Equipment–process–strategy integration for sustainable machining: a review

Abstract

Although the manufacturing industry has improved the quality of processing, optimization and upgrading must be performed to meet the requirements of global sustainable development. Sustainable production is considered to be a favorable strategy for achieving machining upgrades characterized by high quality, high efficiency, energy savings, and emission reduction. Sustainable production has aroused widespread interest, but only a few scholars have studied the sustainability of machining from multiple dimensions. The sustainability of machining must be investigated multidimensionally and accurately. Thus, this study explores the sustainability of machining from the aspects of equipment, process, and strategy. In particular, the equipment, process, and strategy of sustainable machining are systematically analyzed and integrated into a research framework. Then, this study analyzes sustainable machining-oriented machining equipment from the aspects of machine tools, cutting tools, and materials such as cutting fluid. Machining processes are explored as important links of sustainable machining from the aspects of dry cutting, microlubrication, microcutting, low-temperature cutting, and multidirectional cutting. The strategies for sustainable machining are also analyzed from the aspects of energy-saving control, machining simulation, and process optimization of machine tools. Finally, opportunities and challenges, including policies and regulations toward sustainable machining, are discussed. This study is expected to offer prospects for sustainable machining development and strategies for implementing sustainable machining.

Graphical abstract

Keywords

sustainable machining / equipment / process / strategy / manufacturing

References

[1] Niu H Y , Zhang Z S , Luo M T . Evaluation and prediction of low-carbon economic efficiency in China, Japan and South Korea: based on DEA and machine learning. International Journal of Environmental Research and Public Health, 2022, 19(19): 12709

[2] Gilli M , Marin G , Mazzanti M , Nicolli F . Sustainable development and industrial development: manufacturing environmental performance, technology and consumption/production perspectives. Journal of Environmental Economics and Policy, 2017, 6(2): 183–203

[3] Liu C Y , Xin L , Li J Y . Environmental regulation and manufacturing carbon emissions in China: a new perspective on local government competition. Environmental Science and Pollution Research, 2022, 29(24): 36351–36375

[4] Lin B Q , Chen G Y . Energy efficiency and conservation in China’s manufacturing industry. Journal of Cleaner Production, 2018, 174: 492–501

[5] Sarikaya M , Gupta M K , Tomaz I , Danish M , Mia M , Rubaiee S , Jamil M , Pimenov D Y , Khanna N . Cooling techniques to improve the machinability and sustainability of light-weight alloys: a state-of-the-art review. Journal of Manufacturing Processes, 2021, 62: 179–201

[6] Sarıkaya M , Gupta M K , Tomaz I , Krolczyk G M , Khanna N , Karabulut Ş , Prakash C , Buddhi D . Resource savings by sustainability assessment and energy modelling methods in mechanical machining process: a critical review. Journal of Cleaner Production, 2022, 370: 133403

[7] Yang L , Liu Q M , Xia T B , Ye C M , Li J X . Preventive maintenance strategy optimization in manufacturing system considering energy efficiency and quality cost. Energies, 2022, 15(21): 8237

[8] Beraud J J D , Zhao X C , Wu J Y . Revitalization of Chinese’s manufacturing industry under the carbon neutral goal. Environmental Science and Pollution Research, 2022, 29(44): 66462–66478

[9] Tian G D , Yuan G , Aleksandrov A , Zhang T Z , Li Z W , Fathollahi-Fard A M , Ivanov M . Recycling of spent lithium-ion batteries: a comprehensive review for identification of main challenges and future research trends. Sustainable Energy Technologies and Assessments, 2022, 53: 102447

[10] Cheng M L . Energy conservation potential analysis of Chinese manufacturing industry: the case of Jiangsu province. Environmental Science and Pollution Research, 2020, 27(14): 16694–16706

[11] Cheng G, Zhao C J, Iqbal N, Gülmez Ö, Işik H, Kirikkaleli D. Does energy productivity and public-private investment in energy achieve carbon neutrality target of China? Journal of Environmental Management, 2021, 298: 113464

[12] Shankar S , Manikandan M , Raja G , Pramanik A . Experimental investigations of vibration and acoustics signals in milling process using kapok oil as cutting fluid. Mechanics & Industry, 2020, 21(5): 521

[13] Pal A, Chatha S S, Singh K. Performance evaluation of minimum quantity lubrication technique in grinding of AISI 202 stainless steel using nano-MoS₂ with vegetable-based cutting fluid. The International Journal of Advanced Manufacturing Technology, 2020, 110(1–2): 125–137

[14] Lin S F , Sun J , Marinova D , Zhao D T . Evaluation of the green technology innovation efficiency of China’s manufacturing industries: DEA window analysis with ideal window width. Technology Analysis and Strategic Management, 2018, 30(10): 1166–1181

[15] Labucay I . Is there a smart sustainability transition in manufacturing? Tracking externalities in machine tools over three decades. Sustainability, 2022, 14(2): 838

[16] Pimenov D Y , Mia M , Gupta M K , Machado Á R , Pintaude G , Unune D R , Khanna N , Khan A M , Tomaz Í , Wojciechowski S , Kuntoğlu M . Resource saving by optimization and machining environments for sustainable manufacturing: a review and future prospects. Renewable & Sustainable Energy Reviews, 2022, 166: 112660

[17] Avram O I, Xirouchakis P. Evaluating the use phase energy requirements of a machine tool system. Journal of Cleaner Production, 2011, 19(6–7): 699–711

[18] Götze U , Koriath H J , Kolesnikov A , Lindner R , Paetzold J . Integrated methodology for the evaluation of the energy-and cost-effectiveness of machine tools. CIRP Journal of Manufacturing Science and Technology, 2012, 5(3): 151–163

[19] Denkena B , Abele E , Brecher C , Dittrich M A , Kara S , Mori M . Energy efficient machine tools. CIRP Annals, 2020, 69(2): 646–667

[20] Draganescu F , Gheorghe M , Doicin C V . Models of machine tool efficiency and specific consumed energy. Journal of Materials Processing Technology, 2003, 141(1): 9–15

[21] Shang Z D , Gao D , Jiang Z P , Lu Y . Towards less energy intensive heavy-duty machine tools: power consumption characteristics and energy-saving strategies. Energy, 2019, 178: 263–276

