Reliability analysis of waste clean-up manipulator using genetic algorithms and fuzzy methodology

In this paper, the reliability analysis of waste clean-up manipulator has been performed using Real Coded Genetic Algorithms and Fuzzy Lambda Tau Methodology. The optimal values of mean time between failures and mean time to repair are obtained using genetic algorithms. Petri Net tool is applied to represent the interactions among the working components of the system. To enhance the relevance of the reliability study, triangular fuzzy numbers are developed from the computed data, using possibility theory. The use of fuzzy arithmetic in the Petri Net model increases the flexibility for application to various systems and conditions. Various reliability parameters (failure rate, repair time, mean time between failures, expected no. of failures, reliability and availability) are computed using Fuzzy Lambda Tau Methodology. Sensitivity analysis has also been performed and the effects on system mean time between failures are addressed. The adopted methodology improves the shortcomings/drawbacks of the existing probabilistic approaches and gives a better understanding of the system behavior through its graphical representation.     

Fuzzy modeling of system behavior for risk and reliability analysis

The main objective of the article is to permit the reliability analyst's/engineers/managers/practitioners to analyze the failure behavior of a system in a more consistent and logical manner. To this effect, the authors propose a methodological and structured framework, which makes use of both qualitative and quantitative techniques for risk and reliability analysis of the system. The framework has been applied to model and analyze a complex industrial system from a paper mill. In the quantitative framework, after developing the Petrinet model of the system, the fuzzy synthesis of failure and repair data (using fuzzy arithmetic operations) has been done. Various system parameters of managerial importance such as repair time, failure rate, mean time between failures, availability, and expected number of failures are computed to quantify the behavior in terms of fuzzy, crisp and defuzzified values. Further, to improve upon the reliability and maintainability characteristics of the system, in depth qualitative analysis of systems is carried out using failure mode and effect analysis (FMEA) by listing out all possible failure modes, their causes and effect on system performance. To address the limitations of traditional FMEA method based on risky priority number score, a risk ranking approach based on fuzzy and Grey relational analysis is proposed to prioritize failure causes.     

Predicting uncertain behavior of industrial system using FM—A practical case

As such the reliability of system is affected by many factors such as design, manufacturing, installation, commissioning, operation and maintenance. Consequently it may be extremely difficult if not impossible to model, analyze and predict the failure behavior of system.To this effect, the authors presented a structured framework which makes use of fuzzy methodology (FM), an approximate reasoning tool to deal with the imprecise, uncertain and subjective information related to system performance. The component related objective events are modeled with the help of the Petri net model of the system. Various parameters of managerial importance such as repair time, failure rate, mean time between failures, availability and expected number of failures are computed to quantify the uncertain behavior of system. Further, to improve upon the reliability characteristics of the system, in-depth qualitative analysis of unit is carried out using failure mode and effect analysis (FMEA) by listing all possible failure modes and their causes. A decision support system based on fuzzy set theory is developed to counter the limitations of traditional FMEA. The framework has been applied to model and analyze a real complex industrial system from paper mill.     

油井压力测试系统可靠性框图分析

目前用于测试射孔压裂时动态压力数据的石油井下压力测试系统得到了广泛的应用,但对其可靠性的分析研究还是空白.针对这一问题,采用可靠性框图分析技术对测试系统的可靠性进行分析.通过深入分析系统的组成结构和逻辑功能关系,建立测试系统的可靠性框图模型.在此基础上,依据元器件应力分析方法对可能引起系统故障的元器件的失效率进行逐个分析和计算,最后得到测试系统的失效率和平均无故障工作时间.研究结果为测试系统的可靠性评估提供了理论依据.     

Dependability and performance measures for the databasepractitioner

We estimate the availability, reliability, and mean transaction time (response time) for repairable database configurations, centralized or distributed, in which each service component is continuously available for repair. Reliability, the probability that the entire transaction can execute properly without failure, is computed as a function of mean time to failure (MTTF) and mean time to repair (MTTR). Mean transaction time in the system is a function of the mean service delay time for the transaction over all components, plus restart delays due to component failures, plus queuing delays for contention. These estimates are potentially applicable to more generalized distributed systems     

Performance and behavior analysis of repairable industrial systems using Vague Lambda–Tau methodology

