Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286215 
Title (translated): 
Design of a control charter based on principal component analysis: A case study
Year of Publication: 
2020
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 30 [Year:] 2020 [Pages:] 279-296
Publisher: 
Universidad Pablo de Olavide, Sevilla
Abstract (Translated): 
The set of quantitative methods and techniques used to detect assignable variations in manufacturing processes are contained within a discipline classified as statistical process control. Such methods carry out precise evaluations on the general state of productive systems and carry out simultaneous monitoring of various interrelated quality characteristics. In the framework of this research, the analysis of a chemical process based on the theoretical principles of principal component analysis is proposed, which enables the representation of the original variables in a compact dimensional space. In the later phase, a control graph based on the squares of the prediction errors is constructed in order to evaluate the behavior of the composite variables found. The results indicate that the process is not marginally stable and it is necessary to reduce its variability margin.
Subjects: 
chemical industry
data reduction
statistical analysis
multivariate qualitycontrol
variability
JEL: 
C19
C38
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Article

Files in This Item:
File
Size
938.08 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.