An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools

Peiji Liu; Xu Wang; Chao Liu; Qian Zhu; Yameng Shi; Pai Zheng

doi:10.1109/CASE56687.2023.10260611

An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools

Peiji Liu
, Xu Wang
, Chao Liu
, Qian Zhu
, Yameng Shi
, Pai Zheng

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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.

Original language	English
Title of host publication	2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
Publisher	IEEE Computer Society
Number of pages	6
ISBN (Electronic)	9798350320695
DOIs	https://doi.org/10.1109/CASE56687.2023.10260611
Publication status	Published - Aug 2023
Event	19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand Duration: 26 Aug 2023 → 30 Aug 2023

Publication series

Name	IEEE International Conference on Automation Science and Engineering
Volume	2023-August
ISSN (Print)	2161-8070
ISSN (Electronic)	2161-8089

Conference

Conference	19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/Territory	New Zealand
City	Auckland
Period	26/08/23 → 30/08/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

More information

10.1109/CASE56687.2023.10260611

Cite this

Liu, P., Wang, X., Liu, C., Zhu, Q., Shi, Y., & Zheng, P. (2023). An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools. In 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023 (IEEE International Conference on Automation Science and Engineering; Vol. 2023-August). IEEE Computer Society. https://doi.org/10.1109/CASE56687.2023.10260611

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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",

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month = aug,

doi = "10.1109/CASE56687.2023.10260611",

language = "English",

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Liu, P, Wang, X, Liu, C, Zhu, Q, Shi, Y & Zheng, P 2023, An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools. in 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023. IEEE International Conference on Automation Science and Engineering, vol. 2023-August, IEEE Computer Society, 19th IEEE International Conference on Automation Science and Engineering, CASE 2023, Auckland, New Zealand, 26/08/23. https://doi.org/10.1109/CASE56687.2023.10260611

An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools. / Liu, Peiji; Wang, Xu; Liu, Chao et al.
2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023. IEEE Computer Society, 2023. (IEEE International Conference on Automation Science and Engineering; Vol. 2023-August).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Wang, Xu

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AU - Zhu, Qian

AU - Shi, Yameng

AU - Zheng, Pai

PY - 2023/8

Y1 - 2023/8

N2 - 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.

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AN - SCOPUS:85174394613

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ER -

An Investigation on Inherent Energy Efficiency Surface for Energy Labelling of Machine Tools

Abstract

Publication series

Conference

UN SDGs

ASJC Scopus subject areas

More information

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