[22] Plocher J , Panesar A . Review on design and structural optimisation in additive manufacturing: towards next-generation lightweight structures. Materials & Design, 2019, 183: 108164

[23] Lv J X , Tang R Z , Tang W C J , Liu Y , Zhang Y F , Jia S . An investigation into reducing the spindle acceleration energy consumption of machine tools. Journal of Cleaner Production, 2017, 143: 794–803

[24] Huang H H , Zou X , Li L , Li X Y , Liu Z F . Energy-saving design method for hydraulic press drive system with multi motor-pumps. International Journal of Precision Engineering and Manufacturing-Green Technology, 2019, 6(2): 223–234

[25] Shokrani A , Dhokia V , Newman S T . Environmentally conscious machining of difficult-to-machine materials with regard to cutting fluids. International Journal of Machine Tools and Manufacture, 2012, 57: 83–101

[26] Xiong W. Study on optimization design of lathe spindle based on improved BP neural network. Thesis for the Master’s Degree. Zhenjiang: Jiangsu University, 2016 (in Chinese)

[27] Zhang Y, Wan X Y, Zheng X D, Zhan T. Machine tool spindle design based on improved cellular multi-objective genetic algorithm. Computer Engineering and Applications, 2015, 51(6): 260–265 (in Chinese)

[28] Shao H Y. Dynamic structural optimization of machine tool spindle based on genetic algorithm. Modern Machinery, 2005, (4): 39–40, 61 (in Chinese)

[29] Lee D S , Choi D H . Reduced weight design of a flexible rotor with ball bearing stiffness characteristics varying with rotational speed and load. Journal of Vibration and Acoustics, 2000, 122(3): 203–208

[30] Möhring H C, Müller M, Krieger J, Multhoff J, Plagge C, de Wit J, Misch S. Intelligent lightweight structures for hybrid machine tools. Production Engineering, 2020, 14(5–6): 583–600

[31] Fraunhofer I Z M, Fraunhofer I P K. Eco Machine Tools Task 5 report—machine tools and related machinery. 2012, available from Ecomachinetools website

[32] Karpuschewski B , Knoche H J , Hipke M , Beutner M . High performance gear hobbing with powder-metallurgical high-speed-steel. Procedia CIRP, 2012, 1: 196–201

[33] Brecher C, Bäumler S, Jasper D, Johannes T. Energy efficient cooling systems for machine tools. In: Dornfeld D A, Linke B S, eds. Leveraging Technology for a Sustainable World. Berlin: Springer, 2012: 239–244.

[34] Oda Y , Kawamura Y , Fujishima M . Energy consumption reduction by machining process improvement. Procedia CIRP, 2012, 4: 120–124

[35] Lenz J , Kotschenreuther J , Westkaemper E . Energy efficiency in machine tool operation by online energy monitoring capturing and analysis. Procedia CIRP, 2017, 61: 365–369

[36] Montazeri S , Aramesh M , Veldhuis S C . Novel application of ultra-soft and lubricious materials for cutting tool protection and enhancement of machining induced surface integrity of Inconel 718. Journal of Manufacturing Processes, 2020, 57: 431–443

[37] Rizzo A , Goel S , Luisa Grilli M , Iglesias R , Jaworska L , Lapkovskis V , Novak P , Postolnyi B O , Valerini D . The critical raw materials in cutting tools for machining applications: a review. Materials, 2020, 13(6): 1377

[38] Niu J H, Huang C Z, Li C W, Zou B, Xu L H, Wang J, Liu Z Q. A comprehensive method for selecting cutting tool materials. The International Journal of Advanced Manufacturing Technology, 2020, 110(1–2): 229–240

[39] Jadam T , Datta S , Masanta M . Influence of cutting tool material on machinability of Inconel 718 superalloy. Machining Science and Technology, 2021, 25(3): 349–397

[40] Singh Parihar R , Kumar Sahu R , Gangi Setti S . Novel design and composition optimization of self-lubricating functionally graded cemented tungsten carbide cutting tool material for dry machining. Advances in Manufacturing, 2021, 9(1): 34–46

[41] Varghese K P , Balaji A K . Effects of tool material, tool topography and minimal quantity lubrication (MQL) on machining performance of compacted graphite iron (CGI). International Journal of Cast Metals Research, 2007, 20(6): 347–358

[42] Liu B Q , Wei W Q , Gan Y Q , Duan C X , Cui H C . Preparation, mechanical properties and microstructure of TiB₂ based ceramic cutting tool material toughened by TiC whisker. International Journal of Refractory & Hard Metals, 2020, 93: 105372

[43] Shakoori N, Fu G Y, Le B, Khaliq J, Jiang L, Huo D H, Shyha I. An experimental investigation on tool wear behaviour of uncoated and coated micro-tools in micro-milling of graphene-reinforced polymer nanocomposites. The International Journal of Advanced Manufacturing Technology, 2021, 113(7–8): 2003–2015

[44] Grigoriev S N , Fedorov S V , Hamdy K . Materials, properties, manufacturing methods and cutting performance of innovative ceramic cutting tools—a review. Manufacturing Review, 2019, 6: 19

[45] Slipchenko K V , Stratiichuk D A , Turkevich V Z , Belyavina N M , Bushlya V M , Ståhl J E . Sintering of cBN based materials with a TaC binder for cutting tool application. Journal of Superhard Materials, 2020, 42(2): 51–57

[46] Lavrinenko V I . Porosity and water absorbability of tool composite materials as factors of improving wear resistance of superabrasive grinding wheels. Part 1. Superabrasive composites. Journal of Superhard Materials, 2019, 41(2): 126–132

[47] Sharma V S , Dogra M , Suri N M . Cooling techniques for improved productivity in turning. International Journal of Machine Tools and Manufacture, 2009, 49(6): 435–453

[48] Bhowmick S , Eskandari B , Krishnamurthy G , Alpas A T . Effect of WS2 particles in cutting fluid on tribological behaviour of Ti–6Al–4V and on its machining performance. Tribology-Materials, Surfaces and Interfaces, 2021, 15(4): 229–242

