TY - GEN
T1 - A Revised KDD Procedure for the Modeling of Continuous Production in Powder Processing
AU - Vernickel, K.
AU - Weber, J.
AU - Li, X.
AU - Berg, J.
AU - Reinhart, G.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - In this paper, a revised Knowledge Discovery in Databases (KDD) procedure is proposed, which is designed especially for data mining in powder processing and other types of continuous production. The revised KDD procedure includes data preprocessing, feature engineering, machine learning and model evaluation. The proposed methods are implemented and evaluated using a dataset from a fluidized bed opposed jet mill. The evaluation results show that the machine learning model can accurately predict the product quality in this scenario and capture the internal relations between processing parameters and product quality.
AB - In this paper, a revised Knowledge Discovery in Databases (KDD) procedure is proposed, which is designed especially for data mining in powder processing and other types of continuous production. The revised KDD procedure includes data preprocessing, feature engineering, machine learning and model evaluation. The proposed methods are implemented and evaluated using a dataset from a fluidized bed opposed jet mill. The evaluation results show that the machine learning model can accurately predict the product quality in this scenario and capture the internal relations between processing parameters and product quality.
KW - KDD
KW - Machine Learning
KW - Powder Processing
UR - http://www.scopus.com/inward/record.url?scp=85079637546&partnerID=8YFLogxK
U2 - 10.1109/IEEM44572.2019.8978828
DO - 10.1109/IEEM44572.2019.8978828
M3 - Conference contribution
AN - SCOPUS:85079637546
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 340
EP - 344
BT - 2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
PB - IEEE Computer Society
T2 - 2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
Y2 - 15 December 2019 through 18 December 2019
ER -