Enhancing data quality and process optimization for smart manufacturing lines in industry 4.0 scenarios

Author:

Paasche Simon1,Groppe Sven2

Affiliation:

1. Robert Bosch GmbH, Salzgitter, Germany

2. University of Lübeck, Germany

Publisher

ACM

Cited by 5 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. A Finite State Automaton for Green Data Validation in a Real-World Smart Manufacturing Environment with Special Regard to Time-Outs and Overtaking;Future Internet;2023-10-26

2. Using Machine Learning and Routing Protocols for Optimizing Distributed SPARQL Queries in Collaboration;Computers;2023-10-17

3. Poster: Handling Inconsistent Data in Industry 4.0;Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems;2023-06-27

4. Data Shower in Electronics Manufacturing: Measuring Wi-Fi 4, Wi-Fi 6, and 5G SA behavior in production assembly lines;2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S);2023-06

5. A SPARQL benchmark for distributed databases in IoT environments;Proceedings of The International Workshop on Big Data in Emergent Distributed Environments;2022-06-12

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