Univariate and multivariate control charts for monitoring sugar production process

• Main Authors: Sutirman, Zetty Azrah, Mohamad, Ismail
• Format: Conference or Workshop Item
• Language: English
• Published: 2015
• Subjects: TS156.6 Quality Control
• Online Access: http://eprints.utm.my/id/eprint/62201/1/IsmailMohamad2015_UnivariateandMultivariateControlChartsforMonitoringSugarProductionProcess.pdf; http://eprints.utm.my/id/eprint/62201/

Quality control is a system to maintain quality of product or service to achieve specification standard of product. One of the most powerful tools is through graphical method which is control chart. This is because control chart easy to analyse the data and able to provide comprehensive information on existing product or process characteristics. There are two types of control chart. First, statistical process control (SPC) and second is multivariate statistical process control (MSPC). Statistical process control commonly referred as SPC, was developed by Dr. Walter A. Shewhart in the mid-1920s. In general, statistical process control is to control and monitor the process of production line and detect abnormal process. However , the Shewhart control chart can only monitor single process variable at a time. Multivariate statistical process control , MSPC was established by Hotelling in his 1947 pioneering paper. MSPC can simultaneously control and monitor more than one process variables at a time. The three most popular multivariate control statistics of multivariate control charts, such as Shewhart charts (x and Range charts) ,cumulative sum plots (CUSUM), and exponentially weighted moving average charts (EMWA).