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Additive Manufacturing in Industry 4.0: A Review

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Recent Trends in Mechanical Engineering

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Abstract

Additive manufacturing is one of the imperative components in the Industry 4.0 framework. It is widely used in concurrent engineering for effective product development and many other vital domains. Extensive research is being carried out in a continuum of Industry 4.0 fields, namely Internet of things, cloud computing, cybersecurity, autonomous robotics, big data, simulation, and augmented reality. AM has a crucial impact in these fields. This review paper provides a comprehensive study in various spheres of additive manufacturing and Industry 4.0. This research also provides a profound inter-association of these systems in the domain of product development and optimization of process parameters, which can be later employed in biomedical, aerospace, and construction applications. The exploration would foster a crucial review of the subject and reveal the matter to understand the future latitude in the domain. The study embraces the amalgamation of various ecosystems in Industry 4.0 and frameworks to substantially affect the research and development in numerous industries. This review study will support industries to keep themselves alongside the advancements in additive manufacturing and Industry 4.0.

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References

  1. Vinodh S, Wankhede VA (2020) Application of fuzzy DEMATEL and fuzzy CODAS for analysis of workforce attributes pertaining to Industry 4.0: a case study. Int J Qual Reliab Manag. https://doi.org/10.1108/IJQRM-09-2020-0322

  2. Qi X, Chen G, Li Y, Cheng X, Li C (2019) Applying neural-network-based machine learning to additive manufacturing : current applications, challenges, and future perspectives. Engineering 5(4):721–729. https://doi.org/10.1016/j.eng.2019.04.012

    Article  Google Scholar 

  3. Labeaga-Martínez MN, Sanjurjo-Rivo JD-Á, Martínez-Frías J (2017) Additive manufacturing for a Moon village Additive manufacturing for a Moon village. Procedia Manuf 13:794–801. https://doi.org/10.1016/j.promfg.2017.09.186

    Article  Google Scholar 

  4. Paszkiewicz A, Bolanowski M, Budzik G, Sowa P (2020) Applied sciences remote design and manufacture through the example of a ventilator

    Google Scholar 

  5. Kim KM, Bang IC (2020) Design and operation of the transparent integral effect test facility, URI-LO for nuclear innovation platform. Nucl Eng Technol. https://doi.org/10.1016/j.net.2020.08.006

  6. Pan H, Yang X (2019) Application of Internet of Things technology in 3D medical image model. IEEE Access 7:5508–5518. https://doi.org/10.1109/ACCESS.2018.2886223

    Article  Google Scholar 

  7. Dilberoglu UM, Gharehpapagh B, Yaman U, Dolen M (2017) The role of additive manufacturing in the era of Industry 4. 0. Procedia Manuf 11(June):545–554. https://doi.org/10.1016/j.promfg.2017.07.148

    Article  Google Scholar 

  8. Mehrpouya M, Dehghanghadikolaei A, Fotovvati B, Vosooghnia A, Emamian SS, Gisario A (2019) The potential of additive manufacturing in the smart. Appl Sci:34

    Google Scholar 

  9. Lidong W, Guanghui W (2016) Big data in cyber-physical systems, digital manufacturing and industry 4.0. Int J Eng Manuf 6(4):1–8. https://doi.org/10.5815/ijem.2016.04.01

    Article  Google Scholar 

  10. Guo L, Qiu J (2018) Combination of cloud manufacturing and 3D printing : research progress and prospect

    Google Scholar 

  11. Mai J, Zhang L, Tao F, Ren L (2015) Customized production based on distributed 3D printing services in cloud manufacturing. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-015-7871-y

    Article  Google Scholar 

  12. Khan Z, Kahin K, Rauf S, Ramirez-Calderon G, Papagiannis N, Abdulmajid M, Hauser C (2019) Optimization of a 3D bioprinting process using ultrashort peptide bioinks. Int J Bioprint 5(1):3–6. https://doi.org/10.18063/ijb.v5i1.173

    Article  Google Scholar 

  13. Tan K (2018) The framework of combining artificial intelligence and construction 3D printing in civil engineering. MATEC Web Conf 206:1–5. https://doi.org/10.1051/matecconf/201820601008

    Article  Google Scholar 

  14. Nee AYC, Ong SK, Chryssolouris G, Mourtzis D (2012) CIRP annals—Manufacturing technology augmented reality applications in design and manufacturing. CIRP Ann Manuf Technol 61(2):657–679. https://doi.org/10.1016/j.cirp.2012.05.010

