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Readiness of subtractive and additive manufacturing and their sustainable amalgamation from the perspective of Industry 4.0: a comprehensive review

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Abstract

The successful realization of Industry 4.0 depends much on how coherently the cyber and physical realms are conjoined in cyber-physical systems. In the context of the fourth industrial revolution, research efforts have mostly been channeled toward the cyber domain, whereas the physical domain has received significantly lesser consideration. A physical domain generally comprises material shaping equipment, work material, tools, working medium, sensors, automation technology, and connectivity mechanisms. The article provides a comprehensive review of the published literature to establish the states of readiness of the two most important manufacturing technologies: subtractive and additive and their sustainable merger from the perspective of Industry 4.0. Rich potentials in the four characteristics at the process level: speed, sustainability, agility, and customer centricity and three at the system level: connectivity, data collection, and automation are required for a manufacturing system (physical domain) to be Industry 4.0 compatible. The review establishes that the subtractive manufacturing domain is nearly compatible regarding speed and agility but needs improvements in respect of sustainability and customer centricity. Additive manufacturing, on the other hand, appears strong on agility and customer-centricity fronts but needs amelioration regarding production speed and sustainability. In respect of the system level characteristics, both technologies seem to be compatible regarding automation, whereas significant improvements are required in connectivity and data sensing and collection. For the sake of raising compatibility levels of the manufacturing systems, subtractive-additive amalgamation is scrutinized. The amalgamation, especially in a done-in-one configuration, has, reportedly, succeeded to retain the favorable traits of the two manufacturing technologies, thus, bringing the merger much closer to the Industry 4.0 requirements. Proper process planning and optimal work distribution between the subtractive and additive modes are critical for operating an amalgamated system at high levels of the key characteristics.

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References

  1. Riel A, Kreiner C, Macher G, Messnarz R (2017) Integrated design for tackling safety and security challenges of smart products and digital manufacturing. CIRP Ann Manuf Technol 66(1):177–180. https://doi.org/10.1016/j.cirp.2017.04.037

    Article  Google Scholar 

  2. Chen D, Heyer S, Ibbotson S, Salonitis K, Steingrímsson JG, Thiede S (2015) Direct digital manufacturing: definition, evolution, and sustainability implications. J Clean Prod 107:615–625. https://doi.org/10.1016/j.jclepro.2015.05.009

    Article  Google Scholar 

  3. Beyond the vision: realizing the promise of Industry 4.0. Cognizant (July 2019). https://www.cognizant.com/whitepapers/beyond-the-vision-realizing-the-promise-of-industry-4-codex4719.pdf. Accessed 17 December 2019

  4. Alcácer V, Cruz-Machado V (2019) Scanning the industry 4.0: a literature review on technologies for manufacturing systems. Eng Sci Technol Int J 22:899–919. https://doi.org/10.1016/j.jestch.2019.01.006

    Article  Google Scholar 

  5. Schieberl J, Nickles M (2014) Outsourcing US jobs abroad: why? Int Bus Econ Res J 13(2):253. https://doi.org/10.19030/iber.v13i2.8439

    Article  Google Scholar 

  6. Michael B, Michael R (2012) Outsourcing: mass layoffs and displaced workers’ experiences. Manag Res Rev 35(11):1029–1045. https://doi.org/10.1108/01409171211276927

    Article  Google Scholar 

  7. Bals L, Kirchoff JF, Foerstl K (2016) Exploring the reshoring and insourcing decision making process: toward an agenda for future research. Oper Manag Res 9(3–4):102–116. https://doi.org/10.1007/s12063-016-0113-0

    Article  Google Scholar 

  8. Müller J, Dotzauer V, Voigt KI (2017) Industry 4.0 and its impact on reshoring decisions of German manufacturing enterprises. In: Bode C, Bogaschewsky R, Eßig M, Lasch R, Stölzle W (eds) Supply management research. Advanced studies in supply management. Springer Gabler, Wiesbaden, pp 165–179. https://doi.org/10.1007/978-3-658-18632-6_8

    Chapter  Google Scholar 

  9. Zhou J, Li P, Zhou Y, Wang B, Zang J, Meng L (2018) Toward new-generation intelligent manufacturing. Engineering 4(1):11–20. https://doi.org/10.1016/j.eng.2018.01.002

    Article  Google Scholar 

  10. Kusiak A (2018) Smart manufacturing. Int J Prod Res 56(1–2):508–517. https://doi.org/10.1080/00207543.2017.1351644

    Article  Google Scholar 

  11. Dilberoglu UM, Gharehpapagh B, Yaman U, Dolen M (2017) The role of additive manufacturing in the era of industry 4.0. Proc Manuf 11:545–554. https://doi.org/10.1016/j.promfg.2017.07.148

    Article  Google Scholar 

  12. Federal Ministry of Education and Research, Germany. Industrie 4.0. https://www.bmbf.de/de/zukunftsprojekt-industrie-4-0-848.html. Accessed 18 December, 2019

  13. Liao Y, Deschamps F, Loures ED, Ramos LF (2017) Past, present and future of Industry 4.0-a systematic literature review and research agenda proposal. Int J Prod Res 55(12):3609–3629. https://doi.org/10.1080/00207543.2017.1308576

