Authors: Azadeh Adibi; Douglas C. Montgomery; Connie M. Borror
Addresses: School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, 699 S Mill Ave, Tempe, AZ 85281, USA ' School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, 699 S Mill Ave, Tempe, AZ 85281, USA ' School of Mathematical and Natural Sciences, Arizona State University at the West Campus, P.O. Box 37100, Phoenix, AZ 85069, USA
Abstract: We propose a P-value-based method to assess the performance of linear profiles in phase II. Performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of a linear model. In our proposed approach, P-values are computed at each level within a sample. If at least one of the P-values is less than a pre-specified significance level, chart signals out-of-control. The primary advantage of our approach is that only one control chart is required to monitor three parameters simultaneously: the intercept, slope, and standard deviation. A comprehensive comparison of the proposed method and the existing KMW-Shewhart method for monitoring linear profiles is conducted. In addition, the effect that number of observations within a sample has on the performance of the proposed method is investigated. A simulation study shows that the proposed P-value method performs satisfactorily in terms of average run length compared to KMW-Shewhart method.
Keywords: average run length; ARL; control charts; linear regression; Phase II monitoring; profile monitoring; P-value; linear profiles; process modelling; process quality; simulation; statistical process control; SPC.
International Journal of Quality Engineering and Technology, 2014 Vol.4 No.2, pp.97 - 106
Published online: 14 Apr 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article