[49] Das A , Patel S K , Arakha M , Dey A , Biswal B B . Processing of hardened steel by MQL technique using nano cutting fluids. Materials and Manufacturing Processes, 2021, 36(3): 316–328

[50] Li L H , Wong H C , Lee R B . Evaluation of a novel nanodroplet cutting fluid for diamond turning of optical polymers. Polymers, 2020, 12(10): 2213

[51] Sharmin I , Gafur M A , Dhar N R . Preparation and evaluation of a stable CNT-water based nano cutting fluid for machining hard-to-cut material. SN Applied Sciences, 2020, 2(4): 626

[52] Ni J , Feng K , He L H , Liu X F , Meng Z . Assessment of water-based cutting fluids with green additives in broaching. Friction, 2020, 8(6): 1051–1062

[53] Sułek M W , Bąk-Sowińska A , Przepiórka J . Ecological cutting fluids. Materials, 2020, 13(24): 5812

[54] Derani M N, Ratnam M M. The use of tool flank wear and average roughness in assessing effectiveness of vegetable oils as cutting fluids during turning—a critical review. The International Journal of Advanced Manufacturing Technology, 2021, 112(7–8): 1841–1871

[55] Debnath S , Anwar M , Basak A K , Pramanik A . Use of palm olein as cutting fluid during turning of mild steel. Australian Journal of Mechanical Engineering, 2023, 21(1): 192–202

[56] Kazeem R A , Fadare D A , Abutu J , Lawal S A , Adesina O S . Performance evaluation of jatropha oil-based cutting fluid in turning AISI 1525 steel alloy. CIRP Journal of Manufacturing Science and Technology, 2020, 31: 418–430

[57] Pal A , Chatha S S , Sidhu H S . Experimental investigation on the performance of MQL drilling of AISI 321 stainless steel using nano-graphene enhanced vegetable-oil-based cutting fluid. Tribology International, 2020, 151: 106508

[58] Lin C P , Tseng J M . Green technology for improving process manufacturing design and storage management of organic peroxide. Chemical Engineering Journal, 2012, 180: 284–292

[59] Zaitsev A I, Rodionova I G, Pavlov A A, Shaposhnikov N G, Grishin A V. Effect of composition, structural state, and manufacturing technology on service properties of high-strength low-carbon steel main bimetal layer. Metallurgist, 2015, 59(7–8): 684–692

[60] Nadtochii A M, Fokin V P, Kokhanovskii S A, Ochkov V V, Zyulkovskaya E A. Manufacturing technology and methods for technical evaluation of the quality characteristics of a cold-rammed low-shrinkage carbon-based material at the energoprom–novosibirsk electrode plant. Metallurgist, 2013, 56(11–12): 904–907

[61] Sun Y , Jin L Y , Gong Y D , Qi Y , Zhang H , Su Z P , Sun K . Experimental investigation on machinability of aluminum alloy during dry micro cutting process using helical micro end mills with micro textures. Materials, 2020, 13(20): 4664

[62] Zhang P , Yue X J , Wang P H , Yu X . Surface integrity and tool wear mechanism of 7050-T7451 aluminum alloy under dry cutting. Vacuum, 2021, 184: 109886

[63] Dennison M S , Meji M A , Umar M M . Data-set collected during turning operation of AISI 1045 alloy steel with green cutting fluids in near dry condition. Data in Brief, 2020, 32: 106215

[64] Tu L Q , Tian S , Xu F , Wang X , Xu C H , He B , Zuo D W , Zhang W J . Cutting performance of cubic boron nitride-coated tools in dry turning of hardened ductile iron. Journal of Manufacturing Processes, 2020, 56: 158–168

[65] Zhang P, Cao X, Zhang X C, Wang Y Q. Machinability and cutting force modeling of 7055 aluminum alloy with wide temperature range based on dry cutting. The International Journal of Advanced Manufacturing Technology, 2020, 111(9–10): 2787–2808

[66] Pervaiz S , Deiab I , Rashid A , Nicolescu M . Minimal quantity cooling lubrication in turning of Ti6Al4V: influence on surface roughness, cutting force and tool wear. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2017, 231(9): 1542–1558

[67] Chetan, Ghosh S, Rao P V. Specific cutting energy modeling for turning nickel-based Nimonic 90 alloy under MQL condition. International Journal of Mechanical Sciences, 2018, 146–147: 25–38

[68] Saha S , Deb S , Bandyopadhyay P P . Progressive wear based tool failure analysis during dry and MQL assisted sustainable micro-milling. International Journal of Mechanical Sciences, 2021, 212: 106844

[69] Attanasio A , Gelfi M , Giardini C , Remino C . Minimal quantity lubrication in turning: effect on tool wear. Wear, 2006, 260(3): 333–338

[70] Huang X M, Ren Y H, Jiang W, He Z J, Deng Z H. Investigation on grind-hardening annealed AISI5140 steel with minimal quantity lubrication. The International Journal of Advanced Manufacturing Technology, 2017, 89(1–4): 1069–1077

[71] Kong L F , Li Y , Lv Y J , Wang Q F . Numerical investigation on dynamic characteristics of drilling shaft in deep hole drilling influenced by minimal quantity lubrication. Nonlinear Dynamics, 2013, 74(4): 943–955

[72] Huang W T , Chou F I , Tsai J T , Lin T W , Chou J H . Optimal design of parameters for the nanofluid/ultrasonic atomization minimal quantity lubrication in a micromilling process. IEEE Transactions on Industrial Informatics, 2020, 16(8): 5202–5212

[73] Itoigawa F , Childs T H C , Nakamura T , Belluco W . Effects and mechanisms in minimal quantity lubrication machining of an aluminum alloy. Wear, 2006, 260(3): 339–344

[74] Wang S, Li C H, Zhang D K, Jia D Z, Zhang Y B. Modeling the operation of a common grinding wheel with nanoparticle jet flow minimal quantity lubrication. The International Journal of Advanced Manufacturing Technology, 2014, 74(5–8): 835–850

[75] Aoyama T . Development of a mixture supply system for machining with minimal quantity lubrication. CIRP Annals, 2002, 51(1): 289–292

