@inproceedings{6b8323d5d0cb40a4af5aaa0b49e84bc1,
title = "Statistical process control based on Kalman filter in manufacturing process",
abstract = "In order to reduce the impact of data noise to quality control and make monitor results more precise in manufacturing process, the method of statistical process control based on Kalman filter was proposed. In this method, the statistical process control model based on Kalman filter was built and the quality control method of exponentially weighted moving average based on Kalman filter was put forward. While monitoring manufacturing process, first the technology of Kalman filter was used to smooth data and to reduce noise, and then control charts were built by the method of exponentially weighted moving average to monitor quality. Finally, the performance of the exponentially weighted moving average method based on Kalman filter and the tranditional exponentially weighted moving average method was compared. The performance result illustrates the feasibility and validity of the proposed quality monitor method.",
keywords = "Data noise, Exponentially weighted moving average, Kalman filter, Statistical process control",
author = "Pei Wang and Zhang, {Ding Hua} and Shan Li and Wang, {Ming Wei} and Bing Chen",
year = "2011",
doi = "10.4028/www.scientific.net/AMR.201-203.986",
language = "英语",
isbn = "9783037850398",
series = "Advanced Materials Research",
pages = "986--989",
booktitle = "Advanced Manufacturing Systems",
note = "2nd International Conference on Manufacturing Science and Engineering, ICMSE 2011 ; Conference date: 09-04-2011 Through 11-04-2011",
}