@inproceedings{e030156c8b1945a9bad1ca648132a362,
title = "A new model for predicting power consumption of machining processes: A turning case",
abstract = "Nowadays, discrete manufacturing enterprises are forced to reduce energy consumption owing to high energy cost, growing production demands, and environmental problems. An accurate energy consumption model is needed urgently to achieve this goal. In this paper, a new model based on empirical modeling and experiments is proposed to estimate energy consumption for machining processes. Experimental results show that the new model can make more accurate prediction of energy consumption in comparison with existing models. The new model is of great value to enterprises to develop energy-efficient optimization strategies.",
keywords = "Energy consumption model, green production, machining process, manufacturing process",
author = "Leilei Meng and Mengchu Zhou and Chaoyong Zhang and Guangdong Tian",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 ; Conference date: 21-08-2016 Through 24-08-2016",
year = "2016",
month = nov,
day = "14",
doi = "10.1109/COASE.2016.7743556",
language = "English (US)",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society",
pages = "1289--1294",
booktitle = "2016 IEEE International Conference on Automation Science and Engineering, CASE 2016",
address = "United States",
}