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An iterative statistical tolerance analysis procedure to deal with linearized behavior models

机译:处理线性化行为模型的迭代统计公差分析程序

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摘要

tolerance analysis consists of analyzing the impact of variations on the mechanism behavior due to the manufacturing process. The goal is to predict its quality level at the design stage. The technique involves computing probabilities of failure of the mechanism in a mass production process. The various analysis methods have to consider the component’s variations as random variables and the worst configuration of gaps for over-constrained systems. This consideration varies in function by the type of mechanism behavior and is realized by an optimization scheme combined with a monte Carlo simulation. To simplify the optimization step, it is necessary to linearize the mechanism behavior into several parts. This study aims at analyzing the impact of the linearization strategy on the probability of failure estimation; a highly over-constrained mechanism with two pins and five cotters is used as an illustration for this study. The purpose is to strike a balance among model error caused by the linearization, computing time, and result accuracy. In addition, an iterative procedure is proposed for the assembly requirement to provide accurate results without using the entire monte Carlo simulation.
机译:耐受性分析包括分析由于制造过程引起的机制行为的影响。目标是在设计阶段预测其质量水平。该技术涉及在大规模生产过程中计算机制失效的概率。各种分析方法必须将组件的变化视为随机变量以及用于过度约束系统的间隙的最差配置。这种考虑因机构行为的类型而变化,并且通过优化方案与蒙特卡罗模拟结合使用。为了简化优化步骤,有必要将机制行为线性化为几个部分。本研究旨在分析线性化策略对失败估计概率的影响;具有两个引脚和五个孵出蛋白的高度限制机制作为本研究的插图。目的是在线性化,计算时间和结果准确性引起的模型误差之间取得平衡。此外,提出了一个迭代程序,为大会要求提供准确的结果而不使用整个蒙特卡罗模拟。

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