在制造过程中基于零射击学习的同时控制图表模式识别

相关实验视频

Updated: Jun 13, 2025

10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.6K

Yazhou Li¹, Wei Dai¹, Shuang Yu²

¹School of Reliability and Systems Engineering, Beihang University, Weimin Building, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China.

ISA transactions

|September 10, 2024

概括

本研究引入了零射击学习,用于识别工业质量控制中的并发异常控制图模式 (C-CCP). 这种新的方法在没有先前的C-CCP培训数据的情况下,在未见的模式上实现了高精度.

科学领域:

工业工程工业工程工业工程
机器学习机器学习
统计过程控制统计过程控制

背景情况:

在工业环境中,很难收集标记的并发异常控制图 (C-CCP) 模式.
现有的C-CCP识别 (CCPR) 方法由于缺乏培训数据而受到限制.
零射击学习为识别新型C-CCPs提供了一个潜在的解决方案.

研究的目的:

提出一个智能零射击学习模型,用于识别并发异常控制图形模式 (C-CCPs).
为了应对在工业质量控制中有限的标记C-CCP数据的挑战.
提高CPC认可 (CCPR) 方法的有效性.

主要方法:

在C-CCP认可的质量控制中引入了零射击学习.
开发了一种多尺度顺序模式 (OP) 功能,以捕获数据的顺序关系.
建立了一个属性描述空间 (ADS),使用专家知识来弥合单个CCP和C-CCP.
集成了一个属性分类器来将特征与属性关联起来.

主要成果:

在没有C-CCP培训样本的情况下,对于11个未见的C-CCP实现了98.73%的准确性.
在所有19个CPT中,获得了98.89%的整体准确性.
与其他功能相比,在未见的C-CCP上,多尺度OP功能表现出优异的识别性能.

结论:

拟议的零射击学习模型有效地识别了未见的C-CCPs.
多尺度OP功能和ADS对于成功的C-CCP识别至关重要.
这种方法在工业质量控制中显著推进了CPR,特别是在有限的数据的情况下.

关键词:

同时的中央对手控制图表模式识别控制图表模式识别一般化的ZSL 一个普通的模式.零射击学习的学习.

相关概念视频

00:58

The X̄ Chart

109

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...

109

01:15

Introduction to Statistical Process Control

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...

01:13

Interpreting X̄ Charts

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...

01:02

The R Chart

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...

01:10

Control Systems

1.1K

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

1.1K

01:22

Interpreting R Charts

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...