Application of Statistical Monitoring Using Autocorrelated Data and With the Influence of Multicollinearity in a Steel Process (2021)
- Authors:
- Autor USP: SILVA, MESSIAS BORGES - EEL
- Unidade: EEL
- DOI: 10.5539/ijsp.v10n4p96
- Assunto: ENGENHARIA DE PRODUÇÃO
- Keywords: control chart; autocorrelated data; multicollinearity
- Language: Inglês
- Abstract: The purpose of this article is to demonstrate a practical application of control charts in an industrial process that has data auto-correlated with each other. Although the control charts created by Walter A. Shewhart are very effective in monitoring processes, there are very important statistical assumptions for Shewhart's control charts to be applied correctly. Choosing the correct Control Chart is essential for managers to be able to make coherent decisions within companies. With this study, it was possible to demonstrate that the original data collected in the process, which at first appeared to have many special causes of variation, was actually a stable process (no anomalies present). However, this finding required the use of autoregressive models, multivariate statistics, autocorrelation and normality tests, multicollinearity analysis and the use of the EWMA control chart. It was concluded that it is of fundamental importance to choose the appropriate control chart for monitoring industrial processes, to ensure that changes in processes do not incorporate non-existent variations and do not cause an increase in the number of defective products.principal component analysis
- Imprenta:
- Publisher: Canadian Center of Science and Education
- Publisher place: Ontario
- Date published: 2021
- Source:
- Título: International journal of statistics and probability
- ISSN: 1927-7040
- Volume/Número/Paginação/Ano: v.10, n.4, p.96-118, 2021
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: cc-by
-
ABNT
PIMENTA, Cristie Diego et al. Application of Statistical Monitoring Using Autocorrelated Data and With the Influence of Multicollinearity in a Steel Process. International journal of statistics and probability, v. 10, n. 4, p. 96-118, 2021Tradução . . Disponível em: https://doi.org/10.5539/ijsp.v10n4p96. Acesso em: 28 dez. 2025. -
APA
Pimenta, C. D., Silva, M. B., Marins, F. A. S., & Silva, A. F. da. (2021). Application of Statistical Monitoring Using Autocorrelated Data and With the Influence of Multicollinearity in a Steel Process. International journal of statistics and probability, 10( 4), 96-118. doi:10.5539/ijsp.v10n4p96 -
NLM
Pimenta CD, Silva MB, Marins FAS, Silva AF da. Application of Statistical Monitoring Using Autocorrelated Data and With the Influence of Multicollinearity in a Steel Process [Internet]. International journal of statistics and probability. 2021 ;10( 4): 96-118.[citado 2025 dez. 28 ] Available from: https://doi.org/10.5539/ijsp.v10n4p96 -
Vancouver
Pimenta CD, Silva MB, Marins FAS, Silva AF da. Application of Statistical Monitoring Using Autocorrelated Data and With the Influence of Multicollinearity in a Steel Process [Internet]. International journal of statistics and probability. 2021 ;10( 4): 96-118.[citado 2025 dez. 28 ] Available from: https://doi.org/10.5539/ijsp.v10n4p96 - Avaliação da atividade antibacteriana do óleo da microalga Chlorella minutissima como alternativa para o tratamento de dermatite atópica
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Informações sobre o DOI: 10.5539/ijsp.v10n4p96 (Fonte: oaDOI API)
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