Abstract
The manufacturing industries have played a stellar role in contributing toward global economy. However, the industrial development of the past decades was built on traditional manufacturing. Nowadays, smart manufacturing approach is desirable for economic growth of the country. In this paper, various emerging approaches are discussed for sustainable and smart machining process. The first four approaches are concerned with the process of machinability enhancement and are used to assess machining performance as well as its economic implications. Novel approaches for designing and modelling of tools that aid in the supply of coolant/lubricant in a smooth and effective manner are discussed. Modelling and setting upgraded fixtures can assist in regulating the production time of machining process. The implementation of developing technologies in futuristic manufacturing is the fifth crucial factor. Furthermore, it aims to figure out how to increase machinability so that it does not affect the employees and results in a more environmentally friendly manufacturing process. The discussed approaches can make industries more productive and efficient to bring ground breaking changes in order to move toward smart and sustainable machining processes that can help in bringing about a cleaner world and a better tomorrow.
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References
F. Pusavec, H. Hamdi, J. Kopac, I. Jawahir, Surface integrity in cryogenic machining of nickel based alloy—Inconel 718. J. Mater. Process. Technol. 211(4), 773–783 (2011). https://doi.org/10.1016/j.jmatprotec.2010.12.013
P. Sivaiah, G.V. Ajay Kumar, M.M. Singh, H. Kumar, Effect of novel hybrid texture tool on turning process performance in MQL machining of Inconel 718 superalloy. Mater. Manuf. Process. 35(1), 61–71 (2020)
S. Shu, Y. Zhang, Y. He, H. Zhang, Design of a novel turning tool cooled by combining circulating internal cooling with spray cooling for green cutting. J. Adv. Mech. Des. Syst. Manuf. (2021). https://doi.org/10.1299/jamdsm.2021jamdsm0003
S.R. Oke, G.S. Ogunwande, M. Onifade, E. Aikulola, E.D. Adewale, O.E. Olawale, M.O. Bodunrin, An overview of conventional and non-conventional techniques for machining of titanium alloys. Manuf. Rev. 7, 34 (2020)
World Commission on Environment and Development, Our Common Future (Oxford University Press, New York, 1987)
K.R. Haapala, Fu. Zhao, J. Camelio, J.W. Sutherland, S.J. Skerlos, D.A. Dornfeld, I.S. Jawahir, A.F. Clarens, J.L. Rickli, A review of engineering research in sustainable manufacturing. J. Manuf. Sci. Eng. 135(4), 041013 (2013)
D. Hariyani, S. Mishra, P. Hariyani, M.K. Sharma, Drivers and motives for sustainable manufacturing system. Innov. Green Dev. 2(1), 100031 (2023)
D. Hariyani, S. Mishra, M.K. Sharma, P. Hariyani, Organizational barriers to the sustainable manufacturing system: A literature review. Environ. Chall. 9, 100606 (2022). https://doi.org/10.1016/j.envc.2022.100606
Y. Su, N. He, L. Li, X. Li, An experimental investigation of effects of cooling/lubrication conditions on tool wear in high-speed end milling of Ti-6Al-4V. Wear 261(7–8), 760–766 (2006). https://doi.org/10.1016/j.wear.2006.01.013
Ç. Yıldırım, T. Kıvak, M. Sarıkaya, F. Erzincanlı, Determination of MQL parameters contributing to sustainable machining in the milling of nickel-base superalloywaspaloy. Arab. J. Sci. Eng. 42(11), 4667–4681 (2017). https://doi.org/10.1007/s13369-017-2594-z
A. Okafor, T. Nwoguh, Comparative evaluation of soybean oil–based MQL flow rates and emulsion flood cooling strategy in high-speed face milling of Inconel 718. Int. J. Adv. Manuf. Technol. 107(9–10), 3779–3793 (2020). https://doi.org/10.1007/s00170-020-05248-3
