Overlap in Automatic Root Cause Analysis in Manufacturing: An Information Theory-Based Approach

被引:2
|
作者
Oliveira, Eduardo [1 ]
Migueis, Vera L. L. [2 ]
Borges, Jose L. [2 ]
机构
[1] Inst Ciencia & Inovacao Engn Mecan & Engn Ind INE, Associate Lab Energy Transports & Aerosp LAETA, Campus FEUP,R Dr Roberto Frias 400, P-4200465 Porto, Portugal
[2] Univ Porto, Inst Engn Sistemas & Comp Tecnol & Ciencia INESC, Fac Engn, Campus FEUP,R Dr Roberto Frias 400, P-4200465 Porto, Portugal
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 06期
关键词
Root Cause Analysis; manufacturing; fault diagnosis; data mining; information theory; DIAGNOSIS; FAULTS;
D O I
10.3390/app13063416
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Automatic Root Cause Analysis solutions aid analysts in finding problems' root causes by using automatic data analysis. When trying to locate the root cause of a problem in a manufacturing process, an issue-denominated overlap can occur. Overlap can impede automated diagnosis using algorithms, as the data make it impossible to discern the influence of each machine on the quality of products. This paper proposes a new measure of overlap based on an information theory concept called Positive Mutual Information. This new measure allows for a more detailed analysis. A new approach is developed for automatically finding the root causes of problems when overlap occurs. A visualization that depicts overlapped locations is also proposed to ease practitioners' analysis. The proposed solution is validated in simulated and real case-study data. Compared to previous solutions, the proposed approach improves the capacity to pinpoint a problem's root causes.
引用
收藏
页数:18
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