Towards less energy intensive heavy-duty machine tools: Power consumption characteristics and energy-saving strategies
Zhendong Shang,
Dong Gao,
Zhipeng Jiang and
Yong Lu
Energy, 2019, vol. 178, issue C, 263-276
Abstract:
Energy conservation in manufacturing sector has received growing attention in an increasingly more carbon-restrained world due to the great concerns over climate change. The heavy-duty machine tool is usually the critical equipment in a factory, which consumes much more power than normal-sized machine tool but received less attention regarding energy saving. In this research, a generic power consumption model was developed from three hierarchies (i.e. system boundary definition, generic power consumption framework and detailed power consumption), which integrates the design parameters of the machine tool thus enabling the prediction of the power consumption even when the machine tool is physically unavailable. In addition, the relations between the power consumed in air-cutting and cutting states were also discussed, which can significantly simplify the study on machine tool power characteristics. The proposed model was verified by experiments and five power consumption characteristics of the tested heavy-duty machine tools were summarised. Additionally, four strategies for designing an energy-efficient machine tool and four tactics for using an existing machine tool more energy efficiently were proposed. This study represents part of a major comprehensive energy conservation research programme for heavy-duty machine tools, which aims to find solutions to improved energy efficiency for the manufacturing industry.
Keywords: Machine tool; Heavy-duty machine; Power consumption; Power model; Energy saving (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:178:y:2019:i:c:p:263-276
DOI: 10.1016/j.energy.2019.04.133
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