寻找PET无纺布布面克重异常点的分析数据

通过密集的取样测试，可以充分分析一款PET无纺布产品的克重偏差情况，找到布面克重异常点，对改善PET无纺布的生产工艺提供数据支持。1内在逻辑：通过对同一块PET无纺布纵向5个不同位置，横向全幅24个点的取样测试，分析5个不同纵向位置的克重偏差，找到偏差最大的几个横向点，针对这些位置进行有针对性的工艺改良，提升产品质量。2.具体计算：选取相邻的纵向5个位置，每个位置取横向全幅24个样，分别测试克重数据，并计算24个样的平均值，重复5次计算出纵向5个位置的平均值，再找出5个平均值的最大最小值，并计算它们的差值，将该差值+10设定为异常判定的标准值(上限值)，之后分别计算横向每一个点的克重最大最小偏差值，根据异常判定标准进行判定，找到异常点。

Through intensive sampling and testing, the basis weight deviation of a PET nonwoven fabric product can be fully analyzed, and the basis weight anomalies on the fabric surface can be identified, providing data support for improving the production process of PET nonwoven fabrics.
1. Internal Logic: By sampling and testing 5 distinct longitudinal positions and 24 points across the full transverse width of the same PET nonwoven fabric, the basis weight deviations at the 5 longitudinal positions are analyzed to identify the transverse points with the most significant deviations. Targeted process improvements are then carried out for these positions to enhance product quality.
2. Specific Calculation Procedure: Select 5 adjacent longitudinal positions, collect 24 transverse samples across the full width at each position, and test the basis weight data respectively. Calculate the average value of the 24 samples at each longitudinal position, then repeat the process 5 times to obtain the average basis weight for each of the 5 longitudinal positions. Identify the maximum and minimum values among these 5 average results, and calculate their difference. Set this difference plus 10 as the standard threshold (upper limit) for anomaly determination. Subsequently, calculate the maximum and minimum deviation values of the basis weight for each transverse point individually, and identify the anomaly points according to the pre-defined anomaly determination standard.

搜集汇总

数据集介绍

特点

该数据集为PET无纺布布面克重异常点的分析数据，包含12条记录，用于通过密集取样测试分析克重偏差，改善生产工艺。数据已在浙江省知识产权区块链公共存证平台存证。