This study develops a least squares support vector machines (LS-SVM) based model for bivariate process to diagnose abnormal patterns of process mean vector, and to help identify abnormal variable(s) when Shewhart-type multivariate control charts based on Hotelling’s T 2 are used. On the basis of studying and defining the normal/abnormal patterns of the bivariate process mean shifts, a LS-SVM pa...

An algorithm for locating all occurrences of a finite number of keywords in an arbitrary string, also known as multiple strings matching, is commonly required in information retrieval (such as sequence analysis, evolutionary biological studies, gene/protein identification and network intrusion detection) and text editing applications. Although Aho-Corasick was one of the commonly used exact mul...

Statistical process monitoring (SPM) literature recommends the combination of Shewhart and exponentially weighted moving average (EWMA) schemes to improve ability standalone EWMA in detecting small large shifts. The resulting scheme is named combined (or composite) Shewhart-EWMA (CSEWMA) scheme. In this paper, a new single composite (denoted as SCSEWMA) for mean when parameters are known or unk...

The Shewhart, Bonferroni-adjustment and analysis of means (ANOM) control chart are typically applied to monitor the mean of a quality characteristic. The Shewhart and Bonferroni procedure are utilized to recognize special causes in production process, where the control limits are constructed by assuming normal distribution for known parameters (mean and standard deviation), and approximately no...

We describe the adaptation of the decision limit cumulative sum method (cusum) to internal quality control in clinical chemistry. With the decision limit method, the cusum is interpreted against a numerical limit, rather than by use of a V-mask. The method can be readily implemented in computerized quality-control systems or manually on controls charts. We emphasize the manual application here ...

The accuracy of the measurement system is vital for reliable process monitoring using statistical control charts. applied chart’s effectiveness depends on system's performance. Measurement uncertainty can lead to incorrect decisions like unnecessary stops or failure intervene. In this paper, we investigated effect errors performance four well-established combined charts mean normally distribute...

Abstract: Today's society is characterized by consumers becoming more educated and demanding for products and services they use. Wherever, organizations are structured to respond the explicit or implicit needs of consumers, which lead to increased competitiveness of organizations. This competitiveness is reflected in the ongoing quest to provide high quality products and excellence process deve...

One of the most powerful tools in quality control is the statistical control chart. First developed in the 1920's by Walter Shewhart, the control chart found widespread use during World War II and has been employed, with various modifications ever since. The drawbacks to multivariate charting schemes is their inability to identify which variable was the source of the signal. The multivariate ex...