A Rough Set Approach to the Ordering of Basic Events in a Fault Tree for Fault Diagnosis

The performance of manufacturing systems or equipment is, to a great extent, dependent upon the condition of their components. Closely monitoring the condition of the critical components and carrying out timely system diagnosis whenever a fault symptom is detected would help to reduce system downtime and improve overall productivity. Fault tree analysis (FTA) is a powerful tool for reliability studies and risk assessment. However, most research on FTA focuses on the generation of minimum cut sets and how to calculate the probability of main events. As a result, the issue concerning the ordering of basic events in a fault tree has been largely neglected. In this paper, a novel approach based on rough set theory and a pairwise comparison table for fault diagnosis is proposed. The approach attempts to learn from the pattern of decision-making by domain experts from past experience and uses the knowledge acquired, which is in the form of a minimum decision rule set, to determine the ordering of basic events in a fault tree. The details of the approach, together with the basic concepts of rough set theory, are presented. A case study is used to illustrate the application of the proposed approach. Results show that a reasonable ordering of basic events in a fault tree can be generated easily. With the ordering of basic events determined, a maintenance engineer in a manufacturing plant can then carry out fault diagnosis in an efficient and orderly manner.     

A study of time‐between‐events control chart for the monitoring of regularly maintained systems

Owing to usage, environment and aging, the condition of a system deteriorates over time. Regular maintenance is often conducted to restore its condition and to prevent failures from occurring. In this kind of a situation, the process is considered to be stable, thus statistical process control charts can be used to monitor the process. The monitoring can help in making a decision on whether further maintenance is worthwhile or whether the system has deteriorated to a state where regular maintenance is no longer effective. When modeling a deteriorating system, lifetime distributions with increasing failure rate are more appropriate. However, for a regularly maintained system, the failure time distribution can be approximated by the exponential distribution with an average failure rate that depends on the maintenance interval. In this paper, we adopt a modification for a time‐between‐events control chart, i.e. the exponential chart for monitoring the failure process of a maintained Weibull distributed system. We study the effect of changes on the scale parameter of the Weibull distribution while the shape parameter remains at the same level on the sensitivity of the exponential chart. This paper illustrates an approach of integrating maintenance decision with statistical process monitoring methods. Copyright © 2008 John Wiley & Sons, Ltd.     

Multi‐surface sliding control for fast finite‐time leader–follower consensus with high order SISO uncertain nonlinear agents

In this paper, multi surface sliding cooperative control scheme is presented and new multiple sliding surfaces are proposed. It is proven that, for the setup that each agent is described by a chain of integrators, where the last integrator is perturbed by a bounded disturbance, leader–follower consensus can be achieved on these sliding surfaces if the communication graph has a directed spanning tree. Also, sliding variables can be driven to the sliding surfaces in fast finite time by the nonsmooth control law. The fast finite‐time Lyapunov stability theorem, the terminal sliding control technique, and the adding a power integrator design approach are used in our proposed control. Simulation results demonstrate the effectiveness of the proposed scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

A multi-dimensional scheduling scheme in a Grid computing environment

In this paper, we propose a novel distributed resource-scheduling algorithm capable of handling multiple resource requirements for jobs that arrive in a Grid computing environment. In our proposed algorithm, referred to as multiple resource scheduling (MRS) algorithm, we take into account both the site capabilities and the resource requirements of jobs. The main objective of the algorithm is to obtain a minimal execution schedule through efficient management of available Grid resources. We first propose a model in which the job and site resource characteristics can be captured together and used in the scheduling algorithm. To do so, we introduce the concept of a n-dimensional virtual map and resource potential. Based on the proposed model, we conduct rigorous simulation experiments with real-life workload traces reported in the literature to quantify the performance. We compare our strategy with most of the commonly used algorithms in place on performance metrics such as job wait times, queue completion times, and average resource utilization. Our combined consideration of job and resource characteristics is shown to render high-performance with respect to above-mentioned metrics in the environment. Our study also reveals the fact that MRS scheme has a capability to adapt to both serial and parallel job requirements, especially when job fragmentation occurs. Our experimental results clearly show that MRS outperforms other strategies and we highlight the impact and importance of our strategy.     