Y. Deshpande, A. Andhare, P. Padole, Experimental results on the performance of cryogenic treatment of tool and minimum quantity lubrication for machinability improvement in the turning of Inconel 718. J. Braz. Soc. Mech. Sci. Eng. (2018). https://doi.org/10.1007/s40430-017-0920-8
M. Sadik, S. Isakson, A. Malakizadi, L. Nyborg, Influence of coolant flow rate on tool life and wear development in cryogenic and wet milling of Ti-6Al-4V. Procedia CIRP 46, 91–94 (2016). https://doi.org/10.1016/j.procir.2016.02.014
A. Aramcharoen, S. Chuan, An experimental investigation on cryogenic milling of inconel 718 and its sustainability assessment. Procedia CIRP 14, 529–534 (2014). https://doi.org/10.1016/j.procir.2014.03.076
A. Iturbe, E. Hormaetxe, A. Garay, P. Arrazola, Surface integrity analysis when machining inconel 718 with conventional and cryogenic cooling. Procedia CIRP 45, 67–70 (2016). https://doi.org/10.1016/j.procir.2016.02.095
D. Shokrani, V., Newman, S., & Imani-Asrai, R., An initial study of the effect of using liquid nitrogen coolant on the surface roughness of inconel 718 nickel-based alloy in CNC milling. Procedia CIRP 3, 121–125 (2012). https://doi.org/10.1016/j.procir.2012.07.022
F. Pusavec, Porous tungsten machining under cryogenic conditions. Int. J. Refr. Metals Hard Mater. 35, 84–89 (2012). https://doi.org/10.1016/j.ijrmhm.2012.04.009
T. Obikawa, A. Kamio, H. Takaoka, A. Osada, Micro-texture at the coated tool face for high performance cutting. Int. J. Mach. Tools Manuf 51(12), 966–972 (2011)
Shu, S. R. Design and analysis of the internally cooled smart turning tool and experimental study. Ph.D. thesis, Harbin Institute of Technology, Harbin, 2014 (in Chinese).
T. Sugihara, Y. Nishimoto, T. Enomoto, Development of a novel cubic boron nitride cutting tool with a textured flank face for high-speed machining of Inconel 718. Precis. Eng. 48, 75–82 (2017)
M. El-Bestawi, T. El-Wardany, D. Yan, M. Tan, Performance of whisker-reinforced ceramic tools in milling nickel-based superalloy. CIRP Ann. 42(1), 99–102 (1993). https://doi.org/10.1016/s0007-8506(07)62401-9
M. Aramesh, S. Montazeri, S. Veldhuis, A novel treatment for cutting tools for reducing the chipping and improving tool life during machining of Inconel 718. Wear 414–415, 79–88 (2018). https://doi.org/10.1016/j.wear.2018.08.002
Swami, A., & Kondhalkar, G. Design, development and analysis of hydraulic fixture for machining engine cylinder block on VMC. Int. Res. J. Eng. Technol. 463–469 (2016).
C. Patel, G. Acharya, Design and manufacturing of 8 cylinder hydraulic fixture for boring yoke on VMC - 1050. Procedia Technol. 14, 405–412 (2014). https://doi.org/10.1016/j.protcy.2014.08.052
J. Dhulia, N. Maniar, Design, modelling and manufacturing of 16 cylinder hydraulic fixture with automated clamping system. J. Phys. Conf. Ser. 1240(1), 012036 (2019). https://doi.org/10.1088/1742-6596/1240/1/012036
N. Amaral, J. Rencis, Y. Rong, Development of a finite element analysis tool for fixture design integrity verification and optimisation. Int. J. Adv. Manuf. Technol. 25(5–6), 409–419 (2004). https://doi.org/10.1007/s00170-003-1796-6
N. Maniar, D. Vakharia, Design & development of rotary fixture for CNC with computer aided mass balancing method as pre-mortem tool. Procedia Technol. 14, 397–404 (2014). https://doi.org/10.1016/j.protcy.2014.08.051
