Variation source identification in manufacturing processes based on relational measurements of key product characteristics
Variation source identification in manufacturing processes based on relational measurements of key product characteristics
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DOI：
10.1115/1.2844591
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发表时间：
2008-06
影响因子：
4
通讯作者：
J. Loose;Shiyu Zhou;D. Ceglarek
中科院分区：
文献类型：
--
作者：
J. Loose;Shiyu Zhou;D. Ceglarek
制造过程偏差源识别是提高产品尺寸质量的关键，近年来发展了各种技术。现有的偏差源识别技术大多基于线性故障-质量模型，其中过程故障和产品尺寸质量测量之间的关系是线性的。在实践中，许多尺寸测量实际上与过程故障非线性相关：例如，关系尺寸测量（如特征之间的相对距离）用于监控复合公差。本文提出了一种变异源识别方法，在这些关系维度测量的存在。在所提出的方法中，测量的联合概率密度被确定为过程参数的函数，然后，进行一系列的统计比较，以区分和识别的变化源。最后通过一个实例说明了该方法的有效性。
Variation source identification for manufacturing processes is critical for product dimensional quality improvement, and various techniques have been developed in recent years. Most existing variation source identification techniques are based on a linear fault-quality model, in which the relationships between process faults and product dimensional quality measurements are linear. In practice, many dimensional measurements are actually nonlinearly related to the process faults: For example, relational dimension measurements such as the relative distance between features are used to monitor composite tolerances. This paper presents a variation source identification methodology in the presence of these relational dimension measurements. In the proposed methodology, the joint probability density of the measurements is determined as a function of the process parameters; then, series of statistical comparisons are performed to differentiate and identify the variation source. A case study is also presented to illustrate the effectiveness of the methodology.