Green machining technology and application driven by digital intelligence: a review

Tai-Min Luo , Jin Zhang , Chen-Jie Deng , Dai-Xin Luo , Gui-Bao Tao , Hua-Jun Cao

Advances in Manufacturing ›› : 1 -60.

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Advances in Manufacturing ›› : 1 -60. DOI: 10.1007/s40436-025-00567-8
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Green machining technology and application driven by digital intelligence: a review

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Abstract

With the continuous advancement of science and technology, alongside the increasing significant attention within the manufacturing industry, high-performance demands are placed on advanced equipment and components because of extreme temperatures, heavy impact loads, and other challenging operating conditions. The importance of resource conservation and environmental preservation is becoming more widely recognized. This paper reviews green machining technology, driven by digital intelligence. Initially, the background of green machining powered by digital technologies is introduced, focusing on digitalization, intelligence, and sustainability as key factors for improving machining efficiency, enhancing product performance, and minimizing both energy consumption and environmental pollution. Subsequently, the paper elaborates on the current research and development in digital intelligence-driven green machining technologies, highlighting four critical areas: smart toolholders, minimal quantity lubrication (MQL), machine tool compensation, machine tool energy consumption monitoring, and intelligent carbon emission control. Lastly, the future trends and challenges in these technologies are discussed, with an outlook on the growing importance of green machining in response to technological advancements and evolving market demands.

Keywords

Digital intelligent drives / Green machining / Smart toolholder / Minimal quantity lubrication (MQL) / Machine tool compensation / Machine tool energy monitoring / Intelligent carbon emission control

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Tai-Min Luo,Jin Zhang,Chen-Jie Deng,Dai-Xin Luo,Gui-Bao Tao,Hua-Jun Cao. Green machining technology and application driven by digital intelligence: a review. Advances in Manufacturing 1-60 DOI:10.1007/s40436-025-00567-8

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Funding

National Key R&D Program of China(2022YFB3206700)

Graduate Research and Innovation Foundation of Chongqing, China(CYB23017)

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Shanghai University and Periodicals Agency of Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature

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