基于机器学习的无参数自适应EWMA控制图用于监控过程分散
Muhammad Noor-Ul-Amin1, Muhammad Waqas Kazmi1, Salem Alkhalaf2
1Department of Statistics, COMSATS University Islamabad-Lahore Campus, Lahore, Pakistan.
Scientific reports
|December 29, 2024
概括
本研究引入了使用支向量回归 (SVR) 进行改进的过程分散监测的自适应指数加权移动平均 (AEWMA) 控制图. 这种新的方法通过调整参数来增强转移检测,在工业应用中提供更高的可靠性.
科学领域:
- 工业工程 工业工程 工业工程
- 统计过程控制 统计过程控制
- 机器学习 机器学习
背景情况:
- 传统的控制图使用固定的参数,限制在线监控期间的适应性.
- 适应性控制图表可以动态调整参数,以增强过程控制.
- 在不同的操作环境中,对流程分散的有效监控至关重要.
研究的目的:
- 开发和评估一个自适应指数加权移动平均线 (AEWMA) 控制图.
- 在控制图表中集成支持向量回归 (SVR) 进行自适应参数调整.
- 提高工艺分散监测的灵敏度和可靠性.
主要方法:
- 实现一个自适应指数加权移动平均线 (AEWMA) 控制图.
- 使用支持向量回归 (SVR) 与线性,多项式和辐射基础函数 (RBF) 内核.
- 根据检测到的工艺分散的变化,调整光滑常数.
主要成果:
- 提出的基于SVR的AEWMA控制图表显示了在检测工艺分散转移方面提高了性能.
- 在SVR框架中的RBF内核在适应性监控方面尤其有效.
- 使用现实数据的验证证实了该方法的适应性和可靠性.
结论:
- 基于SVR的AEWMA控制图为流程分散监控提供了强大的和适应性的解决方案.
- 这种方法通过动态调整控制参数来改进传统方法.
- 该研究强调了机器学习在统计过程控制中的整合潜力.
相关概念视频
The X̄ Chart
80
The x̄ chart is a statistical tool for monitoring the means in a process.
The x̄ chart, often known as the individual control chart, is a crucial tool in statistical process control. It is designed to monitor process behavior and performance over time and is widely used in various industries to ensure that processes are operating at their optimum capacity and within specified limits.
A x̄ chart is constructed by plotting individual measurements of a quality...
The x̄ chart, often known as the individual control chart, is a crucial tool in statistical process control. It is designed to monitor process behavior and performance over time and is widely used in various industries to ensure that processes are operating at their optimum capacity and within specified limits.
A x̄ chart is constructed by plotting individual measurements of a quality...
80
Interpreting X̄ Charts
36
Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
36
Interpreting R Charts
38
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
38
The R Chart
36
In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
36
Introduction to Statistical Process Control
49
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
49
Interpreting Run Charts
39
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
39


