A parameters reduction method for monitoring multiple linear regression profiles

In certain applications of statistical process control, it is possible to model quality of a product or process using a multiple linear regression profile. Some methods exist in the literature which could be used for monitoring multiple linear regression profiles. However, the performance of most of these methods deteriorates as the number of regression parameters increases. In this paper, we specifically concentrate on phase II monitoring of multiple linear regression profiles and propose a new dimension reduction method to overcome the dimensionality problem of some of the existing methods. The robustness, effectiveness, and limitations of the proposed method are also discussed. Simulation results show that in term of average run length criterion, the proposed method outperforms the traditional methods and has comparable performance with another dimension reduction method in the literature.