Carbon emission in manufacturing processes: modeling and evaluation

Abstract

Sustainable production depends on the optimization of manufacturing processes. The assessment of carbon emissions in manufacturing is crucial for achieving sustainability. However, a comprehensive systematic framework to reflect the carbon emission regularity of manufacturing processes is currently lacking. This study focuses on the modeling and evaluation of carbon emissions by considering machining processes and multiple factors. First, carbon emission models for machining processes, such as turning, milling, and drilling, are systematically summarized by considering power consumption. Second, the influence of system parameters on carbon emissions is analyzed. Results show that cutting depth exerts a substantial effect on carbon emissions, and material removal rate has minimal influence. Last, the emission reduction mechanism and performance of novel sustainable machining processes are examined to contribute to carbon emission reduction. This study helps in systematically understanding carbon emissions in manufacturing processes, providing support for the further development of sustainable manufacturing.

Graphical abstract

Keywords

sustainable production / carbon emission / manufacturing process / power consumption / novel machining processes

References

[1] Ge W W, Li H C, Cao H J, Li C C, Wen X H, Zhang C Y, Mativenga P. Welding parameters and sequences integrated decision-making considering carbon emission and processing time for multi-characteristic laser welding cell. Journal of Manufacturing Systems, 2023, 70: 1–17

[2] Johnson J M F, Franzluebbers A J, Weyers S L, Reicosky D C. Agricultural opportunities to mitigate greenhouse gas emissions. Environmental Pollution, 2007, 150(1): 107–124

[3] Hansen J, Sato M. Greenhouse gas growth rates. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(46): 16109–16114

[4] Sabine C, Ciais P, Jones C, Canadell J G. Ask the experts: the IPCC fifth assessment report. Carbon Management, 2014, 5(1): 17–25

[5] CarbonMonitor. Global Daily Carbon Dioxide Emissions Report 2023. Carbon Emission Accounts and Datasets. 2023

[6] YoonH S, Lee J Y, KimH S, KimM S, KimE S, ShinY J, Chu W S, AhnS H. A comparison of energy consumption in bulk forming, subtractive, and additive processes: review and case study. International Journal of Precision Engineering and Manufacturing-Green Technology, 2014, 1(3): 261–279

[7] Ge W W, Cao H J, Li H C, Zhang C Y, Li C C, Wen X H. Multi-feature driven carbon emission time series coupling model for laser welding system. Journal of Manufacturing Systems, 2022, 65: 767–784

[8] Jin M Z, Tang R Z, Ji Y J, Liu F, Gao L, Huisingh D. Impact of advanced manufacturing on sustainability: An overview of the special volume on advanced manufacturing for sustainability and low fossil carbon emissions. Journal of Cleaner Production, 2017, 161: 69–74

[9] Salahi N, Jafari M A. Energy-performance as a driver for optimal production planning. Applied Energy, 2016, 174: 88–100

[10] Fang K, Uhan N, Zhao F, Sutherland J W. A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction. Journal of Manufacturing Systems, 2011, 30(4): 234–240

[11] He B, Yu Q Y. Product sustainable design for carbon footprint during product life cycle. Journal of Engineering Design, 2021, 32(9): 478–495

[12] Du H B, Li B L, Brown M A, Mao G Z, Rameezdeen R, Chen H. Expanding and shifting trends in carbon market research: a quantitative bibliometric study. Journal of Cleaner Production, 2015, 103: 104–111

[13] Haddad Y, De Bonneval E G, Afy-Shararah M, Carter J, Artingstall J, Salonitis K. Energy flexibility in aerospace manufacturing: The case of low carbon intensity production. Journal of Manufacturing Systems, 2024, 74: 812–825

[14] TuR H. Introduction to united nations framework convention on climate change and its Kyoto Protocol and their negotiation process. Environmental Protection, 2005, 36: 65–71 (in Chinese)

[15] Kong L, Wang L M, Li F Y, Lv X T, Li J F, Ma Y, Chen B, Guo J. Multi-layer integration framework for low carbon design based on design features. Journal of Manufacturing Systems, 2021, 61: 223–238

[16] Jeffry L, Ong M Y, Nomanbhay S, Mofijur M, Mubashir M, Show P L. Greenhouse gases utilization: A review. Fuel, 2021, 301: 121017

[17] CaoH J, Li H C. Dynamic Modelling of Carbon Flows in Manufacturing Systems and Carbon Efficiency Assessment Methods. Beijing: China Machine Press, 2022, 54–77

[18] CaiWLiL JiaSLiuC H XieJHuL K. Task-oriented energy benchmark of machining systems for energy-efficient production. International Journal of Precision Engineering and Manufacturing-Green Technology, 2020, 7(1): 205–218

[19] Ge W W, Cao H J, Li H C, Zhang Q Z, Wen X H, Zhang C Y, Mativenga P. Data-driven carbon emission accounting for manufacturing systems based on meta-carbon-emission block. Journal of Manufacturing Systems, 2024, 74: 141–156