M. Jegan, B. Pitchia Krishnan, M. Shanmugam, I.K. Raj, P., & Bose, K., Design and analysis of hydraulic fixture for hydraulic lift housing. J. Phys. Conf. Ser. 1964(7), 072019 (2021). https://doi.org/10.1088/1742-6596/1964/7/072019
R. Patil, D. Dinesh, H. Sachin, K. Vishal, Design of milling fixture in mass production of pivot block. Asian Rev. Mech. Eng. 6(1), 13–17 (2017)
Ç. Yıldırım, T. Kıvak, F. Erzincanlı, Influence of different cooling methods on tool life, wear mechanisms and surface roughness in the milling of nickel-based waspaloy with WC tools. Arab. J. Sci. Eng. 44(9), 7979–7995 (2019). https://doi.org/10.1007/s13369-019-03963-y
Deshpande, Y., Andhare, A., & Padole, P. Performance appraisal of cryogenically treated tool in dry, MQL and cryogenic machining of Inconel 718. Adv. Mech. Engi., Lecture Notes Mech. Eng. (2020)
Pham, M., Yoon, H., Khare, V., &Ahn, S. Evaluation of ionic liquids as lubricants in micro milling—process capability and sustainability. (2014)
A. Khan, K. Maity, Comparative study of some machinability aspects in turning of pure titanium with untreated and cryogenically treated carbide inserts. J. Manuf. Process. 28, 272–328 (2017)
A.V. Pradeep, A., Dumpala, L., & Ramakrishna, S., Effect of MQL on roughness, white layer and microhardness in hard turning of AISI 52100. Emerg. Mater. Res. 8(1), 29–43 (2019). https://doi.org/10.1680/jemmr.18.00038
N. Uçak, A. Çiçek, The effects of cutting conditions on cutting temperature and hole quality in drilling of Inconel 718 using solid carbide drills. J. Manuf. Process. 31, 662–673 (2018). https://doi.org/10.1016/j.jmapro.2018.01.003
D. Ibrahim, An overview of soft computing. Procedia Comput. Sci. 102, 34–38 (2016)
Shukla, K. K., Sinha, Naresh K.; Gupta, MADAN M. (eds.), "CHAPTER 17 - Soft Computing Paradigms for Artificial Vision", Soft Computing and Intelligent Systems, Academic Press Series in Engineering, San Diego: Academic Press, pp. 405–417, ISBN 978–0–12 646490–0, retrieved 2021–02–24 (2000)
I.S. Jawahir, D.A. Stephenson, B. Wang, A review of advances in modeling of conventional machining processes: from merchant to the present. J. Manuf. Sci. Eng. 144, 110801–110811 (2022)
Y. Deshpande, A. Andhare, P. Padole, Application of statistical and soft computational techniques in machining of Nickel based supper-alloy using cryogenically treated tools for estimation of surface roughness. Aust. J. Mech. Eng. (2022). https://doi.org/10.1080/14484846.2021.2023349
Kuram, E., Simsek, B. T., Ozcelik, B., Demirbas, E., & Askin, S. Optimization of the cutting fluids and parameters using Taguchi and ANOVA in milling. In: Proceedings of the world congress on engineering (Vol. 2, pp. 1–5) (2010)
S. Tesic, D. Cica, S. Borojevic, B. Sredanovic, M. Zeljkovic, D. Kramar, F. Pusavec, Optimization and prediction of specific energy consumption in ball-end milling of Ti-6Al-4V alloy under MQL and cryogenic cooling/lubrication conditions. Int. J. Precis. Engi. Manuf. Green Technol. (2022). https://doi.org/10.1007/s40684-021-00413-9
P. Dumbhare, S. Dubey, V. Deshpande, Y., Andhare, A., & Barve, P., Modelling and multi-objective optimization of surface roughness and kerf taper angle in abrasive water jet machining of steel. J. Braz. Soc. Mech. Sci. Eng. (2018). https://doi.org/10.1007/s40430-018-1186-5
A. Madankar, P. Dumbhare, Y. Deshpande, A. Andhare, P. Barve, Estimation and control of surface quality and traverse speed in abrasive water jet machining of AISI 1030 steel using different work-piece thicknesses by RSM. Aust. J. Mech. Eng. (2021). https://doi.org/10.1080/14484846.2021.1876600
