Faktor Koreksi Diagram Kendali Shewhart pada Situasi Unconditional ARL dan Penerapannya terhadap Data Brix (Kekentalan) Saus

Statistical Proses Control (SPC) is application of method in statistics on measurements and analysis variation in proses. Shewhart control chart is ussually used as a device in SPC. In practice, the parameters prosses are usually unknown. The parameters prosses is estimated using data often from the previous processes, ARL of the control chart with estimated parameters as called as unconditional ARL. Goedhart et al propose a new correction factor to improve unconditional ARL such data unconditional ARL close to the expected ARL. In this articel we apply the correction factor of Goedhart to brix’s data of PT. XXX. We offten the obtained the upper control limit is 39.51, the lower control limit is 36.87 with mean 38.19 applying this control limit to brix’s data results that the proses is under control. Abstrak. Statistical Proses Control (SPC) merupakan penerapan metode statistik dalam pengukuran dan analisis variasi proses. Alat yang sering digunakan dalam metode SPC yaitu diagram kendali Shewhart. Dalam praktiknya, parameter proses biasanya tidak diketahui. Parameter proses tersebut biasanya diestimasi melalui data yang diperoleh dari proses sebelumnya, ARL untuk diagram kendali dengan parameter yang diestimasi dinamakan ARL unconditional. Goedhart dkk mengusulkan faktor koreksi baru untuk meningkatkan ARL unconditional yang memiliki ekspetasi sebesar ARL yang diharapkan. Dalam artikel ini kami menerapkan faktor koreksi Goedhart terhadap data brix PT. XXX dan diperoleh batas kendali atas 39.51, batas kendali bawah 36.87 dengan rata-rata 38.19 Dari implementasi diagram kendali terhadap data kekentalan diperoleh bahwa proses terkendali.

On power of control chart for the ratio of two Poisson distributions under misclassification error

When the control charts for the ratio of two Poisson distributions need to be constructed, a situation may require controlling the ratio rather than a single parameter. Chakraborty and Khurshid [6] constructed Shewhart control chart and Chakraborty and Khurshid [7] studied measurement error effect on control chart for the ratio of two Poisson distributions, respectively. The effects of misclassification on the performance of control charts have been investigated by several authors. Measurement error variability has uncertainty that can arise from several sources. In this paper, we study the effect of the two sources of variability on the power characteristics of control chart under misclassification error for the ratio of two Poisson distributions as studied by Sahai and Khurshid [36]. Probabilities of misclassification of conforming and non-conforming units for grid of values are provided.

PETA KENDALI EWMA RESIDUAL PADA DATA BERAUTOKORELASI

Control charts with autocorrelation can be overcome by creating control chart with residuals from the best forecasting model. EWMA control chart is a alternative to the Shewhart control chart when detecting small shifts. The purpose of this study is to make the best forecasting model to obtain residual, and see the stability of the rupiah exchange rate against US dollar using EWMA control chart with residual. The best model of the case is ARIMA (1,1,1). The results of the EWMA residual control chart with ? = 0.1 there is a pattern that makes the process unstable.

Design of a New Variable Shewhart Control Chart Using Multiple Dependent State Repetitive Sampling

In this paper, a new variable control chart is proposed using multiple dependent-state repetitive sampling by assuming that the data follows a normal distribution having a symmetry property. Its efficiency will be evaluated in terms of in-control and out-of-control average run lengths. The results showed that the proposed chart is better than the existing variable control chart to detect an early shift in the process. An industrial example is given to illustrate the proposed chart in the industry.