proposed, integrating the fuzzy analytic hierarchy process (F-AHP) and the fuzzy preference-ranking-organization-method-for-enrichment-of-evaluation (PROMETHEE) group decision support system (F-PROMETHEE GDSS) method. F-AHP is used to determine the weight of multiple criteria while F-PROMETHEE GDSS is applied for the final ranking of suppliers from a group decision viewpoint. The approach advances the supplier evaluation context in two aspects. First, it treats each decision maker uniquely in terms of the preference function and threshold levels. Second, it provides rapid communication between teams through video conferencing. The hybrid approach is used to evaluate the suppliers of a dairy company.     

Identification and control of dynamical systems using different architectures of recurrent fuzzy system

Fuzzy logic based systems are very widely used for modeling and control of complex non-linear, plants. Fuzzy systems require the knowledge about the structure of the dynamic plant in order to achieve fruitful results. Recurrent Fuzzy systems (RFS) are a variation of fuzzy systems and have the ability to model and control dynamic plants without using the information about the structure of the plant. This paper presents identification and control of non-linear dynamical systems using two different architectures of recurrent fuzzy system (RFS). It highlights the importance of RFS over the conventional type-1 fuzzy based system. The objective of system identification as well as control has been achieved using both the architectures of RFS and the simulation results clearly show their efficiency. This paper also highlights yet another advantage of RFS over the conventional type-1 fuzzy systems which comes into light when dealing with higher order systems. The paper explains how the computational complexity can be greatly reduced by using RFS for higher order dynamical systems. A comparative analysis between the conventional type-1 fuzzy system and the two recurrent fuzzy systems has also been performed.     

考虑共因失效的新型连续时间动态 贝叶斯网络可靠性分析方法

现代系统失效行为复杂,动态性与相关性并存。首先为直观准确地刻画分析系统中的动态失效行为,提出新型连续时间动态贝叶斯网络分析方法,利用节点时序条件概率表刻画事件关系,进而提出基于节点时序条件概率表规则执行度与冲激函数抽样性质的子节点故障概率、根节点后验概率及重要度的计算方法;进一步,针对共因失效引起的系统相关性失效行为,提出考虑共因失效的新型连续时间动态贝叶斯网络分析方法,解决系统失效逻辑动态性和相关性的重叠问题。通过与贝叶斯网络、离散时间动态贝叶斯网络分析方法、Markov链、Monte Carlo法对比,验证所提方法的可行性与优越性。最后,对动态失效相关系统进行可靠性分析,结果表明,本文方法能够直观有效地刻画动态性与相关性失效行为,得到准确的系统可靠性指标,考虑共因失效相比于忽略共因失效,在任务时间为5×10~6 h时能够提高系统29%的可靠性分析精度,更加符合实际。     

A novel non-probabilistic approach using interval analysis for robust design optimization

A technique for formulation of the objective and constraint functions with uncertainty plays a crucial role in robust design optimization. This paper presents the first application of interval methods for reformulating the robust optimization problem. Based on interval mathematics, the original real-valued objective and constraint functions are replaced with the interval-valued functions, which directly represent the upper and lower bounds of the new functions under uncertainty. The single objective function is converted into two objective functions for minimizing the mean value and the variation, and the constraint functions are reformulated with the acceptable robustness level, resulting in a bi-level mathematical model. Compared with other methods, this method is efficient and does not require presumed probability distribution of uncertain factors or gradient or continuous information of constraints. Two numerical examples are used to illustrate the validity and feasibility of the presented method.     

A novel gas-loading system for mechanically closing of various types of diamond anvil cells

Loading of gases in diamond anvil cells is a complicated but necessary task to obtain hydrostatic conditions for high-pressure measurements. A simple in operation, safe, and universal gas-loading system has been designed and constructed. Innovations were introduced to simplify the loading procedure up to the "three-button" mode.     

An emotional learning-based fuzzy inference system for improvement of system reliability evaluation in redundancy allocation problem

A major challenge in reliability based optimal design problems is the evaluation of system reliability given a system design. Reliability evaluator is a tool, a model, or a system that analyses the reliability of a system given a specified system design. Reliability evaluator usually is embedded in reliability optimization model and it can be seen as a computational engine that can provide optimization model with the value of its objective function. Enhancing performance of the reliability evaluator in optimization models is important as the overall performance of optimization model is significantly affected by its embedded reliability evaluator. The purpose of this paper is to present an approach to improve the accuracy and generalization ability of evaluating system reliability in redundancy allocation problem. The main idea is to employ emotional learning-based fuzzy inference system (ELFIS) to improve performance of reliability evaluator. A series–parallel case reliability–redundancy allocation is considered and the proposed ELFIS is validated by comparison of its results with those of multi-layer perceptron neural network and adaptive network-based fuzzy inference system. Normalized mean squared error and mean absolute percentage error show that ELFIS can bring better accuracy in evaluating the system reliability for those reliability-based optimal designs.