Recent studies have shown the X-bar control chart with variable sampling interval detects shifts in the process mean faster than the traditional X-bar chart. These studies are usually based on the assumption that the process data are independently and normally distributed. However, many situations in practice violate these assumptions. In this study, a methodology is developed to economically ...

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...

the paper presents an economical model for double variable acceptance sampling with inspection errors. taguchi cost function is used as acceptance cost while quality specification functions are normal with known variance. an optimization model is developed for double variables acceptance sampling scheme at the presence of inspection errors with either constant or monotone value functions. the m...