Tese
Metodologia para a detecção da fonte de variabilidade em gráficos de controle multivariados para processos com dados de autocorrelação serial
Fecha
2023-02-24Autor
Ueda, Renan Mitsuo
Institución
Resumen
The modernizing of the industrial manufacturing process requires simultaneous
monitoring of product and process quality characteristics. Multivariate Statistical
Process Control (MSPC) are able to assess the existing dependence between the
investigated variables. In several hypotheses, the autocorrelation between the
analyzed variables is present, where one of the main causes is the gradual wear and
tear of machines and equipment. The use of multivariate control charts allows the
process to be monitored in real time, ensuring the reduction of variability in the
production system. The objective of this research is to propose a methodology based
on residuals from vector autoregressive (VAR) models and vectors error correction
(VEC), combined with Hotelling's T2 decomposition to identify the variable causing
instability in the process. The methodology was tested through simulations and
application to real data. Hotelling's T2 control chart, prepared from the residuals of the
vector models, accurately indicated the intentionally incorporated outliers, and the T2
decomposition technique effectively pointed out the variable causing the variability. In
terms of practical contributions, there was a combination of two distinct areas of
knowledge: quality engineering and econometrics. The research sought to bring the
academy closer to the industrial sector, since the focus of this methodology is to help
managers and professionals who work in the area to deal with the presence of
autocorrelated data in production processes. The use of this methodology helps in
manufacturing competitiveness, and consequently, in the generation of employment
and income for the sector. For future research, it is strongly suggested the application
of this methodology in other industrial processes, combining other tools, and
confronting them with different types of MSPCs.