Monitoring and change-point estimation for spline-modeled non-linear profiles in phase II

Zahra Hadidoust, Yaser Samimi and Hamid Shahriari

Journal of Applied Statistics, 2015, vol. 42, issue 12, 2520-2530

Abstract: In some applications of statistical quality control, quality of a process or a product is best characterized by a functional relationship between a response variable and one or more explanatory variables. This relationship is referred to as a profile. In certain cases, the quality of a process or a product is better described by a non-linear profile which does not follow a specific parametric model. In these circumstances, nonparametric approaches with greater flexibility in modeling the complicated profiles are adopted. In this research, the spline smoothing method is used to model a complicated non-linear profile and the Hotelling T -super-2 control chart based on the spline coefficients is used to monitor the process. After receiving an out-of-control signal, a maximum likelihood estimator is employed for change point estimation. The simulation studies, which include both global and local shifts, provide appropriate evaluation of the performance of the proposed estimation and monitoring procedure. The results indicate that the proposed method detects large global shifts while it is very sensitive in detecting local shifts.

Date: 2015
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DOI: 10.1080/02664763.2015.1043864

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