Detecting and estimating the time of a single-step change in nonlinear profiles using artificial neural networks

被引：0
作者：
Ali Ghazizadeh
Mehrdad Sarani
Mahdi Hamid
Ahmad Ghasemkhani
机构：
[1] Sharif University of Technology,Department of Industrial Engineering
[2] Iran University of Science and Technology,School of Industrial Engineering
[3] University of Tehran,School of Industrial Engineering, College of Engineering
来源：
International Journal of System Assurance Engineering and Management | 2023年 / 14卷
关键词：
Statistical process control; Non-linear profile; Step change point; Artificial Neural Network; Multi-layer perceptron;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This effort attempts to study the change point problem in the area of non-linear profiles. A method based on Artificial Neural Networks (ANN) is proposed for estimating the real time of a single step change. The feature vector of the proposed Multi-Layer Perceptron (MLP) is based on Z and control chart statistics for nonlinear profiles. The merits of the proposed estimator are evaluated through simulation experiments. The results show that the estimator provides an accurate estimate of the single step change point in non-linear profiles in the selected case problem.
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页码：74 / 86
页数：12
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