Confidence limits for Weibull parameters estimated using linear least squares analysis

Confidence limits (at selected levels of 68.27%, 90%, 95% and 99%) for unbiased estimation of Weibull parameters obtained using linear least squares (LLS) analysis were investigated in this paper. A Monte Carlo procedure was used to obtain probability distributions for unbiased estimates of Weibull modulus, m, and Weibull scale parameter, S_o, as a function of total specimen number, N (10 ≤ N ≤ 200), and m (1 ≤ m ≤ 25). Inspection of the probability distributions indicated that confidence limits for m depended only on N whereas those for S_o depended on both N and m. Whilst the determination of confidence limits for m proved to be relatively straightforward, the respective values for S_o were obtained by fitting an empirical equation to the S_o probability distributions approximated by a Gaussian curve. Example values of m and S_o confidence limits for selected N have been presented in this work.     

A Calculation Method for Power System Frequency Deviation Considering Intensity of Turbulence

As more and more wind farms are installed in power systems around the world, frequency fluctuations due to output power variations have become a serious problem. Various countermeasures for the problem, such as battery systems, have been investigated. It is very important to evaluate the magnitude of the frequency fluctuations in order to design compensating systems. This paper presents a new and simple method to evaluate the expected value of the frequency deviation due to variations in wind farm output, which is based on the intensity of turbulence and annual probability distribution for the wind speed.     

Some Statistical Aspects of the Economics of Analytical Testing

In establishing an economical testing program the costs of routine analytical tests must be weighed against losses due to shipping material which is either above or below stated specifications. A method for obtaining an optimum sampling and testing procedure is described and examples given.     

Life Tests Under Dependent Competing Causes of Failure

In a life testing situation the failure of an individual, either a living organism or an inanimate object, may be classified into one of k(< 1) mutually exclusive classes, usually causes of failure. One often has dependent causes of failure in actual physical situations, i.e., the theoretical lifetime of an individual failing from one cause may be correlated with the theoretical lifetime of the same individual failing from a different cause. This paper i) discusses some properties of a bivariate Weibull distribution and ii) is concerned with estimating, by the method of maximum likelihood, the unknown parameters of life distributions belonging to two particular parametric families, viz., bivariate normal and bivariate Weibull, when the causes of failure are dependent. An example involving the failure of small electrical appliances is analyzed and compared with an analysis which assumes the causes of failure to be independent.     

Availability and cost-centered preventive maintenance scheduling of continuous operating series systems using multi-objective genetic algorithm: A case study

This article presents a multi-objective (maximization of availability and minimization of maintenance cost) preventive maintenance (PM) scheduling model for a continuous operating series system (COSS) which do not provide an off-working period for PM. The objective functions are optimized by using a Multi-Objective Genetic Algorithm (MOGA). The effectiveness of the model is demonstrated through a coal-fired boiler-tube. The case study shows that the model can improve the availability along with profound reduction of the maintenance cost, i.e., increases the profit of the plant.     

Generation scheduling in smart grid environment using global best artificial bee colony algorithm

Generation scheduling is an important concern of the current power system which is suffering from many obstacles of limited generation resources, grown energy demand and fuel price, inconsistent load demand and fluctuations of available wind power in case of the thermal–wind system. Smart grid system has a great potential of tumbling existing power system difficulties with intelligent infrastructure and computation technologies. Three different distributed energy resources, namely, distributed generation, demand response and gridable vehicles are used in this paper to overcome the power system hitches. The classical generation scheduling is solved with insertion of the cost of demand response and the cost model pertaining to underestimation and overestimation of fluctuating wind power. The modified optimization problem is solved using an efficient Global best artificial bee colony algorithm for 10 generating units test system. Generation scheduling in the smart grid environment yields a significant reduction in the total cost.     

Cumulative Sum Control Charts for Monitoring Weibull‐distributed Time Between Events

The Weibull distribution can be used to effectively model many different failure mechanisms due to its inherent flexibility through the appropriate selection of a shape and a scale parameter. In this paper, we evaluate and compare the performance of three cumulative sum (CUSUM) control charts to monitor Weibull‐distributed time‐between‐event observations. The first two methods are the Weibull CUSUM chart and the exponential CUSUM (ECUSUM) chart. The latter is considered in literature to be robust to the assumption of the exponential distribution when observations have a Weibull distribution. For the third CUSUM chart included in this study, an adjustment in the design of the ECUSUM chart is used to account for the true underlying time‐between‐event distribution. This adjustment allows for the adjusted ECUSUM chart to be directly comparable to the Weibull CUSUM chart. By comparing the zero‐state average run length and average time to signal performance of the three charts, the ECUSUM chart is shown to be much less robust to departures from the exponential distribution than was previously claimed in the literature. We demonstrate the advantages of using one of the other two charts, which show surprisingly similar performance. Copyright © 2014 John Wiley & Sons, Ltd.     

三参数Weibull分布下基于BRM的LED照明灯寿命预测

为了在短时间内准确获得LED照明灯的寿命信息,以3组恒定加速应力的试验数据为基础,采用三参数Weibull函数描述其寿命分布,基于双线性回归法(BRM)对试验数据进行处理分析,并利用自行开发的寿命预测软件较为精确地得出LED照明灯在正常工作应力下的寿命。数值结果表明,LED照明灯的寿命服从三参数Weibull分布,其加速模型符合Arrhenius方程,精确预测的LED照明灯寿命为工程技术人员关于产品的可靠性设计提供技术参考。     

Impact of geometry on stretchable meandered interconnect uniaxial tensile extension fatigue reliability

This work investigates the impact of geometry on the reliability of a high conductivity, meandered, stretchable interconnect. Meandered copper conductor interconnects of varying geometries that have been encapsulated into a PDMS matrix, are evaluated for reliability under tensile stretching conditions to 10% elongation. We present results that support our earlier findings by experiment and FEM simulation. Following, we vary interconnect parameters related to the encapsulation geometry, such as encapsulation hardness, thickness and stretchable zone perimeter, to assess impact on fatigue life of the embedded meandered copper lines. Results confirm and refine the prior simulation findings. Combinations of interconnect geometry parameters critical for stretching reliability are identified. Among others, we find that the meander radius (R) and encapsulation thickness are strongly coupled, causing very large meanders with thick encapsulation to fail very early. We show that, depending on the design of the meander transition, the characteristic life of an interconnect can differ 50 times under moderate, 10% cyclic elongation. Finally, we indicate the significance of our findings for the design of reliable, stretchable electronic systems.     

Wind characteristics and energy potential assessment in Akure,South West Nigeria: econometrics and policy implications

This paper analysed 11 years of daily mean wind-speed data, measured at Akure, Ondo State, Nigeria, using Weibull and Rayleigh distribution functions. While both distributions showed good agreements in extreme-value estimation patterns, investigation of their wind-speed characteristics modelling criteria, using goodness-of-fit statistics, revealed that the wind data followed the Weibull more than Rayleigh. Monthly wind-speed of Akure city ranged from 1.41 to 4.24 m/s by the Weibull fittings and from 1.40 to 4.16 m/s by the Rayleigh fittings. Overall results, of 2.71 m/s (Weibull) or 2.70 m/s (Rayleigh) mean wind-speed and 18.51 W/m² (Weibull) or 22.26 W/m² (Rayleigh) mean power density, indicated Akure a low wind-speed site, requiring low wind-speed turbine for generating wind energy. Econometric analyses of power output simulations using such turbine system resulted in affordable wind energy cost. These bear policy implications for sustainable wind energy usage in this and similar regions of the world.