    Article  Google Scholar 

  15. Zhang Y, Kwok TH (2018) Design and interaction interface using augmented reality for smart manufacturing. Procedia Manuf 26:1278–1286. https://doi.org/10.1016/j.promfg.2018.07.140

    Article  Google Scholar 

  16. Ceruti A, Marzocca P, Liverani A, Bil C (2019) Maintenance in aeronautics in an Industry 4.0 context: the role of augmented reality and additive manufacturing. J Comput Des Eng 6(4):516–526. https://doi.org/10.1016/j.jcde.2019.02.001

    Article  Google Scholar 

  17. Pence HE (2020) Education sciences how should chemistry educators respond to the next generation of technology change?

    Google Scholar 

  18. Liao Y, Rocha E, Deschamps F, Brezinski G (2018) The impact of the fourth industrial revolution: a cross-country/region comparison. Production 5411:18. https://doi.org/10.1590/0103-6513.20180061

    Article  Google Scholar 

  19. Anand P, Nagendra A (2019) Industry 4.0: India’s defence industry needs smart manufacturing. Int J Innov Technol Explor Eng 8(11) Special Issue:476–485. https://doi.org/10.35940/ijitee.K1081.09811S19

  20. Goguelin S, Colaco J, Dhokia V, Schaefer D (2017) Smart manufacturability analysis for digital product development. Procedia CIRP 60:56–61. https://doi.org/10.1016/j.procir.2017.02.026

    Article  Google Scholar 

  21. Bilal M, Sanin C, Szczerbicki E, Ahmed MB, Sanin C, Szczerbicki E (2019) ScienceDirect Smart Virtual Product Development (SVPD) to Enhance Product Smart Virtual Product Development (SVPD) to enhance product manufacturing in industry 4. 0 manufacturing in industry 4. 0. Procedia Comput Sci 159(2018):2232–2239. https://doi.org/10.1016/j.procs.2019.09.398

    Article  Google Scholar 

  22. Rodriguez-Conde I, Campos C (2020) Towards customer-centric additive manufacturing: making human-centered 3d design tools through a handheld-based multi-touch user interface. Sensors (Switzerland) 20(15):1–28. https://doi.org/10.3390/s20154255

    Article  Google Scholar 

  23. Goh GD, Sing SL, Yeong WY (2020) Potential, and challenges, 0123456789. Springer Netherlands

    Google Scholar 

  24. Zhang Y et al (2020) A parametric study of 3D printed polymer gears, pp 4481–4492

    Google Scholar 

  25. Snell R et al (2020) Methods for rapid pore classification in metal additive manufacturing. JOM 72(1):101–109. https://doi.org/10.1007/s11837-019-03761-9

    Article  Google Scholar 

  26. Wankhede V, Jagetiya D, Joshi, Chaudhari R (2019) Experimental investigation of FDM process parameters using Taguchi analysis. Mater Today Proc 27:2117–2120. https://doi.org/10.1016/j.matpr.2019.09.078

  27. Soni H, Gor M, Rajput G, Sahlot P (2021) Thermal modeling of laser powder-based additive manufacturing process. In: Mathematical modeling, computational intelligence techniques and renewable energy. Advances in Intelligent Systems and Computing, pp 1–8

    Google Scholar 

  28. Baturynska I, Martinsen K (2021) Prediction of geometry deviations in additive manufactured parts: comparison of linear regression with machine learning algorithms. J Intell Manuf 32(1):179–200. https://doi.org/10.1007/s10845-020-01567-0

    Article  Google Scholar 

  29. Godina R, Ribeiro I, Matos F, Ferreira BT, Carvalho H, Peças P (2020) Impact assessment of additive manufacturing on sustainable business models in industry 4.0 context. Sustain 12(17):1–21. https://doi.org/10.3390/su12177066

    Article  Google Scholar 

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Correspondence to Pankaj Sahlot .

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Srivastava, P., Sahlot, P. (2023). Additive Manufacturing in Industry 4.0: A Review. In: Maurya, A., Srivastava, A.K., Jha, P.K., Pandey, S.M. (eds) Recent Trends in Mechanical Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-7709-1_29

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  • DOI: https://doi.org/10.1007/978-981-19-7709-1_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-7708-4

  • Online ISBN: 978-981-19-7709-1

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