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Development of composites based on recycled polypropylene for injection moulding automobile parts using hierarchical clustering analysis and principal component estimate

机译:运用层次聚类分析和主成分估计法开发基于再生聚丙烯的汽车注塑件复合材料

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Adapting recycled plastics into demanding manufacturing industry is helpful in promoting recycling rate of waste plastic scrap, but yet only a few researchers are tackling with this issue and recycled plastics are still ending up in low-value products. This paper presents a novel method to adapt recycled plastic for demanding industrial applications by designing suitable formulae which satisfy the technical requirements of the applications. To illustrate the proposed method which combines hierarchical clustering analysis and principal component estimate, actual requirements of some selected automobile parts were acquired and benchmarked in this study. Two common particle fillers talcum powder and organically modified montmorillonite were added in recycled polypropylene with maleic anhydride grafted polypropylene as a compatibiliser. The initial compositions were selected according to the specific composition selection rules which are adapted from Taguchi method for reducing the number of trials. Corresponding mechanical, rheological, and thermal properties were tested based upon the technical requirements of selected automobile parts. The interrelationships between multiple objectives (requirements) were analysed and classified by hierarchical clustering analysis, and then the total number of requirements were reduced. Effects of each component were identified numerically by principal component estimate, and a corresponding linear regression model was obtained. The linear regression model was compared to other linear regression models which obtained by other mathematic techniques, and it has been proved to be the best model which has the smallest gap between predicted values and experimental results. Optimal formulae were calculated via linear programming with the objects of minimising material cost and satisfying the reduced technical requirements of selected automobile parts. In verification tests, the experimental performance of the obtained formulae closely matched the model predictions. The proposed formula design method is novel and original, and it is shown to be effective and efficient in designing recycled plastic based composites for demanding industrial applications. (C) 2016 Elsevier Ltd. All rights reserved.
机译:使再生塑料适应苛刻的制造业有助于提高废塑料废料的回收率,但只有少数研究人员正在解决这个问题,而再生塑料仍以低价产品为最终目标。本文提出了一种新颖的方法,通过设计满足应用技术要求的合适配方,将再生塑料用于要求苛刻的工业应用。为了说明将分层聚类分析和主成分估计相结合的方法,本研究获得了一些选定汽车零件的实际需求并进行了基准测试。将两种常见的颗粒状滑石粉和有机改性的蒙脱土添加到回收的聚丙烯中,其中顺丁烯二酸酐接枝的聚丙烯作为增容剂。根据特定的成分选择规则来选择初始成分,该特定的成分选择规则是从Taguchi方法改编而来,以减少试验次数。根据所选汽车零件的技术要求,测试了相应的机械,流变和热性能。通过层次聚类分析,对多个目标(需求)之间的相互关系进行了分析和分类,然后减少了需求总数。通过主成分估计从数字上识别每个成分的作用,并获得相应的线性回归模型。将线性回归模型与通过其他数学技术获得的其他线性回归模型进行了比较,已证明这是最佳模型,其预测值与实验结果之间的差距最小。通过线性编程来计算最佳公式,其目的是最大程度地降低材料成本并满足所选汽车零件的降低的技术要求。在验证测试中,所获得公式的实验性能与模型预测非常匹配。所提出的配方设计方法新颖新颖,并且在设计用于要求苛刻的工业应用的可回收塑料基复合材料方面是有效的。 (C)2016 Elsevier Ltd.保留所有权利。

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