@inproceedings{f0965d16eff041b0a509cffe8ec0761d,
title = "An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools",
abstract = "Improving the energy efficiency of machine tools proves to be an important step towards sustainable manufacturing due to their enormous quantity and substantial amounts of energy consumption. How to quantify the energy efficiency of machine tools to support energy-efficient design and energy labeling is a critical issue. Based on the finding that all possible energy efficiency values of a machine tool are distributed within an Inherent Energy Efficiency Surface (IEES) of the machine tool itself, this paper investigates the characteristics of IEES and proposes an IEES-based method for energy labeling. To decouple the IEES from the workpiece machined, cutting tools and operation conditions, standardized domain cells for the description of IEES surface domain are developed according to the series of preferred numbers. The surface peak and surface mean are selected to respectively characterize the maximum and mean energy efficiency of machine tool when machining all possible tasks. Case studies and comparison analysis has showed that the proposed method has better performance in the standardization for energy labeling.",
author = "Peiji Liu and Xu Wang and Chao Liu and Qian Zhu and Yameng Shi and Pai Zheng",
year = "2023",
month = sep,
day = "28",
doi = "10.1109/case56687.2023.10260611",
language = "English",
isbn = "979-8-3503-2070-1",
series = "2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)",
publisher = "IEEE",
booktitle = "2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)",
address = "United States",
note = "2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) ; Conference date: 26-08-2023 Through 30-08-2023",
}