    Article  Google Scholar 

  14. Earls A. From Germany to the world: Industry 4.0; Smart Industry Forum https://www.smartindustry.com/blog/smart-industry-connect/from-germany-to-the-world-industry-4-0/. Accessed 18 December, 2019

  15. Federal Ministry of Labor and Social Affairs of Germany (2015) Re-Imagining Work: White Paper Work 4.0

  16. Mittelmann A (2018) Competence development for work 4.0. In: North K, Maier R, Haas O (eds) Knowledge management in digital change. Progress in IS. Springer, Cham, pp 263–275

    Google Scholar 

  17. Kagermann H, Lukas W, Wahlster W (2011) Industry 4.0: Mit dem Internet der Dinge auf dem Weg zur 4. Industryllen Revolution. VDI nachrichten 13(1):1090–1100

  18. Kagermann H, Wahlster W, Helbig J (2013) Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0 – Abschlussbericht des Arbeitskreises Industrie 4.0. Acatech: National Academy of Science & Engineering, Germany

  19. Davis J, Edgar T, Porter J, Bernaden J, Sarli M (2012) Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Comput Chem Eng 47:145–156. https://doi.org/10.1016/j.compchemeng.2012.06.037

    Article  Google Scholar 

  20. Kiel D, Müller JM, Arnold C, Voigt KI (2017) Sustainable industrial value creation: benefits and challenges of industry 4.0. Int J Innov Manag 21(08):1740015. https://doi.org/10.1142/S1363919617400151

    Article  Google Scholar 

  21. Monostori L, Csáji BC, Kádár B, Pfeiffer A, Ilie-Zudor E, Kemény Z, Szathmári M (2010) Towards adaptive and digital manufacturing. Annu Rev Control 34(1):118–128. https://doi.org/10.1016/j.arcontrol.2010.02.007

    Article  Google Scholar 

  22. Zhong RY, Xu X, Klotz E, Newman ST (2017) Intelligent manufacturing in the context of Industry 4.0: a review. Engineering 3(5):616–630. https://doi.org/10.1016/J.ENG.2017.05.015

    Article  Google Scholar 

  23. Bauernhansl PDT, Diegner B, Diemer J, Dümmler M, Eckert C, Herfs W, Kalhoff J (2014) Industrie 4.0. Whitepaper FuE - Themen der Plattform Industrie. http://www.zvei.org/Downloads/Automation/Whitepaper-I40-FuE-Themen-2015-04.pdf

  24. Stock T, Seliger G (2016) Opportunities of sustainable manufacturing in industry 4.0. Proc CIRP 40:536–541. https://doi.org/10.1016/j.procir.2016.01.129

    Article  Google Scholar 

  25. Promises and constraints around Industry 4.0 revolution; Prophetic Technologies. https://blog.prophetic-technology.com/promises-and-constraints-around-industry-4.0-revolution. Accessed 22 Dec 2019

  26. Milovanović G, Milovanović S, Radisavljević G (2017) Globalization: the key challenge of modern supply chains. Ekonomika. 63(1):31–40

    Article  Google Scholar 

  27. Davis N, O’Halloran D. The fourth industrial revolution is driving globalization 4.0. World Economic Forum; https://www.weforum.org/agenda/2018/11/the-fourth-industrial-revolution-is-driving-a-new-phase-of-globalization/. Accessed 23 December 2019

  28. Gubán M, Kovács G (2017) Industry 4.0 conception. Acta Technica Corviniensis Bull Eng 10(1):111–114

    Google Scholar 

  29. Pearsall K. Manufacturing supply chain challenges-globalization and IOT. In: 6th Electronic System-Integration Technology Conference (ESTC) 2016 Sep 13 (pp. 1-5). IEEE. https://doi.org/10.1109/ESTC.2016.7764487

  30. Khurana A, Geissbauer R, Arora J. Industry 4.0 is accelerating globalisation, but with a distinctly regional flavor; PWC Middle East. https://www.pwc.com/m1/en/publications/industry-40-survey/globalisation-distinctly-regional-flavour.html. Accessed 23 December 2019

  31. Lee MX, Lee YC, Chou CJ (2017) Essential implications of the digital transformation in industry 4.0. J Sci Ind Res 76(08):465–467 http://nopr.niscair.res.in/handle/123456789/42548

    Google Scholar 

  32. Schwab K. Globalization 4.0–what does it mean? World Economic Forum 2019. https://www.weforum.org/agenda/2018/11/globalization-4-what-does-it-mean-how-it-will-benefit-everyone/. Accessed 23 December 2019

  33. Johnson DG (2002) Globalization: what it is and who benefits. J Asian Econ 13(4):427–439. https://doi.org/10.1016/S1049-0078(02)00162-8

    Article  Google Scholar 

  34. Stearns PN (2016) Globalization in world history, 2nd edn. Routledge, New York

    Book  Google Scholar 

  35. Collins M. The pros and cons of globalization. Forbes. https://www.forbes.com/sites/mikecollins/2015/05/06/the-pros-and-cons-of-globalization/#6be27cc2ccce. Accessed 23 December 2019

