Monitoring the Machining State of Machine Tools Using Artificial Neural Networks with Time-series Data
Year: 2024
Type: article
Abstract: 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: Kang Seok Kim, Deug Woo Lee
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Funder: Pusan National University
OpenAlex ID: W4401377372