[20] Jia S, Cai W, Liu C H, Zhang Z W, Bai S W, Wang Q Y, Li S S, Hu L K. Energy modeling and visualization analysis method of drilling processes in the manufacturing industry. Energy, 2021, 228: 120567

[21] KhanS AAI Rashid AMuhammadJAliFKoç M. 3D printing technology for rapid response to climate change: challenges and emergency needs. Intelligent and Sustainable Manufacturing, 2024, 1(1): 10004

[22] Bhushan R K. Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites. Journal of Cleaner Production, 2013, 39: 242–254

[23] ZhuS, ZhangH, JiangZ G, Cao H J. Multi-granularity dynamic model establishment and simulation of carbon emissions for machining process based on DEVS. Journal of Mechanical Engineering, 2018, 54(19): 158–169 (in Chinese)

[24] Ball P D, Evans S, Levers A, Ellison D. Zero carbon manufacturing facility—towards integrating material, energy, and waste process flows. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2009, 223(9): 1085–1096

[25] CaoH J, Li H C, DuY B, LiX G. Curent situation and development trend of low-carbon manufacture. Aeronautical Manufacturing Technology, 2012, 9: 26–31 (in Chinese)

[26] LiH C, Cao H J, LiuL W, XingB, PanX, WenX H, Ge W W. Research status and technology path of low-carbon manufacturing under the background of emission peak and carbon neutrality. Journal of Mechanical Engineering, 2023, 59(7): 225–240 (in Chinese)

[27] Tridech S, Cheng K. Low carbon manufacturing: characterization, theoretical models and implementation. International Journal of Manufacturing Research, 2011, 6(2): 110–121

[28] Jiang Z P, Gao D, Lu Y, Kong L H, Shang Z D. Quantitative analysis of carbon emissions in precision turning processes and industrial case study. International Journal of Precision Engineering and Manufacturing-Green Technology, 2021, 8(1): 205–216

[29] Ding H, Guo D Y, Cheng K, Cui Q. An investigation on quantitative analysis of energy consumption and carbon footprint in the grinding process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2014, 228(6): 950–956

[30] YinR X, Cao H J, LiH C, DuY B. Carbon emission quantification method of sand casting process and its application. Computer Integrated Manufacturing Systems, 2012, 18(5): 1071–1076 (in Chinese)

[31] LiuF, XuZ J, DanB. Machining System Energy Characteristics and Their Applications. Beijing: China Machine Press, 1995, 55–79

[32] Li W, Kara S. An empirical model for predicting energy consumption of manufacturing processes: a case of turning process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2011, 225(9): 1636–1646

[33] Hu S H, Liu F, He Y, Hu T. An on-line approach for energy efficiency monitoring of machine tools. Journal of Cleaner Production, 2012, 27: 133–140

[34] Balogun V A, Mativenga P T. Modelling of direct energy requirements in mechanical machining processes. Journal of Cleaner Production, 2013, 41: 179–186

[35] Huang Z, Cao H J, Zeng D, Ge W W, Duan C M. A carbon efficiency approach for laser welding environmental performance assessment and the process parameters decision-making. The International Journal of Advanced Manufacturing Technology, 2021, 114(7–8): 2433–2446

[36] Lin W W, Yu D Y, Zhang C Y, Zhang S Q, Tian Y H, Liu S Q, Luo M. Multi-objective optimization of machining parameters in multi-pass turning operations for low-carbon manufacturing. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2017, 231(13): 2372–2383

[37] JiangX Y, Liu A, YangG Z, LiuW J, BianH Y, SuoY Q. Low-carbon modeling and process parameter optimization in laser additive manufacturing process. Journal of Mechanical Engineering, 2022, 58(5): 223–238 (in Chinese)

[38] Zhang C X, Liu C H, Zhao X. Optimization control method for carbon footprint of machining process. The International Journal of Advanced Manufacturing Technology, 2017, 92(5–8): 1601–1607

[39] Yin R X, Cao H J, Li H C, Sutherland J W. A process planning method for reduced carbon emissions. International Journal of Computer Integrated Manufacturing, 2014, 27(12): 1175–1186

[40] Cao H J, Li H C, Cheng H Q, Luo Y, Yin R X, Chen Y P. A carbon efficiency approach for life-cycle carbon emission characteristics of machine tools. Journal of Cleaner Production, 2012, 37: 19–28

[41] Sihag N, Sangwan K S. An improved micro analysis-based energy consumption and carbon emissions modeling approach for a milling center. The International Journal of Advanced Manufacturing Technology, 2019, 104(1–4): 705–721

[42] Cao H J, Li H C. Simulation-based approach to modeling the carbon emissions dynamic characteristics of manufacturing system considering disturbances. Journal of Cleaner Production, 2014, 64: 572–580

[43] SongS L, Cao H J, LiH C. Evaluation method and application for carbon emissions of machine tools based on LCA. In: Proceedings of International Conference on Advanced Technology of Design and Manufacture (ATDM). Beijing: Institution of Engineering and Technology, 2010, 74–78

