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首页> 外文会议>Joint 2015 e-Manufacturing amp; Design Collaboration Symposium 2015 and 2015 International Symposium on Semiconductor Manufacturing >Data analytics in semiconductor industry
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Data analytics in semiconductor industry

机译：半导体行业的数据分析

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Batch-wise manufacturing processes are found in many industries like chemical, pharmaceutical, bio-technical and semi-conductor. Typical examples include PVC polymerization, fermentations, beer brewing, and wafer etching. Batch process usually has a finite duration, from initialization to completion, and the trajectories of batch process variables describe dynamic time dependency. Batch processes give rise to data tables that are different from the two-way data structures. Measured data from batches are handled in three-way matrices (Figure 1). There might be more than one block of batch process data. Initial conditions data are given by one data table (often called the Z-matrix), information of relevance here would be characteristics of raw material or environment. In the second data matrix, batch evolution data are gathered. This matrix is often called the X-matrix. Naturally, the last block of data, often called the Y-matrix, is composed of results and product quality data for each batch.
机译：在化学，制药，生物技术和半导体等许多行业中发现了批量生产过程。典型示例包括PVC聚合，发酵，啤酒酿造和威化饼蚀刻。批处理过程通常具有从初始化到完成的有限持续时间，并且批处理过程变量的轨迹描述了动态时间依赖性。批处理过程产生的数据表与双向数据结构不同。来自批次的测量数据以三向矩阵处理（图1）。批处理数据可能有多个块。初始条件数据由一个数据表（通常称为Z矩阵）给出，此处的相关信息将是原材料或环境的特征。在第二个数据矩阵中，收集批处理演化数据。该矩阵通常称为X矩阵。自然地，最后一个数据块（通常称为Y矩阵）由每个批次的结果和产品质量数据组成。

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