Abstract

Stochastic textured surface (STS) data (e.g., material microstructure microscopy images) are increasingly common in many quality control settings. Because of their stochastic nature, performing statistical process control (SPC) for STS data without requiring advanced knowledge of abnormal behavior is challenging, and there is no existing SPC software available to solve this problem. This article introduces the spc4sts $R$ package, which is the first implementation of recent developments that address SPC problems for STS data. The package provides tools for modeling, monitoring for defects and changes, and diagnosing variation and other patterns or modes that occur due to manufacturing and processing conditions.

摘要

随机纹理表面 (STS) 数据（例如，材料微观结构显微镜图像）在许多质量控制设置中越来越普遍。由于它们的随机性，对 STS 数据执行统计过程控制 (SPC) 而不需要异常行为的高级知识具有挑战性，并且没有可用的现有 SPC 软件来解决这个问题。本文介绍了spc4sts$\mathrm{电阻}$包，这是解决 STS 数据 SPC 问题的最新发展的第一个实现。该软件包提供了用于建模、监测缺陷和变化以及诊断因制造和加工条件而发生的变化和其他模式或模式的工具。