[76] Sadeghi M H, Haddad M J, Tawakoli T, Emami M. Minimal quantity lubrication-MQL in grinding of Ti–6Al–4V titanium alloy. The International Journal of Advanced Manufacturing Technology, 2009, 44(5–6): 487–500

[77] Suda S , Yokota H , Inasaki I , Wakabayashi T . A synthetic ester as an optimal cutting fluid for minimal quantity lubrication machining. CIRP Annals, 2002, 51(1): 95–98

[78] Zhang Y B , Li C H , Jia D Z , Zhang D K , Zhang X W . Experimental evaluation of the lubrication performance of MoS₂/CNT nanofluid for minimal quantity lubrication in Ni-based alloy grinding. International Journal of Machine Tools and Manufacture, 2015, 99: 19–33

[79] Aslantas K , Alatrushi L K H . Experimental study on the effect of cutting tool geometry in micro-milling of Inconel 718. Arabian Journal for Science and Engineering, 2021, 46(3): 2327–2342

[80] Zhai C T, Xu J K, Li Y Q, Hou Y G, Yuan S S, Wang X, Liu Q M. Study on surface heat-affected zone and surface quality of Ti−6Al−4V alloy by laser-assisted micro-cutting. The International Journal of Advanced Manufacturing Technology, 2020, 109(7–8): 2337–2352

[81] Xue B , Geng Y Q , Yan Y D , Ma G J , Wang D , He Y . Rapid prototyping of microfluidic chip with burr-free PMMA microchannel fabricated by revolving tip-based micro-cutting. Journal of Materials Processing Technology, 2020, 277: 116468

[82] Xiao H , Hu X L , Luo S Q , Li W . Developing and testing the proto type structure for micro tool fabrication. Machines, 2022, 10(10): 938

[83] Yang S C, Su S, Wang X L, Ren W. Study on mechanical properties of titanium alloy with micro-texture ball-end milling cutter under different cutting edges. Advances in Mechanical Engineering, 2020, 12(7): 1687814020908423

[84] Schneider F , Effgen C , Kirsch B , Aurich J C . Manufacturing and preparation of micro cutting tools: influence on chip formation and surface topography when micro cutting titanium. Production Engineering, 2019, 13(6): 731–741

[85] Zhu J C , Fang X L , Qu N S . Micro-slit cutting in an aluminum foil using an un-traveling tungsten wire. Applied Sciences, 2020, 10(2): 665

[86] Li C P , Qiu X Y , Yu Z , Li S J , Li P N , Niu Q L , Kurniawan R , Ko T J . Novel environmentally friendly manufacturing method for micro-textured cutting tools. International Journal of Precision Engineering and Manufacturing-Green Technology, 2021, 8(1): 193–204

[87] Ding Y C, Shi G F, Luo X H, Shi G Q, Wang S K. Study on the critical negative rake angle of the negative rake angle tool based on the stagnant characteristics in micro-cutting. The International Journal of Advanced Manufacturing Technology, 2020, 107(5–6): 2055–2064

[88] Pramanik D , Kuar A S , Sarkar S , Mitra S . Enhancement of sawing strategy of multiple surface quality characteristics in low power fiber laser micro cutting process on titanium alloy sheet. Optics & Laser Technology, 2020, 122: 105847

[89] Ogawa K , Tanabe H , Nakagawa H , Goto M . Shape formation after laser hardening for high-precision micro-cutting edge. Advances in Materials and Processing Technologies, 2022, 8(2): 1575–1582

[90] Wang J S , Zhang X D , Fang F Z . Numerical study via total Lagrangian smoothed particle hydrodynamics on chip formation in micro cutting. Advances in Manufacturing, 2020, 8(2): 144–159

[91] Wang X, Li Y Q, Xu J K, Yu H D, Liu Q M, Liang W. Comparison and research on simulation models of aluminum-based silicon carbide micro-cutting. The International Journal of Advanced Manufacturing Technology, 2020, 109(1–2): 589–605

[92] Chen N, Zhang X L, Wu J M, Wu Y, Li L, He N. Suppressing the burr of high aspect ratio structure by optimizing the cutting parameters in the micro-milling process. The International Journal of Advanced Manufacturing Technology, 2020, 111(3–4): 985–997

[93] Yang C Y, Huang J Z, Xu J H, Ding W F, Fu Y C, Gao S W. Investigation on formation mechanism of the burrs during abrasive reaming based on the single-particle abrasive micro-cutting behavior. The International Journal of Advanced Manufacturing Technology, 2021, 113(3–4): 907–921

[94] Zhang X W , Yu T B , Dai Y X , Qu S , Zhao J . Energy consumption considering tool wear and optimization of cutting parameters in micro milling process. International Journal of Mechanical Sciences, 2020, 178: 105628

[95] Medina-Clavijo B , Ortiz-de-Zarate G , Sela A , Arrieta I M , Fedorets A , Arrazola P J , Chuvilin A . In-SEM micro-machining reveals the origins of the size effect in the cutting energy. Scientific Reports, 2021, 11(1): 2088

[96] Wen B , Shimizu Y , Watanabe Y , Matsukuma H , Gao W . On-machine profile measurement of a micro cutting edge by using a contact-type compact probe unit. Precision Engineering, 2020, 65: 230–239

[97] Sun S J , Brandt M , Palanisamy S , Dargusch M S . Effect of cryogenic compressed air on the evolution of cutting force and tool wear during machining of Ti–6Al–4V alloy. Journal of Materials Processing Technology, 2015, 221: 243–254

[98] Liu E , Deng S , Zhang C , Zhang H P , Wei X D . Simulation and experimental research on tool temperature field for low-temperature cutting of Ti-5553. Ferroelectrics, 2020, 563(1): 139–147

[99] Jerold B D , Kumar M P . The influence of cryogenic coolants in machining of Ti–6Al–4V. Journal of Manufacturing Science and Engineering, 2013, 135(3): 031005

[100] Ahmed L S , Kumar M P . Cryogenic drilling of Ti–6Al–4V alloy under liquid nitrogen cooling. Materials and Manufacturing Processes, 2016, 31(7): 951–959

[101] 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

[102] Kursuncu B . Influence of cryogenic heat-treatment soaking period and temperature on performance of sintered carbide cutting tools in milling of Inconel 718. International Journal of Refractory Metals and Hard Materials, 2020, 92: 105323