[44] LiT, KongL L, ZhangH C, Iqbal A. Recent research and development of typical cutting machine tool’s energy consumption model. Journal of Mechanical Engineering, 2014, 50(7): 102–111 (in Chinese)

[45] Zhou G H, Zhang C, Lu F Y, Zhang J J. Integrated optimization of cutting parameters and tool path for cavity milling considering carbon emissions. Journal of Cleaner Production, 2020, 250: 119454

[46] WangQ L, Liu F. Mathematical model of multi-source energy flows for CNC machine tools. Journal of Mechanical Engineering, 2013, 49(7): 5–12 (in Chinese)

[47] Mori M, Fujishima M, Inamasu Y, Oda Y. A study on energy efficiency improvement for machine tools. CIRP Annals, 2011, 60(1): 145–148

[48] DahmusJ B, Gutowski T G. An environmental analysis of machining. In: Proceedings of the ASME 2004 International Mechanical Engineering Congress and Exposition. Manufacturing Engineering and Materials Handling Engineering. Anaheim: The American Society of Mechanical Engineers, 2004, 643–652

[49] Khan A M, Jamil M, Mia M, He N, Zhao W, Gong L. Sustainability-based performance evaluation of hybrid nanofluid assisted machining. Journal of Cleaner Production, 2020, 257: 120541

[50] Anderberg S E, Kara S, Beno T. Impact of energy efficiency on computer numerically controlled machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2010, 224(4): 531–541

[51] Khan A M, Gupta M K, Hegab H, Jamil M, Mia M, He N, Song Q H, Liu Z Q, Pruncu C I. Energy-based cost integrated modelling and sustainability assessment of Al-GnP hybrid nanofluid assisted turning of AISI52100 steel. Journal of Cleaner Production, 2020, 257: 120502

[52] Hoghoughi M H, Farahnakian M, Elhami S. Environmental, economical, and machinability based sustainability assessment in hybrid machining process employing tool textures and solid lubricant. Sustainable Materials and Technologies, 2022, 34: e00511

[53] Liu Z J, Sun D P, Lin C X, Zhao X Q, Yang Y. Multi-objective optimization of the operating conditions in a cutting process based on low carbon emission costs. Journal of Cleaner Production, 2016, 124: 266–275

[54] Zhang H, Deng Z H, Fu Y H, Lv L S, Yan C. A process parameters optimization method of multi-pass dry milling for high efficiency, low energy and low carbon emissions. Journal of Cleaner Production, 2017, 148: 174–184

[55] Deng Z H, Lv L S, Li S C, Wan L L, Liu W, Yan C, Zhang H. Study on the model of high efficiency and low carbon for grinding parameters optimization and its application. Journal of Cleaner Production, 2016, 137: 1672–1681

[56] Wang Q, Zhang D H, Chen B, Zhang Y, Wu B H. Energy consumption model for drilling processes based on cutting force. Applied Sciences, 2019, 9(22): 4801

[57] Li L, Yan J H, Xing Z W. Energy requirements evaluation of milling machines based on thermal equilibrium and empirical modelling. Journal of Cleaner Production, 2013, 52: 113–121

[58] Madanchi N, Thiede S, Gutowski T, Herrmann C. Modeling the impact of cutting fluid strategies on environmentally conscious machining systems. Procedia CIRP, 2019, 80: 150–155

[59] LiC B, Cui L G, LiuF, LiL. Multi-objective NC machining parameters optimization model for high efficiency and low carbon. Journal of Mechanical Engineering, 2013, 49(9): 87–96 (in Chinese)

[60] Zhang Y B, Li L Y, Cui X, An Q L, Xu P M, Wang W, Jia D Z, Liu M Z, Dambatta Y S, Li C H. Lubricant activity enhanced technologies for sustainable machining: Mechanisms and processability. Chinese Journal of Aeronautics, 2025, 38(6): 103203

[61] Guo D Y, Cheng K, Ding H, Yan J H, Ma Y H. An investigation on quantitative analysis of carbon footprint in centreless grinding process and its key factors. China Mechanical Engineering, 2014, 25(11): 1478–1485

[62] Wang Y L, Zhang Y B, Cui X, Liang X L, Li R Z, Wang R X, Sharma S, Liu M Z, Gao T, Zhou Z M, Wang X M, Dambatta Y S, Li C H. High-speed grinding: from mechanism to machine tool. Advances in Manufacturing, 2025, 13(1): 105–154

[63] Yi Q, Li C B, Tang Y, Chen X Z. Multi-objective parameter optimization of CNC machining for low carbon manufacturing. Journal of Cleaner Production, 2015, 95: 256–264

[64] Cao W D, Ni J J, Jiang B Y, Ye C Q. A three-stage parameter prediction approach for low-carbon gear hobbing. Journal of Cleaner Production, 2021, 289: 125777

[65] ZhengC W, Yan C P, CaoW D. Gear hobbing process carbon emission quantitative calculation model and its optimization. Modern Manufacturing Engineering, 2018, 457(10): 23–30 (in Chinese)

