Multivariate statistical process control methods for batch production: a review focused on applications

被引：10

作者：

Ramos, Miriam ^{[1
]}

Ascencio, Jose ^{[1
]}

Vanessa Hinojosa, Miriam ^{[1
]}

Vera, Francisco ^{[1
]}

Ruiz, Omar ^{[1
]}

Isabel Jimenez-Feijoo, Maria ^{[1
]}

Galindo, Purificacion ^{[2
]}

机构：

[1] ESPOL Polytech Univ, ESPOL, Escuela Super Politecn Litoral, Campus Gustavo Galindo Km 30-5,Via Perimetral, Guayaquil, Ecuador

[2] Univ Salamanca, Dept Estadist, Campus Miguel Unamuno, Salamanca, Spain

来源：

PRODUCTION AND MANUFACTURING RESEARCH-AN OPEN ACCESS JOURNAL | 2021年 / 9卷 / 01期

关键词：

MSPC; batch; methods; review; applications; PARTIAL LEAST-SQUARES; INDEPENDENT COMPONENT ANALYSIS; PROCESS-CONTROL CHARTS; FAULT-DETECTION; DIAGNOSIS; QUALITY; MODEL; PARAFAC;

D O I：

10.1080/21693277.2020.1871441

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, we highlight the basic techniques of multivariate statistical process control (MSPC) under the dimensionality criteria, such as Multiway Principal Component Analysis, Multiway Partial Squares, Structuration a Trois Indices de la Statistique, Tucker3, Parallel Factors, Multiway Independent Component Analysis, Multiset Canonical Correlation Analysis, Slow Features Analysis, and Parallel Coordinates. Furthermore, we summarize the procedures of each statistical technique and the usage of multivariate control charts. In addition, we review the most significant proposals and applications in practical cases. Finally, we compare and discuss the benefits and limitations within methods.

引用

页码：33 / 55

页数：23

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