To remain competitive and to provide timely and accurate services, the decision maker or system analyst view the reliability and maintainability issues as a part of corporate quest to improve quality of the products/processes and services delivered. But the collected or available data available from the historical records are mostly uncertain, limited and imprecise in nature. Thus in such situation(s), it is difficult, if not impossible, to analyze the behavior and performance of the system up to desired degree of accuracy. Thus attempt has been made by the author for analyzing the behavior and performance of the system using Vague Lambda–Tau methodology. Intuitionistic fuzzy set theory has been used for representing the classical(crisp) data into triangular fuzzy numbers because intuitionistic sets are characterized by a truth membership function and false membership functions (non-membership functions) so that sum of both values is less than 1. Sensitivity analysis has also been performed and the effects on system mean time between failures are addressed. The performance analysis of the system has been investigated through a composite measure of reliability, availability and maintainability (RAM) called RAM-Index which explore the effect of failure/repair rates on system performance. Based on their performance, the most critical component of the system has been investigated. The methodology improves the shortcomings of the existing probabilistic approaches and gives a better understanding of the system behavior through its graphical representation. The pulping unit of a paper mill situated in a northern part of India, producing approximately 200 ton of paper per day, has been considered to demonstrate the proposed approach. The results obtained by proposed approach are compared with the existing fuzzy Lambda–Tau and the crisp methodologies.     

Tuple switching network—When slower may be better

This paper reports an application dependent network design for extreme scale high performance computing (HPC) applications. Traditional scalable network designs focus on fast point-to-point transmission of generic data packets. The proposed network focuses on the sustainability of high performance computing applications by statistical multiplexing of semantic data objects. For HPC applications using data-driven parallel processing, a tuple is a semantic object. We report the design and implementation of a tuple switching network for data parallel HPC applications in order to gain performance and reliability at the same time when adding computing and communication resources. We describe a sustainability model and a simple computational experiment to demonstrate extreme scale application’s sustainability with decreasing system mean time between failures (MTBF). Assuming three times slowdown of statistical multiplexing and 35% time loss per checkpoint, a two-tier tuple switching framework would produce sustained performance and energy savings for extreme scale HPC application using more than 1024 processors or less than 6 hour MTBF. Higher processor counts or higher checkpoint overheads accelerate the benefits.     

考虑维修优先权的多状态温贮备系统可靠性模型

针对工程应用中装备维修和保养两类活动具备不同优先级这一问题,考虑单一维修台可进行维修和保养两类工作,其中维修具有优先权.以多状态温贮备系统为研究对象,采用可近似拟合任意分布的Phase-type(PH)分布构建一种描述能力更强的系统可靠性模型,得出系统稳态可用度、系统故障率、平均故障间隔时间等一系列可靠性指标的解析表达式.最后利用算例验证PH分布的适用性,演示系统可靠性函数随时间的变化趋势,并讨论维修台工作速率对系统故障率、稳态可用度、维修台忙期稳态概率和平均故障间隔时间的影响.算例结果表明,所提模型具有较广泛的应用价值.     

低成本冗余结构可信性定量属性分析

本文分析了六种低成本冗余结构的可信性的定量属性，包括可靠度、MTTF、可用度、MTBF、可维度和MTTR。这些低成本冗余结构是；冷备用双模动态冗余结构、热备用双模动态冗余结构、双侯静态冗余结构、双模比较──单模切换结构、双摸负载分担──单模切换结构和N＋1冗余结构。根据每种结构所可能具有的维修特性，分别给出了相应可信性属性在不可维和可维情况下的计算表达式。     

基于模糊神经网络的WEDM可靠度预计

为了准确预计电火花线切割机床(WEDM)的可靠度,建立基于自适应模糊神经网络的可靠度预计模型。该模型以平均无故障时间为输入,以可靠度为输出,通过神经网络自适应训练获得适合WEDM可靠度预计的平均无故障间隔时间隶属函数。仿真结果表明,该模型的预计精度较高,与应用神经网络的WEDM可靠度预计结果相比,提高了96.4%。     

Modeling optimal release policy under fuzzy paradigm in imperfect debugging environment

ContextIn this study, a software optimal release time with cost-reliability criteria has been discussed in an imperfect debugging environment.ObjectiveThe motive of this study is to model uncertainty involved in estimated parameters of the software reliability growth model (SRGM).MethodInitially the reliability parameters of SRGM are estimated using least square estimation (LSE). Considering the uncertainty involved in the estimated parameters due to human behavior being subjective in nature and the dynamism of the testing environment, the concept of fuzzy set theory is applicable in developing SRGM. Finally, using arithmetic operations on fuzzy numbers, the reliability and total software cost are calculated.ResultsVarious reliability measures have been computed at different levels of uncertainties, and a comparison has been made with the existing results reported in the literature.ConclusionIt is evident from the results that a better prediction of reliability measures, namely, software reliability and total software cost can be made under the fuzzy paradigm.     

