Previsão da exportação brasileira de açúcar avaliada por meio de gráficos de controle de resíduos

Sugar production and exportation are important factors for the Brazilian economy, because Brazil produces the largest amount of sugar and accounts for almost half of the world´s sugar exports. This research aimed to monitor the sugar export from January 2000 to April 2019, by means of residual control charts with pretreatment of autoregressive integrated moving average (ARIMA) models. The data used in the study were collected from the Portal Única website. We opted for the application of ARIMA modeling because the data was not stationarity and presented autocorrelated values. The best model to predict the Brazilian sugar exports was SARIMA (1,1,1)(1,0,1)6 due to the seasonal behavior of the series, which may be related to the sugarcane planting and harvesting period. It was possible to observe the presence of upper-limit outliers in the residual control chart, in October 2012 and February 2016, which characterize a sugar exports higher than forecasted exports.

Monitoring the process quality for multistage systems with multiple characteristics

Purpose The purpose of this paper is to provide a new approach for detecting the small sustained process shifts in multistage systems with correlated multiple quality characteristics. Design/methodology/approach The authors propose a new multivariate linear regression model for a multistage manufacturing system with multivariate quality characteristics in which both the auto-correlated process outputs and the correlations occurring between neighboring stages are considered. Then, the multistage multivariate residual control charts are constructed to monitor the overall process quality of multistage systems with multiple quality characteristics. Moreover, an overall run length concept is adopted to evaluate the performances of the authors’ proposed control charts. Findings In the numerical example with cascade data, the authors show that the detecting abilities of the proposed multistage residual MEWMA and MCUSUM control charts outperform those of Phase II MEWMA and MCUSUM control charts. It further demonstrates the usefulness of the authors’ proposed control charts in the Phase II monitoring. Practical implications The research results of this paper can be applied to any multistage manufacturing or service system with multivariate quality characteristics. This new approach provides quality practitioners a better decision making tool for detecting the small sustained process shifts in multistage systems. Originality/value Once the multistage multivariate residual control charts are constructed, one can employ them in monitoring and controlling the process quality of multistage systems with multiple characteristics. This approach can lead to the direction of continuous improvement for any product or service within a company.