[66] Khanna N, Kshitij G, Solanki M, Bhatt T, Patel O, Uysal A, Sarıkaya M. In pursuit of sustainability in machining thin walled α-titanium tubes: an industry supported study. Sustainable Materials and Technologies, 2023, 36: e00647

[67] Munoz A A, Sheng P. An analytical approach for determining the environmental impact of machining processes. Journal of Materials Processing Technology, 1995, 53(3–4): 736–758

[68] Cui X, Li C H, Yang M, Liu M Z, Gao T, Wang X M, Said Z, Sharma S, Zhang Y B. Enhanced grindability and mechanism in the magnetic traction nanolubricant grinding of Ti-6Al-4V. Tribology International, 2023, 186: 108603

[69] Zhu D H, Zhang X M, Ding H. Tool wear characteristics in machining of nickel-based superalloys. International Journal of Machine Tools and Manufacture, 2013, 64: 60–77

[70] Chen M K, Zhang Y B, Liu B, Zhou Z M, Zhang N Q, Wang H H, Wang L Q. Design of intelligent and sustainable manufacturing production line for automobile wheel hub. Intelligent and Sustainable Manufacturing, 2024, 1(1): 10003

[71] Jiang Z G, Zhou F, Zhang H, Wang Y, Sutherland J W. Optimization of machining parameters considering minimum cutting fluid consumption. Journal of Cleaner Production, 2015, 108: 183–191

[72] Tian C L, Zhou G H, Zhang J J, Zhang C. Optimization of cutting parameters considering tool wear conditions in low-carbon manufacturing environment. Journal of Cleaner Production, 2019, 226: 706–719

[73] YinR X, Cao H J, LiH C. Carbon emission characteristics of mechanical manufacturing process based on functional description and its application. Computer Integrated Manufacturing Systems, 2014, 20(9): 2127–2133 (in Chinese)

[74] Dang J Q, Wang H H, Wang C G, An Q L, Li Y G, Wang H W, Chen M. Microstructure evolution and surface strengthening behavior of 300M ultrahigh strength steel under engineered surface treatments. Materials Characterization, 2024, 215: 114127

[75] Wei S S, Zhang J L, Zhang L, Zhang Y J, Song B, Wang X B, Fan J X, Liu Q, Shi Y S. Laser powder bed fusion additive manufacturing of NiTi shape memory alloys: a review. International Journal of Extreme Manufacturing, 2023, 5(3): 032001

[76] WuJ Z, Sun J H, ZhangC Y, CaoH J, GeW W. Carbon emission modeling and multi-response evaluation of fiber laser welding. Journal of Mechanical Engineering, 2023, 59(7): 186–199 (in Chinese)

[77] Han W, Kong L B, Xu M. Advances in selective laser sintering of polymers. International Journal of Extreme Manufacturing, 2022, 4(4): 042002

[78] LuoY, CaoH J, LiH C, Cheng H Q. Carbon emission model and parameter optimization of CO₂ shielded welding based on GRNN. China Mechanical Engineering, 2013, 24(17): 2398–2403 (in Chinese)

[79] Zheng J, Tang R Z. Carbon efficiency model and evaluation method for sand casting. Journal of Zhejiang University (Engineering Science), 2015, 49(1): 102–109

[80] YinR X. Carbon emission calculation of machining manufacturing process for normal machinery parts. Mechanical Engineer, 2018, 4: 8–11 (in Chinese)

[81] Liu H L, Li B T, Tang W H. Manufacturing oriented topology optimization of 3D structures for carbon emission reduction in casting process. Journal of Cleaner Production, 2019, 225: 755–770

[82] PengT H, Cai X, QuZ H, TangA H, ShenR, WangQ M, Yu W H. Research on calculation model of power supply carbon emission factor in regional power grid considering hierarchical and regional decoupling of large-scale power grid. Proceedings of the CSEE, 2024, 44(3): 894–905 (in Chinese)

[83] Zhang Q Y, Qiao K, Hu C A, Su P, Cheng O Y, Yan N, Yan L H. Study on life-cycle carbon emission factors of electricity in China. International Journal of Low-Carbon Technologies, 2024, 19: 2287–2298

[84] Jeswiet J, Kara S. Carbon emissions and CES™ in manufacturing. CIRP Annals, 2008, 57(1): 17–20

[85] Yu L, Wang Y, Li D Z. Calculating and analyzing carbon emission factors of prefabricated components. Sustainability, 2023, 15(11): 8706

[86] Panagiotopoulou V C, Stavropoulos P, Chryssolouris G. A critical review on the environmental impact of manufacturing: a holistic perspective. The International Journal of Advanced Manufacturing Technology, 2022, 118(1–2): 603–625

[87] Hu X D, Zhang X M, Dong L, Li H J, He Z, Chen H H. Carbon emission factors identification and measurement model construction for railway construction projects. International Journal of Environmental Research and Public Health, 2022, 19(18): 11379

[88] Mohebbi G, Bahadori-Jahromi A, Ferri M, Mylona A. The role of embodied carbon databases in the accuracy of life cycle assessment (LCA) calculations for the embodied carbon of buildings. Sustainability, 2021, 13(14): 7988

