Control charts such as X and R charts are widely used in industry to monitor quality. These charts are effective in detecting large departures from the in-control condition. Other process monitoring methods, such as Cumulative Sum (CUSUM) charts are sequential in nature as they accumulate information from previous observations. CUSUM charts are good at detecting more moderate presistent process...

Statistical process control is a very useful method to improve the product quality and reduce reworks and scraps. In a production environment, control charts are the most important tool to determine whether a process is in-control or out-of-control. Control charts are to detect the occurrence of the shifts in a process rapidly so that their causes can be found and the necessary corrective actio...

The notion of variation and determining and eliminating it has become a subject that has found a wide application area after total quality approach has become widespread. There is a variety of control charts used in determining variation. Since the 1920’s, when W.Shewhart developed the first control chart, control charts, which have been examined many times in every aspect, are accepted to be o...

Statistical quality control using charts is an easy-to-implement method to improve quality. Improvements in the of products and services are continuously implemented meet consumer needs. Products must maintain desired with as few defects possible. Variations naturally created Unintentional variation, but cause can be found. Control used monitor production; particularly serving early warning ind...

in quality control charts, the problem of determining the optimum process mean arises when the deviation of a quality characteristic in one direction is more harmful than in the opposite direction. the failure mode in these two directions is usually different. a great majority of researches in this area have considered asymmet-ric cost function for processes with single quality characteristics....