Abstract
Ultra-precision manufacturing (UPM) is a promising manufacturing technology for fabricating micro-components and its production volume raises in the coming future due to a significant increase in the production volume for highly technological products nowadays. Therefore, UPM industries are accountable for executing sustainability practices to minimize negative environmental impacts from their manufacturing activities. However, sustainable UPM is difficult to execute practically up to now due to different aspects such as technology and knowledge gap. With a high speed of technology advancement nowadays, UPM industries enable to leverage this technological chance and employ the Internet of Things (IoT) technique to move UPM toward sustainability. Therefore, in this article, the current status and future perspective of sustainable UPM, the major research and technological gap between UPM and sustainability development, specific technical challenges for integrated IoT to UPM for sustainability goal are discussed and revealed to promote sustainable UPM. And consequently, a preliminary framework of IoT based UPM system with particular suggestions was firstly presented for facilitating sustainable UPM and acts as the reference to related industries and academia for further developing this novel technique in the future.
Data availability
Data available on request from the authors.
Code availability
No Code is used in this work.
References
Aggogeri, F., Merlo, A., & Pellegrini, N. (2020). Active vibration control development in ultra-precision machining. Journal of Vibration and Control. https://doi.org/10.1177/1077546320933477
Aly, M. F., Ng, E., Veldhuis, S. C., & Elbestawi, M. A. (2006). Prediction of cutting forces in the micro-machining of silicon using a “hybrid molecular dynamic-finite element analysis” force model. International Journal of Machine Tools and Manufacture, 46(14), 1727–1739
Amin, S. (1977). Imperialism and unequal development. Monthly Review Press.
Babiceanu, R. F., & Seker, R. (2016). Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook. Computers in Industry, 81, 128–137
Bi, Z. M., & Wang, L. (2012). Optimization of machining processes from the perspective of energy consumption: A case study. Journal of Manufacturing Systems, 31(4), 420–428
Carr, J. W., & Feger, C. (1993). Ultraprecision machining of polymers. Precision Engineering, 15(4), 221–237
Chen, D., Gao, X., Dong, L., & Fan, J. (2017). An evaluation system for surface waviness generated by the dynamic behavior of a hydrostatic spindle in ultra-precision machining. The International Journal of Advanced Manufacturing Technology, 91(5–8), 2185–2192
Chen, X., Xiao, J., Zhu, Y., Tian, R., Shu, X., & Xu, J. (2017). Micro-machinability of bulk metallic glass in ultra-precision cutting. Materials and Design, 136, 1–12
Cheng, C., Wang, Z., Hung, W., Bukkapatnam, S. T. S., & Komanduri, R. (2015). Ultra-precision machining process dynamics and surface quality monitoring. Procedia Manufacturing, 1, 607–618
Corbett, J., McKeown, P. A., Peggs, G. N., & Whatmore, R. (2000). Nanotechnology: International developments and emerging products. CIRP Annals, 49(2), 523–545
Cui, P., Shi, Z. Y., Li, X., & Duan, N. M. (2019). Evaluation of specific cutting energy considering effects of cutting tool geometry during micro-machining process. The International Journal of Advanced Manufacturing Technology, 102(5–8), 1127–1139
Dai, H., Chen, G., Zhou, C., Fang, Q., & Fei, X. (2017). A numerical study of ultraprecision machining of monocrystalline silicon with laser nano-structured diamond tools by atomistic simulation. Applied Surface Science, 393, 405–416
Franco, A., Rashed, C. A. A., & Romoli, L. (2016). Analysis of energy consumption in micro-drilling processes. Journal of Cleaner Production, 137, 1260–1269
Guo, X., Li, Q., Liu, T., Kang, R., Jin, Z., & Guo, D. (2017). Advances in molecular dynamics simulation of ultra-precision machining of hard and brittle materials. Frontiers of Mechanical Engineering, 12(1), 89–98
Huang, R., Zhang, X., Neo, W. K., Kumar, A. S., & Liu, K. (2018). Ultra-precision machining of grayscale pixelated micro images on metal surface. Precision Engineering, 52, 211–220
Ikawa, N., Donaldson, R. R., Komanduri, R., König, W., McKeown, P. A., Moriwaki, T., & Stowers, I. F. (1991). Ultraprecision metal cutting-the past, the present and the future. CIRP Annals-Manufacturing Technology, 40(2), 587–594
Jovane, F., Westkämper, E., & Williams, D. (2008). The ManuFuture road: towards competitive and sustainable high-adding-value manufacturing. Springer.
