Identification of the assignable causes of process variability and the restriction and elimination of their influence are the main goals of statistical process control (SPC). Identification of these causes is associated with so called tests for special causes or runs tests. From the time of the formulation of the first set of such rules (Western Electric rules) several different...

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...

Control chart is the most well-known chart to monitor the number of nonconformities per inspection unit where each sample consists of constant size. Generally, the design of a control chart requires determination of sample size, sampling interval, and control limits width. Optimally selecting these parameters depends on several process parameters, which have been considered from statistical and...

Traditional statistical process control charts used to monitor key process variables are based on the assumption that measurements are independent and identically distributed about a target value. In practice they are not and often are actually correlated. Reliance on univariate charts can lead to misleading conclusions. This paper addresses the methods for improving the quality of industrial p...

The Multivariate EWMA control chart, MEWMA, Lowry, Woodall, Champ and Ridgon [1] and its univariate version EWMA, may be designed to efficiently detect small shifts in the mean vector of a set of p quality characteristics of a production process. However, this work presents a method for the optimal design of MEWMA and EWMA charts parameters to control processes where it is not convenient to det...

This paper focuses on the design and development of an expert system for on-line detection of various control chart patterns so as to enable the quality control practitioners to initiate prompt corrective actions for an out-of-control manufacturing process. Using this expert system developed in Visual BASIC 6, all the nine most commonly observed control chart patterns, e.g., normal, stratificat...

Control charts have been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior and quality improvement. In particular, multivariate control charts have been effectively used when a process involves a number of correlated process variables. Most existing multivariate control charts were developed using the assumption of normally distributed pro...

CCC-r chart extended approach of CCC charts, is a technique applied when nonconforming items are rarely observed. However, it is usually assumed that the inspection process is perfect in the implementation control charts imperfect inspections may have a significant impact on the performance of the control chart and setting the control limits. This paper first investigates the ...