I. La FéPerdomo, R. Quiza, D. Haeseldonckx, M. Rivas, Sustainability-focused multi-objective optimization of a turning process. Int. J. Precis. Eng. Manuf. Green Technol. 7(5), 1009–1018 (2019). https://doi.org/10.1007/s40684-019-00122-4
F. Han, L. Li, W. Cai, C. Li, X. Deng, J. Sutherland, Parameters optimization considering the trade- off between cutting power and MRR based on linear decreasing particle swarm algorithm in milling. J. Clean. Prod. 262, 121388 (2020). https://doi.org/10.1016/j.jclepro.2020.121388
R. Venkata Rao, P. Pawar, Parameter optimization of a multi-pass milling process using non-traditional optimization algorithms. Appl. Soft Comput. 10(2), 445–456 (2010). https://doi.org/10.1016/j.asoc.2009.08.007
D. Jang, J. Jung, J. Seok, Modeling and parameter optimization for cutting energy reduction in MQL milling process. Int. J. Precis. Eng. Manuf.-Green Technol. 3(1), 5–12 (2016). https://doi.org/10.1007/s40684-016-0001-y
Y.V. Deshpande, A.B. Andhare, P.M. Padole, Application of ANN to estimate surface roughness using cutting parameters, force, sound and vibration in turning of Inconel 718. SN Appl. Sci. 1, 104 (2019). https://doi.org/10.1007/s42452-018-0098-4
Y. Deshpande, A. Andhare, N. Sahu, Estimation of surface roughness using cutting parameters, force, sound, and vibration in turning of Inconel 718. J. Braz. Soc. Mech. Sci. Eng. 39(12), 5087–5096 (2017). https://doi.org/10.1007/s40430-017-0819-4
Deshpande, Y., Andhare, A., Padole, P., & Sahu, N. Application of advanced algorithms for enhancement in machining performance of Inconel 718. Indian J. Eng. Mater. Sci. 25: 366–376 (2018).
L. Zhang, B. Zhang, H. Bao, H. Huang, Optimization of cutting parameters for minimizing environmental impact: considering energy efficiency, noise emission and economic dimension. Int. J. Precis. Eng. Manuf. 19(4), 613–624 (2018). https://doi.org/10.1007/s12541-018-0074-3
M. Aazam, S. Zeadally, K.A. Harras, Deploying fog computing in industrial internet of things and industry 4 0. IEEE Trans. Industr. Inf. 14(10), 4674–4682 (2018)
M.H. Ur Rehman, I. Yaqoob, K. Salah, M. Imran, P.P. Jayaraman, C. Perera, The role of big data analytics in industrial Internet of Things. Future Gener. Comput. Syst. 99, 247–259 (2019)
C. Cronin, A. Conway, J. Walsh, Flexible manufacturing systems using IIoT in the automotive sector. Procedia Manuf. 38, 1652–1659 (2019)
Karnouskos, S., Colombo, A. W., Lastra, J. L. M., & Popescu, C. Towards the energy efficient future factory. In: 2009 7th IEEE International Conference on Industrial Informatics (pp. 367–371) (2009)
D. Wu, S. Liu, L. Zhang, J. Terpenny, R.X. Gao, T. Kurfess, J.A. Guzzo, A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing. J. Manuf. Syst. 43, 25–34 (2017)
L. Wang, W. Ji, Cloud enabled CPS and big data in manufacturing. Lecture Notes Mech. Eng. (2018). https://doi.org/10.1007/978-3-319-89563-5_20
C. Li, Y. Chen, Y. Shang, A review of industrial big data for decision making in intelligent manufacturing. Eng. Sci. Technol. Int. J. 29, 101021 (2022)
W. Ji, J. Shi, X. Liu, L. Wang, S. Liang, A novel approach of tool wear evaluation. J. Manuf. Sci. Eng. (2017). https://doi.org/10.1115/1.4037231
F. Tao, Q. Qi, A. Liu, A. Kusiak, Data-driven smart manufacturing. J. Manuf. Syst. 48, 157–169 (2018)
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Deshpande, Y.V., Ayer, S., Agrawal, T. et al. Application of Smart Strategies for Sustainable Manufacturing of Conventional Machining Process: A Review. J. Inst. Eng. India Ser. C 104, 1267–1289 (2023). https://doi.org/10.1007/s40032-023-00995-0
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DOI: https://doi.org/10.1007/s40032-023-00995-0