[89] Dang J Q, Wang C G, Wang H H, An Q L, Wei J, Gao B, Liu Z M, Chen M. Deformation behavior and microstructure evolution of 300M ultrahigh strength steel subjected to high strain rate: an analytical approach. Journal of Materials Research and Technology, 2023, 25: 812–831

[90] ZhangH P, Gao D. Analysis of influence factors of carbon dioxide emission during milling processes. Machine Building and Automation, 2013, 444: 29–31 (in Chinese)

[91] Li C B, Tang Y, Cui L G, Li P Y. A quantitative approach to analyze carbon emissions of CNC-based machining systems. Journal of Intelligent Manufacturing, 2015, 26(5): 911–922

[92] Zhang Y, Liu Q, Zhou Y D, Ying B S. Integrated optimization of cutting parameters and scheduling for reducing carbon emissions. Journal of Cleaner Production, 2017, 149: 886–895

[93] Zhou G H, Zhou C, Lu Q, Tian C L, Xiao Z D. Feature-based carbon emission quantitation strategy for the part machining process. International Journal of Computer Integrated Manufacturing, 2018, 31(4–5): 406–425

[94] Jiang Z P, Gao D, Lu Y, Liu X L. Optimization of cutting parameters for trade-off among carbon emissions, surface roughness, and processing time. Chinese Journal of Mechanical Engineering, 2019, 32(1): 94

[95] Cakir A K. A new approach to minimize carbon emission rate in turning processes. International Journal of Low Carbon Technologies, 2021, 16(4): 1444–1452

[96] Günay M, Aslan E, Korkut İ, Şeker U. Investigation of the effect of rake angle on main cutting force. International Journal of Machine Tools and Manufacture, 2004, 44(9): 953–959

[97] Tian C L, Zhou G H, Lu Q, Zhang J J, Xiao Z D, Wang R. An integrated decision-making approach on cutting tools and cutting parameters for machining features considering carbon emissions. International Journal of Computer Integrated Manufacturing, 2019, 32(7): 629–641

[98] Hu L K, Tang R Z, He K Y, Jia S. Estimating machining-related energy consumption of parts at the design phase based on feature technology. International Journal of Production Research, 2015, 53(23): 7016–7033

[99] Hu L K, Liu Y, Peng C, Tang W C J, Tang R Z, Tiwari A. Minimising the energy consumption of tool change and tool path of machining by sequencing the features. Energy, 2018, 147: 390–402

[100] Feng C H, Chen X, Zhang J Y, Huang Y G, Qu Z B. Minimizing the energy consumption of hole machining integrating the optimization of tool path and cutting parameters on CNC machines. The International Journal of Advanced Manufacturing Technology, 2022, 121(1–2): 215–228

[101] Li L, Deng X G, Zhao J H, Zhao F, Sutherland J W. Multi-objective optimization of tool path considering efficiency, energy-saving and carbon-emission for free-form surface milling. Journal of Cleaner Production, 2018, 172: 3311–3322

[102] WangJ S, Duan G H, LiF Y, YangX D, ZhangH C. Current situation and future developing trends of green manufacturing technology based on products’ life cycle. Computer Integrated Manufacturing Systems, 1999, 5(4): 2–9 (in Chinese)

[103] Zhou G H, Lu Q, Xiao Z D, Zhou C, Tian C L. Cutting parameter optimization for machining operations considering carbon emissions. Journal of Cleaner Production, 2019, 208: 937–950

[104] He B, Hua Y C. Feature-based integrated product model for low-carbon conceptual design. Journal of Engineering Design, 2017, 28(6): 408–432

[105] Tian Y Q, Yin R X. The grinding parameter optimization under the carbon benefit objective. Journal of Physics: Conference Series, 2023, 2561(1): 012016

[106] Ic Y T, Saraloğlu Güler E, Cabbaroğlu C, Dilan Yüksel E, Maide Sağlam H. Optimisation of cutting parameters for minimizing carbon emission and maximising cutting quality in turning process. International Journal of Production Research, 2018, 56(11): 4035–4055

[107] LiY, LiuQ. Service-oriented research on multi-pass milling parameters optimization for green and high efficiency. Journal of Mechanical Engineering, 2015, 51(11): 89–98 (in Chinese)

[108] Jiang Z P, Gao D, Lu Y, Shang Z D, Kong L H. Optimisation of cutting parameters for minimising carbon emissions and cost in the turning process. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2022, 236(4): 1973–1985

[109] Nguyen T T, Duong Q D, Mia M. Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2021, 235(13): 2155–2173

[110] ZhangH P. Research on prediction techniques of carbon emission during NC milling processes. Thesis for the Master’s Degree. Harbin: Harbin Institute of Technology, 2012, 23–56 (in Chinese)

[111] Rajemi M F, Mativenga P T, Aramcharoen A. Sustainable machining: selection of optimum turning conditions based on minimum energy considerations. Journal of Cleaner Production, 2010, 18(10–11): 1059–1065

