Distribution-Free SPC Methods for Monitoring Variability of Autocorrelated Processes
نویسنده
چکیده
We consider the problem of monitoring variability of autocorrelated processes. This paper combines variance estimation techniques from simulation literature with two statistical process control charts from statistical process control (SPC) literature. The proposed SPC methods do not require any assumptions on the distribution of the underlying process and use a variance estimate from each batch as a basic observation. The control limits of the charts are determined analytically, and the choice of a good batch size is discussed in the paper. The proposed charts are tested using stationary processes with both normal and nonnormal marginals.
منابع مشابه
Statistical process control via context modeling of finite-state processes: an application to production monitoring
Conventional Statistical Process Control (SPC) schemes fail to monitor nonlinear and finite-state processes that often result from feedback-controlled processes. SPC methods that are designed to monitor autocorrelated processes usually assume a known model (often an ARIMA) that might poorly describe the real process. In this paper, we present a novel SPC methodology based on context modeling of...
متن کاملJntegration of Data Mining Algorithms and Control Charts . for Multivariate and Auto Correlated Processes
INTEGRATION OF DATA MJNING ALGORITHMS AND CONTROL' CBARI'S FOR MULTIVARIATE AND AUTOCORRELATED PROCESSES WEERAWAT JITPITAKLERT, Ph.D. ,The University of Texas at Arlington, 2009 Supervising Professor: Seoung Bum Kim The objective of tllli3 dissertation is to integrate state-of-the-art data mining 3lgoritbms with statistical process control (SPC) tools to a.chieve efficient 'monitoring in multiv...
متن کاملChart for Monitoring Univariate Autocorrelated Processes
I N recent years, statistical process control (SPC) for autocorrelated processes has received a great deal of attention, due in part to the increasing prevalence of autocorrelation in process inspection data. With improvements in measurement and data collection technology, processes can be sampled at higher rates, which often leads to data autocorrelation. It is well known that the run length p...
متن کاملData mining model-based control charts for multivariate and autocorrelated processes
Process monitoring and diagnosis have been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior and quality improvement. Although traditional statistical process control (SPC) tools are effective in simple manufacturing processes that generate a small volume of independent data, these tools are not capable of handling the large streams of mul...
متن کاملDrift Change Point Estimation in the rate and dependence Parameters of Autocorrelated Poisson Count Processes Using MLE Approach: An Application to IP Counts Data
Change point estimation in the area of statistical process control has received considerable attentions in the recent decades because it helps process engineer to identify and remove assignable causes as quickly as possible. On the other hand, improving in measurement systems and data storage, lead to taking observations very close to each other in time and as a result increasing autocorrelatio...
متن کامل