Quality control is one of the most used statistical applications in industry. The control of attribute quality characteristics is a subject of study due to the need of improving the efficiency of the charts. The present paper deals with the improvement of the classical u chart, using the Daudin strategy, based in a double sampling scheme and a variable sample size. The DS-u chart is proposed. T...

Traditionally, the statistical quality control techniques utilize either an attributes or variables product quality measure. Recently, some methods such as three-level control chart have been developed for monitoring multi attribute processes. Control chart usually has three design parameters: the sample size (n), the sampling interval (h) and the control limit coefficient (k).The design parame...

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...

Attribute control charts (e.g., charts for counts and proportions) have discrete jumps in the quantities plotted on the charts, which means that the chart designer has only a discrete set of unique control limits to choose from when designing a chart. These charts have a small set of in-control Average Run Lengths (ARLs) from which to determine the appropriate control scheme. In a chart with ra...