.png){kind=icon}
返回
Multivariate multinomial T2 control chart using fuzzy approach
.png){kind=icon}
OA
AI
DOI：10.1080/00207543.2014.983617.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Quality of a product is often measured through various quality characteristics generally correlated. Multivariate control charts are a response to the need for quality control in such situations. If quality characteristics are qualitative, it sometimes happens that the product quality is defined by linguistic variables - where quality levels are represented by some specific words - and product units are classified into several linguistic forms categories, depending on the degree of fulfilment of expectations, creating a situation of fuzzy classifications. This study first reviews the concepts found in the literature on the development of fuzzy multivariate control charts. We propose a method to control these fuzzy quality evaluations, with correlated multiple attributes quality characteristics, through the use of a Hotelling T-2 control chart.
Keyword:
Hotelling T-2
fuzzy theory
multinomial processes
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.3
论文数:
1.1W
被引数:
3.7W
机构
引用论文
Pathological and clinical associations of Ki‐67 defined growth fractions in human prostatic carcinoma.png)
The Prostate
The ProstateIF0
PREAI
分享收藏分享收藏
查看更多内容