Monitoring the Machining State of Machine Tools Using Artificial Neural Networks with Time-series Data
Journal of the Korean Society for Precision Engineering (JKSPE) is devoted to publishing original research articles with high ethical standard on all aspects of precision engineering and manufacturing. Specifically, the journal focuses on articles related to improving the precision of machines and manufacturing processes through implementation of creative solutions that stem from advanced research using novel experimental methods, predictive modeling techniques, and rigorous analyses based on mechanical engineering or multidisciplinary approach. The expected outcomes of the knowledge disseminated from JKSPE are enhanced reliability, better motion precision, higher measurement accuracy, and sufficient reliability of precision systems, 한국정밀공학회지
Authors
- Deug-Woo Lee (ORCID: https://orcid.org/0000-0001-7462-8341)
- Kang-Seok Kim (ORCID: https://orcid.org/0009-0001-4756-6402)
Publication Details
- Journal
- Journal of the Korean Society for Precision Engineering
- Published
- 2024-08-01
- DOI
- https://doi.org/10.7736/jkspe.024.026
- Citations
- 2
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.43
Funders
- Pusan National University