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A comparison of traditional and maximum likelihood approaches to estimating thermal indices for polymeric materials

机译：估算聚合物材料热索引的传统和最大似然方法的比较

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摘要

Accelerated destructive degradation testing (ADDT) is a widely used technique for long-term material property evaluation. One area of application is in determining the thermal index (TI) of polymeric materials including thermoplastic, thermosetting, and elastomeric materials. There are two approaches to estimating a TI based on data collected from ADDT: the traditional and maximum likelihood (ML) procedures. The traditional procedure is specified in current industrial standards and is widely used in industrial applications. The ML procedure is frequently used in the statistical literature but rarely seen in industrial ADDT applications. At present, the ML procedure is not specified in the current standards. In this article, we compare both approaches with two motivating data sets from the literature and simulation studies. We show that the ML procedure has many advantages over the traditional procedure in terms of estimation performance, uncertainty quantification, material comparisons, and predictions. The comparisons and discussion in this article can be useful in designation of statistical methods for future industrial standards.
机译：加速破坏性降解测试（ADDT）是一种广泛使用的长期材料性能评估技术。一个应用领域在确定聚合物材料的热指数（Ti），包括热塑性，热固性和弹性体材料。基于从ADDT收集的数据估计TI有两种方法：传统和最大可能性（ML）程序。传统的程序在当前的工业标准中规定，广泛用于工业应用。 ML程序经常用于统计文献中，但很少在工业ADDT应用中看到。目前，ML程序未在当前标准中规定。在本文中，我们可以比较来自文献和仿真研究的两个激励数据集的方法。我们表明ML程序在估计性能，不确定性量化，材料比较和预测方面具有传统过程的许多优点。本文的比较和讨论可用于指定未来工业标准的统计方法。

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