Kakinuma, Y., Kidani, S., & Aoyama, T. (2012). Ultra-precision cryogenic machining of viscoelastic polymers. CIRP Annals, 61(1), 79–82
Kan, C., Cheng, C., & Yang, H. (2016). Heterogeneous recurrence monitoring of dynamic transients in ultraprecision machining processes. Journal of Manufacturing Systems, 41, 178–187
Kan, C., Yang, H., & Kumara, S. (2018). Parallel computing and network analytics for fast Industrial Internet-of-Things (IIoT) machine information processing and condition monitoring. Journal of Manufacturing Systems, 46, 282–293
Komanduri, R., & Raff, L. M. (2001). A review on the molecular dynamics simulation of machining at the atomic scale. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 215(12), 1639–1672
Kuila, P. D., & Melkote, S. (2020). Effect of minimum quantity lubrication and vortex tube cooling on laser-assisted micromilling of a difficult-to-cut steel. Proceedings of the Institution of Mechanical Engineers, Part b: Journal of Engineering Manufacture. https://doi.org/10.1177/0954405420911268
Kumar, K., Zindani, D., Kumari, N., & Davim, D. (2019). Micro and nano machining of engineering materials. Springer.
Liu, M., Ma, J., Lin, L., Ge, M., Wang, Q., & Liu, C. (2017). Intelligent assembly system for mechanical products and key technology based on internet of things. Journal of Intelligent Manufacturing, 28(2), 271–299
Liu, Y., Dillon, T., Yu, W., Rahayu, W., & Mostafa, F. (2020). Noise removal in the presence of significant anomalies for Industrial IoT sensor data in manufacturing. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2020.2981476
Machado, C. G., Winroth, M. P., & daSilva, E. H. D. (2020). Sustainable manufacturing in Industry 4.0: An emerging research agenda. International Journal of Production Research, 58(5), 1462–1484
Maher, M., Christiansen, H., & Fortanier, F. (2001). Growth, technology transfer and foreign direct investment. New Horizons and policy challenges for FDI in the 21st Century, OECD.
Marksberry, P. W. (2007). Micro-flood (MF) technology for sustainable manufacturing operations that are coolant less and occupationally friendly. Journal of Cleaner Production, 15(10), 958–971
Marrocco, V., Modica, F., Fassi, I., & Bianchi, G. (2017). Energetic consumption modeling of micro-EDM process. The International Journal of Advanced Manufacturing Technology, 93(5–8), 1843–1852
McKeown, P. A. (1987). The role of precision engineering in manufacturing of the future. CIRP Annals-Manufacturing Technology, 36(2), 495–501
Mia, M., Gupta, M. K., Singh, G., Królczyk, G., & Pimenov, D. Y. (2018). An approach to cleaner production for machining hardened steel using different cooling-lubrication conditions. Journal of Cleaner Production, 187, 1069–1081
Modica, F., Marrocco, V., Copani, G., & Fassi, I. (2011). Sustainable micro-manufacturing of micro-components via micro electrical discharge machining. Sustainability, 3(12), 2456–2469
Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127–182
Pan, W. C., Kondaiah, B., Ding, S. L., & Mo, J. (2013). Tool wear and surface integrity in end milling of Ti6Al4V with polycrystalline diamond tools. Advanced Materials Research, 820, 134–137
Park, K. T., Kang, Y. T., Yang, S. G., Zhao, W. B., Kang, Y. S., Im, S. J., et al. (2020). Cyber physical energy system for saving energy of the dyeing process with industrial Internet of Things and manufacturing big data. International Journal of Precision Engineering and Manufacturing-Green Technology, 7(1), 219–238
Pham, M.-Q., Yoon, H.-S., Khare, V., & Ahn, S.-H. (2014). Evaluation of ionic liquids as lubricants in micro milling-process capability and sustainability. Journal of Cleaner Production, 76, 167–173
