[2H3-GS-3b] 知識の利用：社会応用

[2H3-GS-3b-04] Cause Analysis of Chronic Defects in Aluminum Rolling Process

Modelling by Bayesian Network

〇Takahiro Moriguchi¹, Katsuyoshi Asada¹, Naoko Omachi¹, Yoichi Motomura² (1. UACJ Corporation, 2. National Institute of Advanced Industrial Science and Technology)

Keywords:Bayesian network

The purpose of this study is to develop approach for cause analysis of chronic defects in aluminum rolling process which is combination of data-based method and knowledge-based method. In aluminum rolling process, defects can be classified into two types. One is a sporadic defect, which can be controlled by monitoring changing points, and the other is a chronic defect, which is difficult to be controlled. To combine a data-based method and a knowledge-based method, Bayesian networks are used to represent chronic defect mechanism.