相关实验视频
Updated: May 24, 2025

14:23
Design and Optimization Strategies of a High-Performance Vented Box
Published on: June 9, 2023
1.0K
在短期运行过程中监测多变量变化系数的CUSUM方案的效率
Xuelong Hu1, Yixuan Ma1, Jiening Zhang1
1School of Management, Nanjing University of Posts and Telecommunications, Nanjing, People's Republic of China.
Journal of applied statistics
|March 5, 2025
概括
使用累积和 (CUSUM) 的新多变量变化系数 (MCV) 监测方案改善了小批处理过程的控制. 这些CUSUM MCV方案在检测各种工艺转移方面优于现有方法,提高了制造质量.
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
- 制造系统制造系统的制造
背景情况:
- 目前的工业生产是多样化的,越来越需要对小批量工艺进行有效监测.
- 使用多变量变化系数 (MCV) 进行多变量过程监测,由于过程限制较少,因此具有广泛的适用性.
- 现有的MCV监控方案需要提高有限视界生产的性能.
研究的目的:
- 引入新的单边累积总和 (CUSUM) MCV监控计划.
- 为了提高有限地平线生产过程的MCV监控的性能.
- 与现有方法相比,评估拟议的CUSUM MCV方案的效率.
主要方法:
- 开发两个单方面的CUSUM MCV计划.
- 使用马尔科夫链方法优化设计参数,用于确定性和随机转移.
- 基于运行长度 (RL) 特性 (平均值和标准偏差) 的方案性能分析.
- 与现有的指数加权移动平均 (EWMA) MCV 方案进行比较模拟研究.
主要成果:
- 拟议的CUSUM MCV方案在监测各种轮班方面表现出更高的效率,包括确定性和随机类型.
- 性能分析表明,与现有的EWMAMCV方案相比,它具有优势.
- 一个关于钢套制造的案例研究证实了新方案的实际好处.
结论:
- 开发的CUSUM MCV方案为监控小批量工业过程提供了更有效的方法.
- 与传统的EWMA MCV方法相比,这些方案为工艺转移提供了增强的检测能力.
- 这些发现适用于改善制造环境中的质量控制,例如钢套生产.
相关概念视频
Coefficient of Variation
3.7K
The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can compare two data series with drastically different means or different units of measurement. The coefficient of variation for a sample and a population is expressed as a percentage of the ratio of standard deviation to the mean.
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
3.7K
Variation
6.7K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
6.7K
Interpreting Run Charts
52
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...
52
Testing a Claim about Standard Deviation
2.4K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.4K
Introduction to Statistical Process Control
67
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...
67
Variability: Analysis
124
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
The range is a simple measure of variability, indicating the difference between the highest and...
124

