Key Elements to Contextualize AI-Driven Condition Monitoring Systems towards Their Risk-Based Evaluation
Author:
Affiliation:
1. National Institute of Standards & Technology,Communications Technology Laboratory,Gaithersburg,Maryland,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10123435/10123441/10123562.pdf?arnumber=10123562
Reference21 articles.
1. Quality and inspection of machining operations: tool condition monitoring;roth john;Journal of Manufacturing Science and Engineering,2010
2. State-of-the-art methods and results in tool condition monitoring: a review
3. Quantification of Condition Monitoring Benefit for Offshore Wind Turbines
4. A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests
5. A review of diagnostic and prognostic capabilities and best practices for manufacturing;vogl gregory;Journal of Intelligent Manufacturing,2019
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1. A Simulation-Based Approach to Assess Condition Monitoring-Enabled Maintenance in Manufacturing;2023 7th International Conference on System Reliability and Safety (ICSRS);2023-11-22
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