A side-sensitive synthetic coefficient of variation chart

Control charts for monitoring the coefficient of variation (γ) are useful for processes with an inconsistent mean (μ) and a standard deviation (σ) which changes with μ, by monitoring the consistency in the ratio σ over μ. The synthetic-γ chart is one of the charts proposed to monitor γ, and its attractiveness lie in waiting until a second point to fall outside the control limits before a decision is made. However, existing synthetic-γ charts do not differentiate between the points falling outside the upper control limit (UCL) and lower control limit (LCL). Hence, this paper proposes a side-sensitive synthetic-γ chart, where successive nonconforming samples must either fall above the UCL or below the LCL. Formulae to compute the average run length (ARL), the standard deviation of the run length (SDRL) and expected average run length (EARL) are derived using the Markov chain approach, and the algorithms to obtain the optimal charting parameters are proposed. Subsequently, the optimal charting parameters, ARL, SDRL and EARL values for various numerical examples are shown. Comparisons show that the side-sensitive synthetic-γ chart consistently outperforms the existing synthetic-γ chart, especially for small shifts. The proposed chart also consistently outperforms the Shewhart-γ chart, while showing comparable or better performance than the Exponentially Weighted Moving Average (EWMA) chart for most shift sizes, except for very small shifts. Finally, this paper shows the implementation of the proposed chart on an industrial example.     

Progressive mean control chart is not a special case of an exponentially weighted moving average control chart

The progressive mean (PM) statistic is based on a simple idea of accumulating information of each subgroup by calculating the average progressively. Its weighting structure is based on a subgroup number that changes arithmetically, which makes the PM chart unique and efficient compared with the existing classical memory control charts. In a recent article (see reference 1), it was claimed that the PM chart is a special case of the exponentially weighted moving average (EMWA) chart. In this article, it is shown that even though the PM statistic can be written in the form of an EWMA statistic, the variance of the PM statistic is different from that of the EWMA statistic. Consequently, the limits of the PM chart are different from that of the EWMA chart. Therefore, it is found that the PM chart is not a special case of the EWMA chart; hence, the claim in reference 1 is incorrect. Furthermore, it is pointed out in this paper that no adaptive property in the weighting parameter of the PM statistic exists, further contradicting the claim in reference 1.     

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PKC in rat cortical synaptosomes: effects of depolarization

Glomerulopathy with predominant fibronectin deposits (GFD) is a newly recognized autosomal dominant renal disease that leads to albuminuria, microscopic hematuria, hypertension, renal tubular acidosis type IV, and end-stage renal disease in the second to fourth decade of life. Light microscopy documents extensive deposits in the subendothelial space, which on electron microscopy consist of non-oriented 12 x 125 nm fibers. Deposits are strongly immunoreactive for antibodies to fibronectin. We examined the hypothesis that a genetic defect in the gene for fibronectin is responsible for the disease. In a 197 member pedigree, 13 relatives developed end-stage renal failure from the disease. In 99 individuals haplotype analysis was performed using 6 microsatellite markers spanning a > 56 cM interval in chromosome region 2q34, where fibronectin, villin, and desmin map in close proximity. Haplotype analysis resulted in exclusion of the whole range of 78 cM covered by the markers examined. This result excludes fibronectin, villin, and desmin from being the causative genes for GFD in this large kindred.     

基于标准单元库的多级函数分解

本文提出在ASIC综合技术中基于标准单元库的多级逻辑函数分解技术。分解过程利用单元库函数真值矩阵及各分解部分用标准单元实现的难易程度、逻辑级数来评价、引导分解得到的多级逻辑易于用标准单元组合实现。使用的标准单元类型具有较大程度的相似性,有利于基于标准单元布局布线软件进一步减少芯片面积。