[103] Saliminia A , Abootorabi M M . Experimental investigation of surface roughness and cutting ratio in a spraying cryogenic turning process. Machining Science and Technology, 2019, 23(5): 779–793

[104] Varghese V, Ramesh M R, Chakradhar D. Experimental investigation of cryogenic end milling on maraging steel using cryogenically treated tungsten carbide-cobalt inserts. The International Journal of Advanced Manufacturing Technology, 2019, 105(5–6): 2001–2019

[105] Mia M . Multi-response optimization of end milling parameters under through-tool cryogenic cooling condition. Measurement, 2017, 111: 134–145

[106] Gowthaman B , Boopathy S R , Kanagaraju T . Effect of LN₂ and CO₂ coolants in hard turning of AISI 4340 steel using tungsten carbide tool. Surface Topography: Metrology and Properties, 2022, 10(1): 015032

[107] Sivaiah P , Chakradhar D . Influence of cryogenic coolant on turning performance characteristics: a comparison with wet machining. Materials and Manufacturing Processes, 2017, 32(13): 1475–1485

[108] Huang X D , Zhang X M , Mou H K , Zhang X J , Ding H . The influence of cryogenic cooling on milling stability. Journal of Materials Processing Technology, 2014, 214(12): 3169–3178

[109] Bermingham M J , Kirsch J , Sun S , Palanisamy S , Dargusch M S . New observations on tool life, cutting forces and chip morphology in cryogenic machining Ti−6Al−4V. International Journal of Machine Tools and Manufacture, 2011, 51(6): 500–511

[110] Trabelsi S, Morel A, Germain G, Bouaziz Z. Tool wear and cutting forces under cryogenic machining of titanium alloy (Ti17). The International Journal of Advanced Manufacturing Technology, 2017, 91(5–8): 1493–1505

[111] Nalbant M , Yildiz Y . Effect of cryogenic cooling in milling process of AISI 304 stainless steel. Transactions of Nonferrous Metals Society of China, 2011, 21(1): 72–79

[112] Abdul Halim N H , Che Haron C H , Abdul Ghani J . Sustainable machining of hardened Inconel 718: a comparative study. International Journal of Precision Engineering and Manufacturing, 2020, 21(7): 1375–1387

[113] Gharibi A , Kaynak Y . The influence of depth of cut on cryogenic machining performance of hardened steel. Journal of the Faculty of Engineering and Architecture of Gazi University, 2019, 34(2): 581–596

[114] Su Y . Investigation into the role of cooling/lubrication effect of cryogenic minimum quantity lubrication in machining of AISI H13 steel by three-dimensional finite element method. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2016, 230(6): 1003–1016

[115] Jebaraj M , Pradeep Kumar M . Effect of cryogenic CO₂ and LN₂ coolants in milling of aluminum alloy. Materials and Manufacturing Processes, 2019, 34(5): 511–520

[116] Patil N , Gopalakrishna K , Sangmesh B . Performance evaluation of cryogenic treated and untreated carbide inserts during machining of AISI 304 steel. International Journal of Automotive and Mechanical Engineering, 2020, 17(1): 7709–7718

[117] Wang F B, Bin Z, Wang Y Q. Milling force of quartz fiber-reinforced polyimide composite based on cryogenic cooling. The International Journal of Advanced Manufacturing Technology, 2019, 104(5–8): 2363–2375

[118] Sun S , Brandt M , Dargusch M S . Machining Ti–6Al–4V alloy with cryogenic compressed air cooling. International Journal of Machine Tools and Manufacture, 2010, 50(11): 933–942

[119] 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

[120] Cai W , Li Y Q , Li L , Lai K H , Jia S , Xie J , Zhang Y H , Hu L K . Energy saving and high efficiency production oriented forward-and-reverse multidirectional turning: energy modeling and application. Energy, 2022, 252: 123981

[121] Abele E, Sielaff T, Schiffler A, Rothenbücher S. Analyzing energy consumption of machine tool spindle units and identification of potential for improvements of efficiency. In: Hesselbach J, Herrmann C, eds. Glocalized Solutions for Sustainability in Manufacturing. Berlin: Springer, 2011, 280–285

[122] Sudhakara R , Landers R G . Design and analysis of output feedback force control in parallel turning. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2004, 218(6): 487–501

[123] Ozturk E , Çomak A , Budak E . Tuning of tool dynamics for increased stability of parallel (simultaneous) turning processes. Journal of Sound and Vibration, 2016, 360: 17–30

[124] Brecher C , Epple A , Neus S , Fey M . Optimal process parameters for parallel turning operations on shared cutting surfaces. International Journal of Machine Tools and Manufacture, 2015, 95: 13–19

[125] Azvar M , Budak E . Multi-dimensional chatter stability for enhanced productivity in different parallel turning strategies. International Journal of Machine Tools and Manufacture, 2017, 123: 116–128

[126] Tang L , Landers R G , Balakrishnan S N . Parallel turning process parameter optimization based on a novel heuristic approach. Journal of Manufacturing Science and Engineering, 2008, 130(3): 031002

[127] Budak E , Ozturk E . Dynamics and stability of parallel turning operations. CIRP Annals, 2011, 60(1): 383–386

[128] Yamato S , Yamada Y , Nakanishi K , Suzuki N , Yoshioka H , Kakinuma Y . Integrated in-process chatter monitoring and automatic suppression with adaptive pitch control in parallel turning. Advances in Manufacturing, 2018, 6(3): 291–300

[129] Yamato S , Okuma T , Nakanishi K , Tachibana J , Suzuki N , Kakinuma Y . Chatter suppression in parallel turning assisted with tool swing motion provided by feed system. International Journal of Automotive Technology, 2019, 13(1): 80–91

[130] Yamato S, Nakanishi K, Suzuki N, Kakinuma Y. Experimental verification of design methodology for chatter suppression in tool swing-assisted parallel turning. The International Journal of Advanced Manufacturing Technology, 2020, 110(7–8): 1759–1771

