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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Computer-based management of interactive data transformation systems using Taguchi's robust parameter design
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Computer-based management of interactive data transformation systems using Taguchi's robust parameter design

机译：利用田口健壮的参数设计，基于计算机的交互式数据转换系统管理

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摘要

The Taguchi design method, which uses orthogonal arrays to study the quality of characteristics using only a small number of experiments, produces outstanding outcomes when applied to industrial processes. However, nearly all industrial data is concealed via interactive data transformations, for which Box-Cox, arcsine and logit with computer-based management are proposed. The efficiency of each transformation based on the mean and signal-to-noise ratio was investigated for a different number of replicates and noise levels on the response. A total of four simulated scenarios each with 100 noisy data sets were used to examine the system performance. The numerical results indicate that Box-Cox and arcsine transformations are superior to logit transformations. Moreover, the analytical outcomes from the interactive ranges of transformation parameters via the hybridisation of variable neighbourhood search and particle swarm optimisation methods were a close fit to the natural data. In an actual computer-based application of the interactive data transformation system for a ball swaging process, Box-Cox and arcsine transformations followed the simulated numerical data and provided much more appropriate outcomes closer to the natural data. The target of a gram load control was then met via process parameters with higher levels of ranking results of contribution ratio, as expected from the natural data.
机译：Taguchi设计方法仅使用少量实验就使用正交阵列来研究特征的质量，当应用于工业过程时会产生出色的结果。但是，几乎所有的工业数据都通过交互式数据转换来隐藏，为此提出了Box-Cox，反正弦和logit以及基于计算机的管理方法。针对不同数量的重复和响应中的噪声水平，研究了基于均值和信噪比的每次转换的效率。总共使用四个模拟场景（每个场景有100个噪声数据集）来检查系统性能。数值结果表明Box-Cox和反正弦变换优于logit变换。此外，通过可变邻域搜索和粒子群优化方法的混合得到的变换参数的交互范围的分析结果非常适合自然数据。在用于球锻造过程的交互式数据转换系统的基于计算机的实际应用中，Box-Cox和反正弦转换遵循模拟的数值数据，并提供了更接近自然数据的更合适的结果。然后，通过过程参数达到了克负荷控制的目标，正如自然数据所预期的那样，该过程参数的贡献率排名结果更高。

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