Current Issue : April - June Volume : 2015 Issue Number : 2 Articles : 6 Articles
Reliability is an important phase in durable system designs, specifically in the early phase of the product development. In this paper,\na new methodology is proposed for complex systems� design for reliability. Specific test and field failure data scarcity is evaluated\nhere as a challenge to implement design for reliability of a new product. In the developed approach, modeling and simulation of\nthe system are accomplished by using reliability block diagram (RBD) method. The generic data are corrected to account for the\ndesign and environment effects on the application. The integral methodology evaluates reliability of the system and assesses the\nimportance of each component. In addition, the availability of the system was evaluated using Monte Carlo simulation. Available\ndesign alternatives with different components are analyzed for reliability optimization. Evaluating reliability of complex systems in\ncompetitive design attempts is one of the applications of this method. The advantage of this method is that it is applicable in early\ndesign phase where there is only limited failure data available. As a case study, horizontal drilling equipment is used for assessment\nof the proposed method. Benchmarking of the results with a system with more available failure and maintenance data verifies the\neffectiveness and performance quality of presented method....
This paper studies the acceptance sampling for exponential distributions with type-I and type-II adaptive progressive hybrid\ncensored samples. Algorithms are proposed for deriving Bayesian sampling plans. We compare the performance of the proposed\nsampling plans with the sampling plans of Lin and Huang (2012). The numerical results indicate that the proposed sampling plans\noutperform the sampling plans of Lin and Huang (2012)....
Generalized Estimating Equation (GEE) is a marginal model popularly applied for longitudinal/clustered data analysis in clinical\ntrials or biomedical studies.We provide a systematic review on GEE including basic concepts as well as several recent developments\ndue to practical challenges in real applications.The topics including the selection of ââ?¬Å?workingââ?¬Â correlation structure, sample size\nand power calculation, and the issue of informative cluster size are covered because these aspects play important roles in GEE\nutilization and its statistical inference. A brief summary and discussion of potential research interests regarding GEE are provided\nin the end....
We consider the estimation of stress-strength reliability based on lower record values when X and Y are independently but not\nidentically inverse Rayleigh distributed random variables. The maximum likelihood, Bayes, and empirical Bayes estimators of R are\nobtained and their properties are studied. Confidence intervals, exact and approximate, as well as the Bayesian credible sets for R\nare obtained. A real example is presented in order to illustrate the inferences discussed in the previous sections. A simulation study\nis conducted to investigate and compare the performance of the intervals presented in this paper and some bootstrap intervals....
Statistical process control (SPC) is one of the most important statistical tools for monitoring production processes. It can\nbe effectively designed and implemented when the process or product specifications are consecutively observed from a mass\nproduction condition. Normally, short-cycle productions do not have sufficient data to implement SPC. This research introduced\nhowto design and implement short-run control chart for batch production conditions.Monitoring critical specifications of supplied\nparts to automotive industry was proposed. The results revealed that unequal variables followed normal distribution and can be\nfluctuated over time for the purpose of monitoring multiple products for each product including multidimensions with unequal\nmeans and variances from the central line to control the chart. Out-of-control signals and nonrandom patterns can be recognized\non the developed short-run control chart accordingly....
We consider the parameter inference for a two-parameter life distribution with bathtub-shaped or increasing failure rate function.\nWe present the point and interval estimations for the parameter of interest based on type-II censored samples. Through intensive\nMonte-Carlo simulations, we assess the performance of the proposed estimation methods by a comparison of precision. Example\napplications are demonstrated for the efficiency of the methods....
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