Generating Causal Hypotheses for Explaining Black-Box Industrial Processes

Author:

Balzereit Kaja1,Diedrich Alexander2,Kubus Daniel3,Ginster Jonas2,Bunte Andreas2

Affiliation:

1. Fraunhofer IOSB, Industrial Automation Branch (IOSB-INA) Fraunhofer Center for Machine Learning,Lemgo,Germany

2. Fraunhofer IOSB-INA Fraunhofer Center for Machine Learning,Lemgo,Germany

3. ContiTech AG,Hanover,Germany

Publisher

IEEE

Reference36 articles.

1. Automated Reconfiguration of Cyber-Physical Production Systems using Satisfiability Modulo Theories

2. Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory

3. EFFRA Vision for a manufacturing partnership in Horizon Europe. 2021–2027;European Factories of the Future Research Association,2019

4. Data-driven Identification of Causal Dependencies in Cyber-Physical Production Systems

5. Hierarchical diagnosis in strong fault models;stern;Twenty Fifth International Workshop on Principles of Diagnosis,0

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Concept of a causality-driven fault diagnosis system for cyber-physical production systems;2023 IEEE 21st International Conference on Industrial Informatics (INDIN);2023-07-18

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