Optimisation estimation of uncertainty integrated with production information based on Bayesian fusion method

• Main Authors: Yinbao Cheng, Huadong Fu, Jing Lyu, Zhongyu Wang, Hongli Li, Xiaohuai Chen
• Format: Article
• Language: English
• Published: Wiley 2019-10-01
• Series: The Journal of Engineering
• Subjects: inspection; bayes methods; statistical analysis; sensor fusion; measurement uncertainty; production engineering computing; inference mechanisms; product inspection; optimisation estimation; bayesian fusion method; statistical production information; product detection results; statistical inference principle; uncertainty evaluation; bayesian information fusion model; generation geometrical product specifications; posteriori distribution function
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9213

The new generation Geometrical Product Specifications require consideration of the effects of measurement uncertainty in the product inspection. This study estimated the measurement results and the uncertainty by integrating the statistical production information into the product detection results to rationally and fairly narrow the uncertainty area of qualification determination. Based on the Bayesian information fusion and statistical inference principle, the model of uncertainty evaluation is established. The Bayesian information fusion model integrated measuring information with manufacturing information was built, with which the uncertainty of product inspection was reappraised based on posteriori distribution function. The validity of the proposed method and theory was demonstrated by the example analysis.