Stochastic Analysis of a System with Redundant Robots, One Built-in Safety Unit, and Common-Cause Failures

This paper presents reliability and availability analyses of a mathematical model representing a robot-safety system having n-redundant robots and one built-in safety unit with common-cause failures. At least k robots must function successfully for the overall robot system success. The system failure rates and the partially failed system repair rates are assumed constant and the failed system repair time is assumed arbitrarily distributed. Markov and supplementary variable methods were used to develop generalized expressions for state probabilities, system availabilities, reliability, and mean time to failure. Some plots of these expressions are shown.     

A generalized-exponential decomposition method for the analysis of inhomogeneous assembly/disassembly systems with unreliable machines and finite buffers

This paper presents a new approximate analytical method for the performance evaluation of inhomogeneous assembly/disassembly (A/D) systems with machines subject to failures and finite buffers. Processing times of machines in these systems are deterministic but not identical. Times between failures and times to repair are both assumed to be exponentially distributed. The method developed in this paper provides a generalized approach for analyzing A/D systems. Unlike the previous work on this subject, generalized exponential distributions are adopted instead of exponential distributions to approximate the repair time distributions of the fictitious machines. As a result the proposed method can handle the situation where the orders of magnitude of machines’ reliability parameters (mean times between failures and mean times to repair) are not at the same level. A new algorithm is also developed to improve the convergence reliability and efficiency of the method. Extensive numerical experiments and simulation have been carried out to illustrate that the method proposed for A/D systems is quite accurate and efficient.     

Software-based rerouting for fault-tolerant pipelined communication

This paper presents a software-based approach to fault-tolerant routing in networks using wormhole or virtual cut-through switching. When a message encounters a faulty output link, it is removed from the network by the local router and delivered to the messaging layer of the local node's operating system. The message passing software can reroute this message, possibly along nonminimal paths. Alternatively, the message may be addressed to an intermediate node, which will forward the message to the destination. A message may encounter multiple faults and pass through multiple intermediate nodes. The proposed techniques are applicable to both obliviously and adaptively routed networks. The techniques are specifically targeted toward commercial multiprocessors where the mean time to repair (MTTR) is much smaller than the mean time between router failures (MTBF), i.e., it is sufficient to tolerate a maximum of three failures. This paper presents requirements for buffer management, deadlock freedom, and livelock freedom. Simulation results are presented to evaluate the degradation in latency and throughput as a function of the number and distribution of faults. There are several advantages of such an approach. Router designs are minimally impacted, and thus remain compact and fast. Only messages that encounter faulty components are affected, while the machine is ensured of continued operation until the faulty components can be replaced. The technique leverages existing network technology, and the concepts are portable across evolving switch and router designs. Therefore, we feel that the technique is a good candidate for incorporation into the next generation of multiprocessor networks     

Reliability and sensitivity analysis of a repairable system with imperfect coverage under service pressure condition

This paper investigates reliability and sensitivity analysis of a repairable system with imperfect coverage under service pressure condition. Failure times and repair times of failed units are assumed to be exponentially distributed. As a unit fails, it may be immediately detected, located and replaced with a coverage probability c by a standby if one is available. When the repairmen are under the pressure of a long queue, the repairmen may increase the repair rate to reduce the queue length. We derive the explicit expressions for reliability function and mean time to system failure (MTTF). Various cases are analyzed to study the effects of different parameters on the system reliability and MTTF. We also accomplish sensitivity analysis and relative sensitivity analysis of the reliability characteristics with respect to system parameters.     