[112] Zhong Q Q, Tang R Z, Peng T. Decision rules for energy consumption minimization during material removal process in turning. Journal of Cleaner Production, 2017, 140: 1819–1827

[113] Huisingh D, Zhang Z H, Moore J C, Qiao Q, Li Q. Recent advances in carbon emissions reduction: policies, technologies, monitoring, assessment and modeling. Journal of Cleaner Production, 2015, 103: 1–12

[114] Zhou L R, Li J F, Li F Y, Meng Q, Li J, Xu X S. Energy consumption model and energy efficiency of machine tools: a comprehensive literature review. Journal of Cleaner Production, 2016, 112: 3721–3734

[115] Gutowski T, Murphy C, Allen D, Bauer D, Bras B, Piwonka T, Sheng P, Sutherland J, Thurston D, Wolff E. Environmentally benign manufacturing: observations from Japan, Europe and the United States. Journal of Cleaner Production, 2005, 13(1): 1–17

[116] ShiJ L, Liu F, XuD J, XieD. Power balance equation about the numerical control machine tool’s main driver system driven by variable voltage variable frequency. Journal of Mechanical Engineering, 2010, 46(3): 118–124 (in Chinese)

[117] HuS H, Liu F, HeY, HuT. No-load energy parameter characteristics of computerized numerical control machine tool main transmission system. Computer Integrated Manufacturing Systems, 2012, 18(2): 326–331 (in Chinese)

[118] Weinert K, Inasaki I, Sutherland J W, Wakabayashi T. Dry machining and minimum quantity lubrication. CIRP Annals, 2004, 53(2): 511–537

[119] Pusavec F, Krajnik P, Kopac J. Transitioning to sustainable production–Part I: application on machining technologies. Journal of Cleaner Production, 2010, 18(2): 174–184

[120] Pimenov D Y, Mia M, Gupta M K, Machado A R, Tomaz Í V, Sarikaya M, Wojciechowski S, Mikolajczyk T, Kapłonek W. Improvement of machinability of Ti and its alloys using cooling-lubrication techniques: A review and future prospect. Journal of Materials Research and Technology, 2021, 11: 719–753

[121] Dudzinski D, Devillez A, Moufki A, Larrouquère D, Zerrouki V, Vigneau J. A review of developments towards dry and high speed machining of Inconel 718 alloy. International Journal of Machine Tools and Manufacture, 2004, 44(4): 439–456

[122] Diniz A E, de Oliveira A J. Optimizing the use of dry cutting in rough turning steel operations. International Journal of Machine Tools and Manufacture, 2004, 44(10): 1061–1067

[123] Fratila D, Caizar C. Application of Taguchi method to selection of optimal lubrication and cutting conditions in face milling of AlMg3. Journal of Cleaner Production, 2011, 19(6–7): 640–645

[124] DebnathSReddy M MPramanikA. Dry and near-dry machining techniques for green manufacturing. In: Gupta K (ed). Innovations in Manufacturing for Sustainability. Cham: Springer, 2019, 1–27

[125] Davoodi B, Hosseini Tazehkandi A. Experimental investigation and optimization of cutting parameters in dry and wet machining of aluminum alloy 5083 in order to remove cutting fluid. Journal of Cleaner Production, 2014, 68: 234–242

[126] Kara S, Li W. Unit process energy consumption models for material removal processes. CIRP Annals, 2011, 60(1): 37–40

[127] LiX G, Yang Y, LiC B, ChenP, CaoH J. Analysis of carbon emission in gear dry machining process for green manufacturing. China Mechanical Engineering 2014, 25(16): 2184-2190 (in Chinese)

[128] Shokrani A, Dhokia V, Muñoz-Escalona P, Newman S T. State-of-the-art cryogenic machining and processing. International Journal of Computer Integrated Manufacturing, 2013, 26(7): 616–648

[129] Jouhara H, Chauhan A, Guichet V, Delpech B, Abdelkareem M A, Olabi A G, Trembley J. Low-temperature heat transfer mediums for cryogenic applications. Journal of the Taiwan Institute of Chemical Engineers, 2023, 148: 104709

[130] Debnath S, Reddy M M, Yi Q S. Environmental friendly cutting fluids and cooling techniques in machining: a review. Journal of Cleaner Production, 2014, 83: 33–47

[131] Wang D F, Dang J Q, Li Y G, Liu Z M, Wang H W, Chen M. Study on the surface integrity distribution of 300M ultrahigh strength steel subjected to different surface modification treatments. Surface and Coatings Technology, 2022, 451: 129033

[132] Dubey V, Kumar Sharma A, Kumar Singh R. Study of various cooling methodology used in machining processes. Materials Today: Proceedings, 2020, 21: 1572–1576

[133] Danish M, Ginta T L, Habib K, Carou D, Rani A M A, Saha B B. Thermal analysis during turning of AZ31 magnesium alloy under dry and cryogenic conditions. International Journal of Advanced Manufacturing Technology, 2017, 91(5–8): 2855–2868