Rahman, M. A., Rahman, M., & Kumar, A. S. (2017). Modelling of flow stress by correlating the material grain size and chip thickness in ultra-precision machining. International Journal of Machine Tools and Manufacture, 123, 57–75. https://doi.org/10.1016/j.ijmachtools.2017.08.001
Rahman, M. A., Rahman, M., & Kumar, A. S. (2018). Influence of relative tool sharpness (RTS) on different ultra-precision machining regimes of Mg alloy. The International Journal of Advanced Manufacturing Technology, 96(9), 3545–3563. https://doi.org/10.1007/s00170-018-1599-4
Rao, P., Bukkapatnam, S., Beyca, O., Kong, Z. J., & Komanduri, R. (2014). Real-time identification of incipient surface morphology variations in ultraprecision machining process. Journal of Manufacturing Science and Engineering. https://doi.org/10.1115/1.4026210
Rashid, A., Asif, F. M. A., Krajnik, P., & Nicolescu, C. M. (2013). Resource conservative manufacturing: An essential change in business and technology paradigm for sustainable manufacturing. Journal of Cleaner Production, 57, 166–177
Redelinghuys, A. J. H., Basson, A. H., & Kruger, K. (2019). A six-layer architecture for the digital twin: a manufacturing case study implementation. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-019-01516-6
Rosen, M. A., & Kishawy, H. A. (2012). Sustainable manufacturing and design: Concepts, practices and needs. Sustainability, 4(2), 154–174
Sadoi, Y. (2009). Japanese skill and knowledge transfer: The case of exporting high-precision production technology to China and Vietnam. Meijo Rons, 9(4), 39–50
Schneider, F., Das, J., Kirsch, B., Linke, B., & Aurich, J. C. (2019). Sustainability in ultra precision and micro machining: A review. International Journal of Precision Engineering and Manufacturing-Green Technology. https://doi.org/10.1007/s40684-019-00035-2
Shamsan, A., & Cheng, C. (2019). Intrinsic multiplex graph model detects incipient process drift in ultraprecision manufacturing. Journal of Manufacturing Systems, 50, 81–86
Shindo, R., & Nishiwaki, S. (2020). Latest machine tool structural design technology for ultra-precision machining. International Journal of Automation Technology, 14(2), 304–310
Shore, P., & Morantz, P. (2012). Ultra-precision: Enabling our future. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 370(1973), 3993–4014
Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry 4.0. Procedia Cirp, 40, 536–541
Suma, V. (2019). Towards sustainable industrialization using big data and internet of things. Journal of ISMAC, 1(01), 24–37
Tan, R., Zhao, X., Guo, S., Zou, X., He, Y., Geng, Y., Hu, Z., & Sun, T. (2019). Sustainable production of dry-ultra-precision machining of Ti-6Al-4V alloy using PCD tool under ultrasonic elliptical vibration-assisted cutting. Journal of Cleaner Production, 248, 119254
Tan, Y. S., Ng, Y. T., & Low, J. S. C. (2017). Internet-of-things enabled real-time monitoring of energy efficiency on manufacturing shop floors. Procedia CIRP, 61, 376–381
Vazquez, E., Gomar, J., Ciurana, J., & Rodríguez, C. A. (2015). Analyzing effects of cooling and lubrication conditions in micromilling of Ti6Al4V. Journal of Cleaner Production, 87, 906–913
Wang, J., & Huang, Z. (2017). The recent technological development of intelligent mining in China. Engineering, 3(4), 439–444
Wu, X., Li, L., He, N., Zhao, G., Jiang, F., & Shen, J. (2018). Study on the tool wear and its effect of PCD tool in micro milling of tungsten carbide. International Journal of Refractory Metals and Hard Materials, 77, 61–67
Yan, J., Syoji, K., & Tamaki, J. (2003). Some observations on the wear of diamond tools in ultra-precision cutting of single-crystal silicon. Wear, 255(7–12), 1380–1387
