@inproceedings{395aecbcb1b943a8aabd6e1cbe79045e,
title = "Applications of machine learning algorithms to predictive manufacturing: Trends and application of tool wear compensation parameter recommendation",
abstract = "The manufacturing industry has become more competitive because of globalization and fast change in the industry. To survive from the global market, manufacturing enterprises should reduce the product cost and increase the productivity. The most promising way is applying the information communication technology especially machine learning algorithms to the traditional manufacturing system. This paper presents recent trends of applying machine learning techniques to manufacturing system and briey explains each kind of applications. As a representative application of machine learning algorithms to manufacturing system, a generalized tool wear compensation parameter recommendation framework using regression algorithms and preliminary results using real data gathered from local and small manufacturing are also presented.",
keywords = "Machine learning, Predictive manufacturing, Tool wear compensation parameter recommendation",
author = "Han, \{Ji Hyeong\} and Rockwon Kim and Chi, \{Su Young\}",
note = "Publisher Copyright: {\textcopyright}2015 ACM.; 2015 International Conference on Big Data Applications and Services, BigDAS 2015 ; Conference date: 20-10-2015 Through 23-10-2015",
year = "2015",
month = oct,
day = "20",
doi = "10.1145/2837060.2837066",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "51--57",
editor = "Aziz Nasridinov and Leung, \{Carson K.\}",
booktitle = "Proceedings of the 2015 International Conference on Big Data Applications and Services, BigDAS 2015",
}
