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A job-classifying and data-mining approach for estimating job cycle time in a wafer fabrication factory

机译:一种作业分类和数据挖掘方法,用于估算晶圆制造厂的作业周期时间

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摘要

Before making a due date commitment to our customer, we need to estimate the cycle times of jobs. For this reason, many of the most-advanced methods classify jobs, before or after estimating the cycle times. However, job classification is not directly helpful to optimize the performances of these estimation methods. To solve this problem, a job-classifying and data-mining approach is proposed in this study to improve the performance of cycle time estimation by optimizing the results of job classification. In addition, some association rules are also extracted from the estimation results to facilitate the practical application of the proposed methodology. According to the results of a case study, the job-classifying and data-mining approach achieved a better estimation performance and could produce some useful estimation rules.
机译:在向客户作出到期日承诺之前,我们需要估算工作的周期时间。因此,许多最先进的方法在估算周期之前或之后对作业进行分类。但是,工作分类并不能直接帮助优化这些估计方法的性能。为了解决这个问题,本文提出了一种工作分类和数据挖掘的方法,通过优化工作分类的结果来提高周期时间估计的性能。另外,还从估计结果中提取了一些关联规则,以促进所提出的方法的实际应用。根据案例研究的结果,工作分类和数据挖掘方法获得了更好的估计性能,并且可以产生一些有用的估计规则。

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