Yao, X., Zhou, J., Lin, Y., Li, Y., Yu, H., & Liu, Y. (2019). Smart manufacturing based on cyber-physical systems and beyond. Journal of Intelligent Manufacturing, 30(8), 2805–2817
Yi, H. (2020). Systolic inversion algorithms for building cryptographic systems based on security measurement in IoT-based advanced manufacturing. Measurement, 161, 107827
Yip, W. S., & To, S. (2017). Tool life enhancement in dry diamond turning of titanium alloys using an eddy current damping and a magnetic field for sustainable manufacturing. Journal of Cleaner Production, 168, 929–939
Yip, W. S., & To, S. (2018). Sustainable manufacturing of ultra-precision machining of titanium alloys using a magnetic field and its sustainability assessment. Sustainable Materials and Technologies, 16, 38–46
Yip, W. S., To, S., & Zhou, H. (2020). Social network analysis for optimal machining conditions in ultra-precision manufacturing. Journal of Manufacturing Systems, 56, 93–103
Yoon, H. S., Lee, J. Y., Kim, M. S., & Ahn, S. H. (2014). Empirical power-consumption model for material removal in three-axis milling. Journal of Cleaner Production, 78, 54–62
Yuan, J., Lyu, B., Hang, W., & Deng, Q. (2017). Review on the progress of ultra-precision machining technologies. Frontiers of Mechanical Engineering, 12(2), 158–180
Zhang, J., Ding, G., Zou, Y., Qin, S., & Fu, J. (2019). Review of job shop scheduling research and its new perspectives under Industry 4.0. Journal of Intelligent Manufacturing, 30(4), 1809–1830
Zhang, S. J., To, S., Wang, S. J., & Zhu, Z. W. (2015). A review of surface roughness generation in ultra-precision machining. International Journal of Machine Tools and Manufacture, 91, 76–95
Zhang, Y., Zhang, G., Liu, Y., & Hu, D. (2017). Research on services encapsulation and virtualization access model of machine for cloud manufacturing. Journal of Intelligent Manufacturing, 28(5), 1109–1123
Zheng, P., Xu, X., & Chen, C. H. (2020). A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment. Journal of Intelligent Manufacturing, 31(1), 3–18
Zou, L., Huang, Y., Zhou, M., & Yang, Y. (2018). Effect of cryogenic minimum quantity lubrication on machinability of diamond tool in ultraprecision turning of 3Cr2NiMo steel. Materials and Manufacturing Processes, 33(9), 943–949
Funding
The work described in this paper was supported by the funding support to the State Key Laboratories in Hong Kong from the Innovation and Technology Commission (ITC) of the Government of the Hong Kong Special Administrative Region (HKSAR), China. The authors would also like to express their sincere thanks for the financial support from the Research Office (Project code: BBXM and BBX) of The Hong Kong Polytechnic University, and, the Research Committee of The Hong Kong Polytechnic University under project code: B-Q57Z.
Author information
Authors and Affiliations
Contributions
WSY: Conceptualization, methodology, writing, review, editing. ST: Supervision, conceptualization, resources. writing, review, editing. HZ: Conceptualization, writing, review, editing.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that there are no conflicts of interest.
Ethical approval
This work does not contain any ethical issues or personal information.
Consent to participate
No human or animal was involved in this work; thus, no consent was required.
Consent for publication
All authors have given their permission for publishing this work.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Yip, W.S., To, S. & Zhou, H. Current status, challenges and opportunities of sustainable ultra-precision manufacturing. J Intell Manuf 33, 2193–2205 (2022). https://doi.org/10.1007/s10845-021-01782-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-021-01782-3