[131] Luo Y B , Ong S K , Chen D F , Nee A Y C . An internet-enabled image- and model-based virtual machining system. International Journal of Production Research, 2002, 40(10): 2269–2288

[132] He H W , Wu Y M . Web-based virtual operating of CNC milling machine tools. Computers in Industry, 2009, 60(9): 686–697

[133] Kadir A A , Xu X , Hämmerle E . Virtual machine tools and virtual machining—a technological review. Robotics and Computer-Integrated Manufacturing, 2011, 27(3): 494–508

[134] Yoon H S , Kim E S , Kim M S , Lee J Y , Lee G B , Ahn S H . Towards greener machine tools—a review on energy saving strategies and technologies. Renewable & Sustainable Energy Reviews, 2015, 48: 870–891

[135] Wang Z Q , Wang X R , Wang Y S , Wang R J , Bao M Y , Lin T S , He P . Ball end mill—tool radius compensation of complex NURBS surfaces for 3-axis CNC milling machines. International Journal of Precision Engineering and Manufacturing, 2020, 21(8): 1409–1419

[136] Yue H T , Guo C G , Li Q , Zhao L J , Hao G B . Thermal error modeling of CNC milling machine tool spindle system in load machining: based on optimal specific cutting energy. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2020, 42(9): 456

[137] Piórkowski P , Skoczyński W . Statistical testing of milled objects on numerically controlled three-axis milling machines. Advances in Science and Technology Research Journal, 2021, 15(1): 283–289

[138] Caputi A , Russo D . The optimization of the control logic of a redundant six axis milling machine. Journal of Intelligent Manufacturing, 2021, 32(5): 1441–1453

[139] Li P Z , Zhao R H , Luo L . A geometric accuracy error analysis method for turn-milling combined NC machine tool. Symmetry, 2020, 12(10): 1622

[140] Merghache S M, Hamdi A. Numerical evaluation of geometrical errors of three-axes CNC machine tool due to cutting forces—case: milling. The International Journal of Advanced Manufacturing Technology, 2020, 111(5–6): 1683–1705

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

[142] 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

[143] Shafiq S I , Sanin C , Szczerbicki E . Knowledge-based virtual modeling and simulation of manufacturing processes for Industry 4.0. Cybernetics and Systems, 2020, 51(2): 84–102

[144] Peruzzini M , Grandi F , Cavallaro S , Pellicciari M . Using virtual manufacturing to design human-centric factories: an industrial case. The International Journal of Advanced Manufacturing Technology, 2021, 115(3): 873–887

[145] Berg L P , Vance J M . Industry use of virtual reality in product design and manufacturing: a survey. Virtual Reality, 2017, 21(1): 1–17

[146] Iwase T , Kamaji Y , Kang S Y , Koga K , Kuboi N , Nakamura M , Negishi N , Nozaki T , Nunomura S , Ogawa D , Omura M , Shimizu T , Shinoda K , Sonoda Y , Suzuki H , Takahashi K , Tsutsumi T , Yoshikawa K , Ishijima T , Ishikawa K . Progress and perspectives in dry processes for leading-edge manufacturing of devices: toward intelligent processes and virtual product development. Japanese Journal of Applied Physics, 2019, 58(SE): SE0804

[147] Chen D . A methodology for developing service in virtual manufacturing environment. Annual Reviews in Control, 2015, 39: 102–117

[148] Kao Y C, Chen H Y, Chen Y C. Development of a virtual controller integrating virtual and physical CNC. Materials Science Forum, 2006, 505–507: 631–636

[149] Kadir A A , Xu X . Towards high-fidelity machining simulation. Journal of Manufacturing Systems, 2011, 30(3): 175–186

[150] Cai W , Hu S J , Yuan J X . Deformable sheet metal fixturing: principles, algorithms, and simulations. Journal of Manufacturing Science and Engineering, 1996, 118(3): 318–324

[151] Cheung C F , Lee W B . Modelling and simulation of surface topography in ultra-precision diamond turning. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2000, 214(6): 463–480

[152] Ong S K , Jiang L , Nee A Y C . An internet-based virtual CNC milling system. The International Journal of Advanced Manufacturing Technology, 2002, 20(1): 20–30

[153] Liu H , Peng F , Liu Y . Final machining of large-scale engine block with modularized fixture and virtual manufacturing technologies. Journal of Engineering, 2017, 2017: 3648954

[154] Zhu L D , Li H N , Liang W L , Wang W S . A web-based virtual CNC turn-milling system. The International Journal of Advanced Manufacturing Technology, 2015, 78(1‒4): 99–113

[155] Heugenhauser S , Kaschnitz E , Schumacher P . Development of an aluminum compound casting process-experiments and numerical simulations. Journal of Materials Processing Technology, 2020, 279: 116578

[156] Ren Z Y , Shen L L , Bai H B , Pan L , Xu J . Study on the mechanical properties of metal rubber with complex contact friction of spiral coils based on virtual manufacturing technology. Advanced Engineering Materials, 2020, 22(8): 2000382

[157] Altintas Y , Merdol S D . Virtual high performance milling. CIRP Annals, 2007, 56(1): 81–84

[158] Hu L K , Liu W P , Xu K K , Peng T , Yang H D , Tang R Z . Turning part design for joint optimisation of machining and transportation energy consumption. Journal of Cleaner Production, 2019, 232: 67–78

[159] Cai W , Wang L G , Li L , Xie J , Jia S , Zhang X G , Jiang Z G , Lai K H . A review on methods of energy performance improvement towards sustainable manufacturing from perspectives of energy monitoring, evaluation, optimization and benchmarking. Renewable & Sustainable Energy Reviews, 2022, 159: 112227

[160] Calvanese M L, Albertelli P, Matta A, Taisch M. Analysis of energy consumption in CNC machining centers and determination of optimal cutting conditions. In: Nee A Y C, Song B, Ong S K, eds. Re-engineering Manufacturing for Sustainability. Singapore: Springer, 2013, 227–232

[161] Li C B , Chen X Z , Tang Y , Li L . Selection of optimum parameters in multi-pass face milling for maximum energy efficiency and minimum production cost. Journal of Cleaner Production, 2017, 140: 1805–1818

