Production
https://prod.org.br/doi/10.1590/S0103-65132011005000001?lang=en
Production
Article

Método para aplicação de gráficos de controle de regressão no monitoramento de processos

Method for applying regression control charts to process monitoring

Pedrini, Danilo Cuzzuol; Caten, Carla Schwengber ten

Downloads: 0
Views: 785

Resumo

Este artigo propõe um método para a aplicação do gráfico de controle de regressão no monitoramento de processos industriais. Visando facilitar a aplicação do gráfico, o método é apresentado em duas fases: análise retrospectiva (Fase I) e monitoramento do processo (Fase II), além de incluir uma modificação do gráfico de controle de regressão múltipla, permitindo o monitoramento direto da característica de qualidade do processo ao invés do monitoramento dos resíduos padronizados do modelo. Também é proposto o gráfico de controle de extrapolação, que verifica se as variáveis de controle extrapolam o conjunto de valores utilizado para estimar o modelo de regressão. O método foi aplicado em um processo de uma indústria de borrachas. O desempenho do gráfico de controle foi avaliado pelo Número Médio de Amostras (NMA) até o sinal através do método de Monte Carlo, mostrando a eficiência do gráfico em detectar algumas modificações nos parâmetros do processo.

Palavras-chave

Gráfico de controle de regressão. Modelos de regressão linear. Número médio de amostras.

Abstract

This work proposes a method for the application of regression control charts in the monitoring of manufacturing processes. The proposed method is presented in two phases: retrospective analysis (Phase I) and process monitoring (Phase II). It includes a simple modification of the multiple regression control chart, allowing the monitoring of the values of quality characteristics of the process, instead of monitoring the regression standardized residuals. It also proposes an extrapolation control chart, which verifies whether the control variables extrapolate the set of data used in regression model estimation. The proposed method was successfully applied in a rubber manufacturing process. The Average Run Length (ARL) distribution was estimated using the Monte Carlo method, proving the efficiency of the proposed chart in detecting some alterations in process parameters.

Keywords

Regression control chart. Linear regression models. Average run length.

References



AIZENCHTADT, E.; INGMAN, D.; FRIEDLER, E. Quality control of wastewater treatment: a new approach. European Journal of Operations Research, v. 189, p. 445-458, 2008.

FALTIN, F. W. et al. Considerations in the monitoring of the autocorrelated and independent data. Journal of Quality Technology, v. 29, n. 2, p. 131-133, 1997.

HAUCK, D. J.; RUNER, G. C.; MONTGOMERY, D. C. Multivariate statistical process monitoring and diagnosis with grouped regression-adjusted variables. Comunications in Statistics - Simulation and Computation, v. 28, n. 2, p. 309-328, 1999.

HAWKINS, D. M. Multivariate quality control based on reegression-adjusted variables. Technometrics, v. 33, n. 1, p. 61-75, 1991.

HAWKINS, D. M. Regression adjustment for variables in multivariate quality control. Journal of Quality Technology, v. 25, n. 3, p. 170-182, 1993.

HAWORTH, D. A. Regression control chart to manage software maintenance. Journal of Software Maintenance, v. 8, n. 1, p. 35-48, 1996.

JACOBI, L. F.; SOUZA, A. M.; PEREIRA, J. E. S. Gráfico de controle de regressão aplicado na monitoração de processos. Revista Produção, v. 12, n. 1, p. 46-59, 2002.

JEARKPAPORN, D. et al. Process monitoring for correlated gamma-distributed data using generalized-linear-model-based control charts. Quality and Reliability Engineering International, v. 19, n. 6, p. 477-491, 2003.

JEARKPAPORN, D. et al. Process monitoring for mean shifts for multiple stage processes. International Journal of Production Research, v. 45, n. 3, p. 5547-5570, 2007.

JOHNSON, B.; JOHNSON, C.; SEIBER, J. The use of regression equations for quality control in a pesticide physical property database. Environmental Management, v. 19, n. 1, p. 127-134, 1995.

KANG, L.; ALBIN, S. On-line monitoring when the process yelds linear profiles. Journal of Quality Technology, v. 32, n. 4, p. 418-426, 2000.

LOREDO, E. N.; JEARKPAPORN, D.; BORROR, C. M. Model-based control chart for autoregressive and correlated data. Quality and Reliability Engineering International, v. 18, n. 6, p. 489-496, 2002.

MANDEL, B. J. The regression control chart. Journal of Quality Technology, v. 1, n. 1, p. 1-9, 1969.

MONTGOMERY, D. C. Introdução ao Controle Estatístico da Qualidade. 4. ed. Rio de Janeiro: Editora LTC, 2004. 513 p.

MONTGOMERY, D. C.; MASTRANGELO, C. M. Some statistical process control methods for autocorrelated data. Journal of Quality Technology, v. 23, n. 3, p. 179-193, 1991.

MONTGOMERY, D. C.; VINING, G. G.; PECK, E. A. Introduction to Linear Regression Analysis. 3 ed. New York: John Wiley & Sons, 2001. 641 p.

NETER, J. et al. Applied Linear Statistical Models. 5 ed. New York: Mc Graw-Hill/Irwin, 2005. 1396 p.

OLIN, B. D. Regression control charts revisited: methodology and cases studies. In: ANNUAL FALL TECHNICAL CONFERENCE - AFTC, 42., 1998, New York. Proceedings... New York: American Society for Quality, 1998. 17 p.

OMURA, A. P.; STEFFE, J. H. Mixer viscometry to characterize fluid foods with large particulates. Journal of Food Process Engineering, v. 26, n. 3, p. 435-445, 2003.

SHU, L; TSUNG, F; TSUI, K. L. Run-length perfomance of regression control charts with estimated parameters. Journal of Quality Technology, v. 36, n. 3, p. 280-292, 2004.

SKINNER, K. R.; MONTGOMERY, D. C.; RUNGER, G. C. Process monitoring for multiple count data using generalized linear model-based control charts. International Journal of Production Research, v. 41, n. 6, p. 1167-1180, 2003.

VINING, G. Technical Advice: Phase I and phase II control charts. Quality Engineering, v. 21, n. 4, p. 478-479, 2009.

WADE, M. R.; WOODAL, W. H. A review and analysis of cause-selecting control charts. Journal of Quality Technology, v. 25, n. 3, p. 161-169, 1993.

WOODALL, W. H. Controversions and contradictions in statistical process control. Journal of Quality Technology, v. 32, n. 4, p. 341-350, 2000.

WOODALL, W. H. Current research on profile monitoring. Revista Produção, v. 17, n. 3, p. 420-425, 2007.

WOODALL, W. H. et al. Using control charts to monitor process and product quality profiles. Journal of Quality Technology, v. 36, n. 3, p. 309-320, 2004.

WOODALL, W. H.; MONTGOMERY, D.C. Research issues and ideas in statistical process control. Journal of Quality Technology, v. 31, n. 4, p. 376-386, 1999.

ZHANG, Z. X. Cause-selecting control charts - a new type of quality control charts. The QR Journal, v. 12, p. 221-225, 1985.

5883a3c77f8c9da00c8b4636 1574685864 Articles
Links & Downloads

Production

Share this page
Page Sections