Authors: Nandini Das; Lalit Sachan
Addresses: SQC&OR Unit, Indian Statistical Institute, 203 B T Road, Kolkata-700108, India ' SQC&OR Unit, Indian Statistical Institute, 203 B T Road, Kolkata-700108, India
Abstract: Control charts are very effective tools used for detecting whether there is any assignable cause of variation. They are usually developed under the assumption of independent and normally distributed data, an assumption rarely true in practice, and implemented with estimated control limits. But in general, we essentially want to control the process mean value and the process standard deviation, independently of the data distribution. In order to monitor these parameters, it thus seems sensible to advance with control charts based on robust statistics, because these statistics are expected to be more resistant to moderate changes in the underlying process distribution. In this paper, we will propose some alternatives control charts for controlling location parameters based on some robust estimators. We will also show the performance of the proposed control charts and compare them with some existing robust control chart.
Keywords: robust estimation; MDMAD chart; Sn statistics; Qn statistics; ARL; control charts; parameter estimation; process mean value; process standard deviation; location parameters; statistical process control; SPC.
International Journal of Productivity and Quality Management, 2013 Vol.12 No.1, pp.18 - 37
Published online: 31 Mar 2014 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article