[162] Li Z P , Ren S . Energy efficiency optimization of mechanical numerical control machining parameters. Academic Journal of Manufacturing Engineering, 2018, 16(1): 76–87

[163] Lee W , Kim S H , Park J , Min B K . Simulation-based machining condition optimization for machine tool energy consumption reduction. Journal of Cleaner Production, 2017, 150: 352–360

[164] Hu L K , Tang R Z , Cai W , Feng Y X , Ma X . Optimisation of cutting parameters for improving energy efficiency in machining process. Robotics and Computer-Integrated Manufacturing, 2019, 59: 406–416

[165] Yi Q , Li C B , Ji Q Q , Zhu D G , Jin Y , Li L L . Design optimization of lathe spindle system for optimum energy efficiency. Journal of Cleaner Production, 2020, 250: 119536

[166] Sangwan K S , Kant G . Optimization of machining parameters for improving energy efficiency using integrated response surface methodology and genetic algorithm approach. Procedia CIRP, 2017, 61: 517–522

[167] Li C B , Xiao Q G , Tang Y , Li L . A method integrating Taguchi, RSM and MOPSO to CNC machining parameters optimization for energy saving. Journal of Cleaner Production, 2016, 135: 263–275

[168] Sangwan K S , Sihag N . Multi-objective optimization for energy efficient machining with high productivity and quality for a turning process. Procedia CIRP, 2019, 80: 67–72

[169] Zhao F , Murray V R , Ramani K , Sutherland J W . Toward the development of process plans with reduced environmental impacts. Frontiers of Mechanical Engineering, 2012, 7(3): 231–246

[170] da Costa D D , Gussoli M , Valle P D , Rebeyka C J . A methodology to assess energy efficiency of conventional lathes. Energy Efficiency, 2022, 15(1): 7

[171] Triebe M J , Zhao F , Sutherland J W . Modelling the effect of slide table mass on machine tool energy consumption: the role of lightweighting. Journal of Manufacturing Systems, 2022, 62: 668–680

[172] Dai Y , Tao X S , Li Z L , Zhan S Q , Li Y , Gao Y H . A review of key technologies for high-speed motorized spindles of CNC machine tools. Machines, 2022, 10(2): 145

[173] Muthuswamy P , Shunmugesh K . Artificial intelligence based tool condition monitoring for digital twins and Industry 4.0 applications. International Journal on Interactive Design and Manufacturing, 2023, 17(3): 1067–1087

[174] Zhao G, Cheng K, Wang W, Liu Y Z, Dan Z H. A milling cutting tool selection method for machining features considering energy consumption in the STEP-NC framework. The International Journal of Advanced Manufacturing Technology, 2022, 120(5–6): 3963–3981

[175] Li C B, Wu S Q, Yi Q, Zhao X K, Cui L G. A cutting parameter energy-saving optimization method considering tool wear for multi-feature parts batch processing. The International Journal of Advanced Manufacturing Technology, 2022, 121(7–8): 4941–4960

[176] Mustafa G , Anwar M T , Ahmed A , Nawaz M , Rasheed T . Influence of machining parameters on machinability of Inconel 718—a review. Advanced Engineering Materials, 2022, 24(10): 2200202

[177] Katna R, Suhaib M, Agrawal N. Performance of non-edible oils as cutting fluids for green manufacturing. Materials and Manufacturing Processes, 2023, 38(12): 1531–1548

[178] Wang Y Z, Zheng C L, Liu N C, Wu L, Chen Y. Surface integrity investigation and multi-objective optimization in high-speed cutting of AISI 304 stainless steel for dry cutting and MQCL conditions. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2022 (in press)

[179] Gürbüz H , Gönülaçar Y E . Experimental and statistical investigation of the effects of MQL, dry and wet machining on machinability and sustainability in turning of AISI 4140 steel. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2022, 236(5): 1808–1823

[180] Kishawy H A , Salem A , Hegab H , Hosseini A , Elbestawi M . An analytical model for the optimized design of micro-textured cutting tools. CIRP Annals, 2022, 71(1): 49–52

[181] Gan Y Q, Wang Y Q, Liu K, Yang Y B, Jiang S W, Zhang Y. Machinability investigations in cryogenic internal cooling turning Ti−6Al−2Zr−1Mo−1 V titanium alloy. The International Journal of Advanced Manufacturing Technology, 2022, 120(11–12): 7565–7574

[182] Zhang Y H , Cai W , He Y , Peng T , Jia S , Lai K H , Li L . Forward-and-reverse multidirectional turning: a novel material removal approach for improving energy efficiency, processing efficiency and quality. Energy, 2022, 260: 125162

[183] Lv Y , Li C B , He J X , Li W , Li X Y , Li J . Energy saving design of the machining unit of hobbing machine tool with integrated optimization. Frontiers of Mechanical Engineering, 2022, 17(3): 38

[184] Chuo Y S , Lee J W , Mun C H , Noh I W , Rezvani S , Kim D C , Lee J , Lee S W , Park S S . Artificial intelligence enabled smart machining and machine tools. Journal of Mechanical Science and Technology, 2022, 36(1): 1–23

[185] Feng C H, Huang Y G, Wu Y L, Zhang J Y. Feature-based optimization method integrating sequencing and cutting parameters for minimizing energy consumption of CNC machine tools. The International Journal of Advanced Manufacturing Technology, 2022, 121(1–2): 503–515

[186] Li W , Li C B , Wang N B , Li J , Zhang J W . Energy saving design optimization of CNC machine tool feed system: a data-model hybrid driven approach. IEEE Transactions on Automation Science and Engineering, 2022, 19(4): 3809–3820

[187] Jia S, Wang S, Zhang N, Cai W, Liu Y, Hao J, Zhang Z W, Yang Y, Sui Y. Multi-objective parameter optimization of CNC plane milling for sustainable manufacturing. Environmental Science and Pollution Research, 2022 (in press)

[188] Ruan Y , Hang C C , Wang Y M . Government’s role in disruptive innovation and industry emergence: the case of the electric bike in China. Technovation, 2014, 34(12): 785–796

[189] Wang Y T , Liu J , Hansson L , Zhang K , Wang R Q . Implementing stricter environmental regulation to enhance eco-efficiency and sustainability: a case study of Shandong province’s pulp and paper industry, China. Journal of Cleaner Production, 2011, 19(4): 303–310