Performance and reliability improvement by using asynchronous algorithms in disk buffer cache memory

This paper proposes performance and reliability improvement by using new algorithms for asynchronous operations in disk buffer cache memory. These algorithms allow for writing the files into the buffer cache by the processes and consider the number of active processes in the system and the length of the queue to the disk buffer cache. Writing the contents of the buffer cache to the disk depends on the system load and the write activity. Performance and reliability measures including the elapsed time of writing a file into the buffer cache, the waiting time to start writing a file, and the mean number of blocks written to the disk between system failures are used to show performance and reliability improvement by using the algorithms. Sensitivity analysis is used to influence the algorithms' design. Examples of real systems are used to show the numerical results of performance and reliability improvement in different systems with various disk cache parameters and file sizes.     

System reliability for non-repairable multi-state series–parallel system using fuzzy Bayesian inference based on prior interval probabilities

In this article, the fuzzy concepts are applied in analysis of the system reliability problem. The fuzzy number is used to construct the fuzzy reliability of the non-repairable multi-state series–parallel system (NMSS). The fuzzy failure rate function is represented by an exponential fuzzy number. By using this innovative approach, the fuzzy system reliability of NMSS is created. In order to analyse this fuzzy system reliability, the fuzzy Bayesian point estimate of fuzzy system reliability is made by the conventional Bayesian formula. And, the posterior fuzzy system reliability of NMSS is developed by Bayesian inference with fuzzy probabilities. Finally, the performance of the method is measured by the mean square error of fuzzy Bayesian point estimate for the fuzzy system reliability of NMSS.     

Fuzzy dynamic fault tree analysis for electro-mechanical actuator based on algebraic model with common-cause failures

This paper deals with fuzzy dynamic fault tree analysis for the electro-mechanical actuator with common-cause failures to provide fast fault location strategy. To fully describe the level of uncertainty of basic events, triangle fuzzy set is used. Temporal operators are defined, algebraic model is used to model and analyze dynamic fault tree of the electro-mechanical actuator and is general to all kind of life distribution. An innovative common-cause gate with incomplete common-cause under consideration is raised and it can also match the algebraic model analysis method. Fuzzy probability importance is computed by level-progressive strategy, and complexity of solving entirely is avoided and calculation time is reduced. The analysis result shows that the method is flexible and effectively done with the reliability analysis of electro-mechanical actuator and can provide suggestions for faults location.     

主动容错副本存储系统的可靠性分析模型

主动容错机制通过预先发现即将故障的硬盘来提醒系统提前迁移备份危险数据,从而显著提高存储系统的可靠性。针对现有研究无法准确评价主动容错副本存储系统可靠性的问题,提出几种副本存储系统的状态转换模型,然后利用蒙特卡洛仿真算法实现了该模型,从而模拟主动容错副本存储系统的运行,最后统计系统在某个运行时期内发生数据丢失事件的期望次数。采用韦布分布函数模拟设备故障和故障修复事件的时间分布,并定量评价了主动容错机制、节点故障、节点故障修复、硬盘故障以及硬盘故障修复事件对存储系统可靠性的影响。实验结果表明,当预测模型的准确率达到50%时,系统的可靠性可以提高1~3倍;与二副本系统相比,三副本系统对系统参数更敏感。所提模型可以帮助系统管理者比较权衡不同的容错方式以及系统参数下的系统可靠性水平,从而搭建高可靠和高可用的存储系统。     

An approach for analyzing the reliability of industrial systems using soft-computing based technique

The purpose of this paper is to present a novel technique for analyzing the behavior of an industrial system by utilizing vague, imprecise, and uncertain data. In this, two important tools namely traditional Lambda–Tau and artificial bee colony algorithm have been used to build a technique named as an artificial bee colony (ABC) algorithm based Lambda–Tau (ABCBLT). In real-life situation, data collected from various resources contains a large amount of uncertainties due to human errors and hence it is not easy to analyze the behavior of such system up to a desired accuracy. If somehow behavior of these systems has been calculated, then they have a high range of uncertainty. For handling this situation, a fuzzy set theory has been used in the analysis and an artificial bee colony has been used for determining their corresponding membership functions. To strengthen the analysis, various reliability parameters, which affects the system performance directly, have been computed in the form of fuzzy membership functions. Sensitivity as well as performance analysis has also been analyzed and their computed results are compared with the existing techniques result. The butter–oil processing plant, a complex repairable industrial system has been taken to demonstrate the approach.