[134] da Silva F J, Franco S D, Machado Á R, Ezugwu E O, Souza A M. Performance of cryogenically treated HSS tools. Wear, 2006, 261(5–6): 674–685

[135] ZhaoX G, Hao X Q, ZhangZ H, AnQ L, SunH L, LiL, ChenM, HeN. Low temperature CO₂ assisted PCD tool hard turning bearing ring device and experimental research. Surface Technology, 2023, 52(2): 307–316 (in Chinese)

[136] Agrawal C, Wadhwa J, Pitroda A, Pruncu C I, Sarikaya M, Khanna N. Comprehensive analysis of tool wear, tool life, surface roughness, costing and carbon emissions in turning Ti–6Al–4V titanium alloy: Cryogenic versus wet machining. Tribology International, 2021, 153: 106597

[137] Yildiz Y, Nalbant M. A review of cryogenic cooling in machining processes. International Journal of Machine Tools and Manufacture, 2008, 48(9): 947–964

[138] Jamil M, Zhao W, He N, Gupta M K, Sarikaya M, Khan A M, R S M, Siengchin S, Pimenov D Y. R SM, Siengchin S, Pimenov DY. Sustainable milling of Ti–6Al–4V: A trade-off between energy efficiency, carbon emissions and machining characteristics under MQL and cryogenic environment. Journal of Cleaner Production, 2021, 281: 125374

[139] Ross N S, Rai R, Ananth M B J, Srinivasan D, Ganesh M, Gupta M K, Korkmaz M E, Królczyk G M. Carbon emissions and overall sustainability assessment in eco-friendly machining of Monel-400 alloy. Sustainable Materials and Technologies, 2023, 37: e00675

[140] Iqbal A, Suhaimi H, Zhao W, Jamil M, Nauman M M, He N, Zaini J. Sustainable milling of Ti-6Al-4V: Investigating the effects of milling orientation, cutter’s helix angle, and type of cryogenic coolant. Metals, 2020, 10(2): 258

[141] Zhang S, Li J F, Wang Y W. Tool life and cutting forces in end milling Inconel 718 under dry and minimum quantity cooling lubrication cutting conditions. Journal of Cleaner Production, 2012, 32: 81–87

[142] GuG QWang D ZWuS JZhouSZhangB X. Research status and prospect of ultrasonic vibration and minimum quantity lubrication processing of nickel-based alloys. Intelligent and Sustainable Manufacturing, 2024, 1(1): 10006

[143] Cui X, Li C H, Ding W F, Chen Y, Mao C, Xu X F, Liu B, Wang D Z, Li H N, Zhang Y B, Said Z, Debnath S, Jamil M, Ali H M, Sharma S. Minimum quantity lubrication machining of aeronautical materials using carbon group nanolubricant: From mechanisms to application. Chinese Journal of Aeronautics, 2022, 35(11): 85–112

[144] Kumar A, Sharma A K, Katiyar J K. State-of-the-art in sustainable machining of different materials using nano minimum quality lubrication (NMQL). Lubricants, 2023, 11(2): 64

[145] UysalACaudill J RSchoopJJawahirI S. Minimising carbon emissions and machining costs with improved human health in sustainable machining of austenitic stainless steel through multi-objective optimisation. International Journal of Sustainable Manufacturing, 2020, 4(2–4): 281–299

[146] ZhangF J, Li Z S, CuiW W. Development and application of OoW equipment for gear hobbing. Journal of Mechanical Transmission, 2023, 47(6): 139–147 (in Chinese)

[147] Xu W H, Li C H, Cui X, Zhang Y B, Yang M, Gao T, Liu M Z, Wang X M, Zhou Z M, Sharma S, Dambatta Y S. Atomization mechanism and machinability evaluation with electrically charged nanolubricant grinding of GH4169. Journal of Manufacturing Processes, 2023, 106: 480–493

[148] Shah P, Gadkari A, Sharma A, Shokrani A, Khanna N. Comparison of machining performance under MQL and ultra-high voltage EMQL conditions based on tribological properties. Tribology International, 2021, 153: 106595

[149] HuangS QLv TWangM HXuX F. Effects of machining and oil mist parameters on electrostatic minimum quantity lubrication–EMQL turning process. International Journal of Precision Engineering and Manufacturing-Green Technology, 2018, 5(2): 317–326

[150] Huang S Q, Wang Z, Yao W Q, Xu X F. Tribological evaluation of contact-charged electrostatic spray lubrication as a new near-dry machining technique. Tribology International, 2015, 91: 74–84

[151] KashyapNRahman Rashid R AKhannaN. Carbon emissions, techno-economic and machinability assessments to achieve sustainability in drilling Ti6Al4V ELI for medical industry applications. Sustainable Materials and Technologies, 2022, 33: e00458

[152] SalviHVesuwala HRavalPBadhekaVKhannaN. Sustainability analysis of additive + subtractive manufacturing processes for Inconel 625. Sustainable Materials and Technologies, 2023, 35: e00580

