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Dimensional and Geometrical Errors in Vacuum Thermoforming Products: An Approach to Modeling and Optimization by Multiple Response Optimization

机译:真空热成型产品中的尺寸和几何误差:一种通过多重响应优化进行建模和优化的方法

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In the vacuum thermoforming process, the product deviations depend on several parameters of the system, which make the analysis, the computational modeling, and the optimization of errors a multi-variable process with conflicting objectives. In this sense, the aim of this work was to study the dimensional and geometrical errors as well as the optimization (minimization) of these errors in one typical vacuum thermoforming product made of polystyrene (PS). In particular, it was intended to predict and minimize errors in a range of ideal tolerances using Multiple Response Optimization (MRO) Models. Thus, through the fractional factorial design (2k-p), initial experimental tests were performed using proposed measurement procedures, and Analysis of Variance being the data analysis is discussed. Following that, the MRO models were implemented which were also validated to represent the sample data. Through this analysis of the results, it can be concluded that the regression models of errors are not linear functions, hence, the developed models are valid for the studied process, and finally that the validation results proved the efficiency of MOR models developed, but these models will not be able to generalize to new situations in a range far from the values studied.
机译:在真空热成型过程中,产品偏差取决于系统的几个参数,这使分析,计算模型和误差的优化成为目标相互冲突的多变量过程。从这个意义上讲,这项工作的目的是研究一种由聚苯乙烯(PS)制成的典型真空热成型产品的尺寸和几何误差以及这些误差的优化(最小化)。特别是,它旨在使用多重响应优化(MRO)模型来预测并最小化理想公差范围内的误差。因此,通过分数阶乘设计(2k-p),使用建议的测量程序进行了初始实验测试,并讨论了作为数据分析的方差分析。之后,实施了MRO模型,该模型也经过了验证,可以代表样本数据。通过对结果的分析,可以得出结论,误差的回归模型不是线性函数,因此,所开发的模型对于所研究的过程是有效的,最后,验证结果证明了所建立的MOR模型的有效性,但是这些模型将无法推广到与研究值相差甚远的新情况。

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