[190] Veugelers R. Which policy instruments to induce clean innovating? Research Policy, 2012, 41(10): 1770–1778

[191] Zhao X , Sun B W . The influence of Chinese environmental regulation on corporation innovation and competitiveness. Journal of Cleaner Production, 2016, 112: 1528–1536

[192] Ramanathan R , He Q L , Black A , Ghobadian A , Gallear D . Environmental regulations, innovation and firm performance: a revisit of the Porter hypothesis. Journal of Cleaner Production, 2017, 155: 79–92

[193] Dolfsma W, Seo D B. Government policy and technological innovation—a suggested typology. Technovation, 2013, 33(6–7): 173–179

[194] Huang S K , Kuo L P , Chou K L . The impacts of government policies on green utilization diffusion and social benefits—a case study of electric motorcycles in Taiwan. Energy Policy, 2018, 119: 473–486

[195] YuanB LRenS GChenX H.. Can environmental regulation promote the coordinated development of economy and environment in China’s manufacturing industry?—A panel data analysis of 28 sub-sectors. Journal of Cleaner Production, 2017, 149: 11–24

[196] Wang M M , Lian S , Yin S , Dong H M . A three-player game model for promoting the diffusion of green technology in manufacturing enterprises from the perspective of supply and demand. Mathematics, 2020, 8(9): 1585

[197] Song M L , Wang S H , Sun J . Environmental regulations, staff quality, green technology, R&D efficiency, and profit in manufacturing. Technological Forecasting and Social Change, 2018, 133: 1–14

[198] Yi M , Fang X M , Wen L , Guang F T , Zhang Y . The heterogeneous effects of different environmental policy instruments on green technology innovation. International Journal of Environmental Research and Public Health, 2019, 16(23): 4660

[199] Yin S , Zhang N , Li B Z , Dong H M . Enhancing the effectiveness of multi-agent cooperation for green manufacturing: dynamic co-evolution mechanism of a green technology innovation system based on the innovation value chain. Environmental Impact Assessment Review, 2021, 86: 106475

[200] Dornfeld D A . Moving towards green and sustainable manufacturing. International Journal of Precision Engineering and Manufacturing-Green Technology, 2014, 1(1): 63–66

[201] Du K R , Li J L . Towards a green world: How do green technology innovations affect total-factor carbon productivity. Energy Policy, 2019, 131: 240–250

[202] Palčič I , Prester J . Impact of advanced manufacturing technologies on green innovation. Sustainability, 2020, 12(8): 3499

[203] Kong T , Feng T W , Ye C M . Advanced manufacturing technologies and green innovation: the role of internal environmental collaboration. Sustainability, 2016, 8(10): 1056

[204] Zhang Y L , Sun J , Yang Z J , Wang Y . Critical success factors of green innovation: technology, organization and environment readiness. Journal of Cleaner Production, 2020, 264: 121701

[205] Fu Y , Supriyadi A , Wang T , Wang L W , Cirella G T . Effects of regional innovation capability on the green technology efficiency of China’s manufacturing industry: evidence from listed companies. Energies, 2020, 13(20): 5467

[206] Peng B H , Zheng C Y , Wei G , Elahi E . The cultivation mechanism of green technology innovation in manufacturing industry: from the perspective of ecological niche. Journal of Cleaner Production, 2020, 252: 119711

[207] Yin S , Zhang N , Li B Z . Improving the effectiveness of multi-agent cooperation for green manufacturing in China: a theoretical framework to measure the performance of green technology innovation. International Journal of Environmental Research and Public Health, 2020, 17(9): 3211

[208] Guo R , Lv S , Liao T , Xi F R , Zhang J , Zuo X T , Cao X J , Feng Z , Zhang Y L . Classifying green technologies for sustainable innovation and investment. Resources, Conservation and Recycling, 2020, 153: 104580

[209] Zhang R T , Li J Y . Impact of incentive and selection strength on green technology innovation in Moran process. PLoS ONE, 2020, 15(6): e0235516

[210] Zhou Y C , Zhang B , Zou J , Bi J , Wang K . Joint R&D in low-carbon technology development in China: a case study of the wind-turbine manufacturing industry. Energy Policy, 2012, 46: 100–108

[211] Yin S , Zhang N , Li B Z . Enhancing the competitiveness of multi-agent cooperation for green manufacturing in China: an empirical study of the measure of green technology innovation capabilities and their influencing factors. Sustainable Production and Consumption, 2020, 23: 63–76

[212] Hu D X , Jiao J L , Tang Y S , Han X F , Sun H P . The effect of global value chain position on green technology innovation efficiency: from the perspective of environmental regulation. Ecological Indicators, 2021, 121: 107195

Nomenclature

AMT	Advanced manufacturing technology
CMI	China’s manufacturing industry
CNC	Computer numerical control
CRM	Critical raw materials
FGCC	Functionally graded cemented carbide
MOPSO	Multi-objective particle swarm optimization
MQL	Minimal quantity of lubricant
Mtce	Million tons of coal equivalent
PCBN	Polycrystalline cubic boron nitride
PVD	Physical vapor deposition
R&D	Research and development
RBR	Rule-based reasoning
RSM	Response surface method
TRC	Tool radius compensation
VMT	Virtual machine tool

Acknowledgement

This work was partially supported by the Natural Science Foundation of Chongqing, China (Grant No. 2023NSCQ-MSX1240), Sichuan Science and Technology Program, China (Grant No. 2023JDRC0067), the PolyU Distinguished Postdoctoral Fellowship Scheme, China (Grant No. P0039216), and the National Natural Science Foundation of China (Grant Nos. 51875480 and 51805479).

Conflict of Interest

The authors declare that they have no conflict of interest.

Open Access

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution, and reproduction in any medium or format as long as appropriate credit is given to the original author(s) and source, a link to the Creative Commons license is provided, and the changes made are indicated.

The images or other third-party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Visit http://creativecommons.org/licenses/by/4.0/ to view a copy of this license.

RIGHTS & PERMISSIONS

2023 The Author(s). This article is published with open access at link.springer.com and journal.hep.com.cn