[153] Khanna N, Shah P, Wadhwa J, Pitroda A, Schoop J, Pusavec F. Energy consumption and lifecycle assessment comparison of cutting fluids for drilling titanium alloy. Procedia CIRP, 2021, 98: 175–180

[154] Liu G T, Li C H, Zhang Y B, Yang M, Jia D Z, Zhang X P, Guo S M, Li R Z, Zhai H. Process parameter optimization and experimental evaluation for nanofluid MQL in grinding Ti-6Al-4V based on grey relational analysis. Materials and Manufacturing Processes, 2018, 33(9): 950–963

[155] Sun L Y, Zhang Y B, Cui X, An Q L, Chen Y, Jia D Z, Gong P, Liu M Z, Dambatta Y S, Li C H. Magnetic lubricants: preparation, physical mechanism, and application. Friction, 2025, early access,:

[156] Song Y X, Li C H, Zhou Z M, Liu B, Sharma S, Dambatta Y S, Zhang Y B, Yang M, Gao T, Liu M Z, Cui X, Wang X M, Xu W H, Li R Z, Wang D Z. Nanobiolubricant grinding: a comprehensive review. Advances in Manufacturing, 2025, 13: 1–42

[157] SongY X, Xu Z L, LiC H, ZhouZ M, LiuB, ZhangY B, Dambatta Y S, WangD Z. Research progress on the grinding performance of nanobiolubricant minimum quantity lubrication. Surface Technology, 2023, 52(12): 1–19 (in Chinese)

[158] Khan A M, Anwar S, Jamil M, Nasr M M, Gupta M K, Saleh M, Ahmad S, Mia M. Energy, environmental, economic, and technological analysis of Al-GnP nanofluid- and cryogenic LN₂-assisted sustainable machining of Ti-6Al-4V alloy. Metals, 2021, 11(1): 88

[159] Gupta M K, Song Q H, Liu Z Q, Sarikaya M, Jamil M, Mia M, Singla A K, Khan A M, Khanna N, Pimenov D Y. Environment and economic burden of sustainable cooling/lubrication methods in machining of Inconel-800. Journal of Cleaner Production, 2021, 287: 125074

[160] Cui X, Li C H, Zhang Y B, Said Z, Debnath S, Sharma S, Ali H M, Yang M, Gao T, Li R Z. Grindability of titanium alloy using cryogenic nanolubricant minimum quantity lubrication. Journal of Manufacturing Processes, 2022, 80: 273–286

[161] Çetindağ H A, Çiçek A, Uçak N. The effects of CryoMQL conditions on tool wear and surface integrity in hard turning of AISI 52100 bearing steel. Journal of Manufacturing Processes, 2020, 56: 463–473

[162] Yıldırım Ç V, Kıvak T, Sarıkaya M, Şirin Ş. Evaluation of tool wear, surface roughness/topography and chip morphology when machining of Ni-based alloy 625 under MQL, cryogenic cooling and CryoMQL. Journal of Materials Research and Technology, 2020, 9(2): 2079–2092

[163] Dzido A, Krawczyk P, Badyda K, Chondrokostas P. Operational parameters impact on the performance of dry-ice blasting nozzle. Energy, 2021, 214: 118847

[164] JamilMHe NWeiZGuptaM KKhanA M. A novel quantifiable approach of estimating energy consumption, carbon emissions and cost factors in manufacturing of bearing steel based on triple bottom-line approach. Sustainable Materials and Technologies, 2023, 36: e00593

[165] Khanna N, Agrawal C, Gupta M K, Song Q H, Singla A K. Sustainability and machinability improvement of Nimonic-90 using indigenously developed green hybrid machining technology. Journal of Cleaner Production, 2020, 263: 121402

[166] Xu M R, Chen S, Kurniawan R, Li C P, Wei R, Teng H W, Kumaran T, Han P W, Ko T J. Machinability study of cryogenic-ultrasonic vibration-assisted milling Inconel 718 alloy. The International Journal of Advanced Manufacturing Technology, 2023, 127(9–10): 4887–4901

[167] Dang J Q, An Q L, Lian G H, Zuo Z Y, Li Y G, Wang H W, Chen M. Surface modification and its effect on the tensile and fatigue properties of 300M steel subjected to ultrasonic surface rolling process. Surface and Coatings Technology, 2021, 422: 127566

[168] Zhao B, You H X, Miao Q, Ding W F, Qian N, Xu J H. Surface integrity characterization of third-generation nickel-based single crystal blade tenons after ultrasonic vibration-assisted grinding. Chinese Journal of Aeronautics, 2025, 38(1): 103138

[169] Cao Y, Ding W F, Zhao B, Wen X B, Li S P, Wang J Z. Effect of intermittent cutting behavior on the ultrasonic vibration-assisted grinding performance of Inconel718 nickel-based superalloy. Precision Engineering, 2022, 78: 248–260

[170] Cao Y, Zhu Y J, Li H N, Wang C X, Su H H, Yin Z, Ding W F. Development and performance of a novel ultrasonic vibration plate sonotrode for grinding. Journal of Manufacturing Processes, 2020, 57: 174–186

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