Title :
Statistical process control by model Bayesian
Author :
Camargo, M.E. ; Filho, W.P. ; Dullius, A. I dos Santos ; Russo, S.L. ; Galelli, A.
Author_Institution :
Univ. of Caxias do Sul, Caxias
Abstract :
Currently considerable attention has been given to the effect of data correlation on statistical process control (SPC). Use of traditional SPC methods when observations are correlated often leads to misleading conclusions as to whether or not the process is under control. The objective of this paper is to develop an algorithm to adjust a Dynamic Linear Model, to calculate the run length distribution (RLD), the average run length (ARL), standard deviation of the run length (SRL), for residual control charts X macr and R. The algorithm is applied to data collected from a textile company. The results showed that the process had been out of control needing systematic monitoring, with the objective of improving the quality of the products.
Keywords :
Bayes methods; control charts; optimisation; quality control; statistical process control; textile industry; Bayesian model; average run length; dynamic linear model; products quality improvement; residual control charts; run length distribution; standard deviation; statistical process control; textile company; Autocorrelation; Bayesian methods; Control charts; Electronic mail; Equations; Monitoring; Process control; Standards development; Textiles; Yttrium; Dynamic Linear Model; algorithm; autocorrelated processes; residual control charts;
Conference_Titel :
Management of Innovation and Technology, 2008. ICMIT 2008. 4th IEEE International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4244-2329-3
Electronic_ISBN :
978-1-4244-2330-9
DOI :
10.1109/ICMIT.2008.4654459