  36. Sustainable Development Goals; United Nations. https://sustainabledevelopment.un.org/?menu=1300. Accessed 23 December 2019

  37. Sachs J, Schmidt-Traub G, Kroll C, Lafortune G, Fuller G (2019) Sustainable development report 2019. Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN), New York

    Google Scholar 

  38. Stock T, Obenaus M, Kunz S, Kohl H (2018) Industry 4.0 as enabler for a sustainable development: a qualitative assessment of its ecological and social potential. Proc Saf Environ Prot 118:254–267. https://doi.org/10.1016/j.psep.2018.06.026

    Article  Google Scholar 

  39. Papyshev GD (2017) Impact of Industry 4. 0 on sustainable development. Международный журнал гуманитарных и естественных наук. Int J Hum Nat Sci 7. https://cyberleninka.ru/article/n/impact-of-industry-4-0-on-sustainable-development

  40. Bonilla SH, Silva HR, Terra da Silva M, Franco Gonçalves R, Sacomano JB (2018) Industry 4.0 and sustainability implications: a scenario-based analysis of the impacts and challenges. Sustainability 10(10):3740. https://doi.org/10.3390/su10103740

    Article  Google Scholar 

  41. Tsvetkova R (2017) What does Industry 4.0 mean for sustainable development? Industry 4.0. 2(6):294–297

    Google Scholar 

  42. The United Nations Development Programme (2018) Development 4.0: Opportunities and challenges for accelerating progress towards the sustainable development goals in Asia and the Pacific. https://www.asia-pacific.undp.org/content/rbap/en/home/library/sustainable-development/Asia-Pacific-Development-40.html

  43. de Sousa Jabbour AB, Jabbour CJ, Godinho Filho M, Roubaud D (2018) Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Ann Oper Res 270(1–2):273–286. https://doi.org/10.1007/s10479-018-2772-8

    Article  MATH  Google Scholar 

  44. Zawadzki P, Żywicki K (2016) Smart product design and production control for effective mass customization in the Industry 4.0 concept. Man Prod Eng Rev 7(3):105–112. https://doi.org/10.1515/mper-2016-0030

    Article  Google Scholar 

  45. Murphie C. How Industry 4.0 supports flexibility and mass customization; SL Controls; https://slcontrols.com/how-industry-4-0-supports-flexibility-and-mass-customisation/. Accessed 3 January 2020

  46. Wang Y, Ma HS, Yang JH, Wang KS (2017) Industry 4.0: a way from mass customization to mass personalization production. Adv Manuf 5(4):311–320. https://doi.org/10.1007/s40436-017-0204-7

    Article  Google Scholar 

  47. Karaköse M, Yetiş H (2017) A cyberphysical system based mass-customization approach with integration of Industry 4.0 and smart city. Wirel Commun Mob Comput. https://doi.org/10.1155/2017/1058081

  48. Armengaud E, Sams C, Von Falck G, List G, Kreiner C, Riel A (2017) Industry 4.0 as digitalization over the entire product lifecycle: opportunities in the automotive domain. In: European Conference on Software Process Improvement 2017 Sep 6, pp 334-351. Springer, Cham. https://doi.org/10.1007/978-3-319-64218-5_28

  49. Chhetri SR, Faezi S, Rashid N, Al Faruque MA (2018) Manufacturing supply chain and product lifecycle security in the era of industry 4.0. J Hardware Syst Sec 2(1):51–68. https://doi.org/10.1007/s41635-017-0031-0

    Article  Google Scholar 

  50. Ferreira FD, Faria J, Azevedo A, Marques AL (2016) Product lifecycle management enabled by Industry 4.0 technology. INESCTEC Documents Repository. https://repositorio.inesctec.pt/handle/123456789/6854. Accessed 15 February 2020

  51. Qi Q, Tao F (2018) Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. IEEE Access 6:3585–3593. https://doi.org/10.1109/ACCESS.2018.2793265

    Article  Google Scholar 

  52. Olsen TL, Tomlin B (2020) Industry 4.0: opportunities and challenges for operations management. Manuf Serv Oper Manag 22(1):113–122. https://doi.org/10.1287/msom.2019.0796

    Article  Google Scholar 

  53. Aheleroff S, Xu X, Lu Y, Aristizabal M, Velásquez JP, Joa B, Valencia Y (2020) IoT-enabled smart appliances under industry 4.0: a case study. Adv Eng Inf 43:101043. https://doi.org/10.1016/j.aei.2020.101043

    Article  Google Scholar 

  54. Majstorovic VD, Durakbasa NM, Mourtzis D, Vlachou E (2016) Cloud-based cyber-physical systems and quality of services. TQM J 28(5):704–733. https://doi.org/10.1108/TQM-10-2015-0133

    Article  Google Scholar 

  55. Belli L, Davoli L, Medioli A, Marchini PL, Ferrari G (2019) Towards industry 4.0 with IoT: optimizing business processes in an evolving manufacturing factory. Front ICT 6:17. https://doi.org/10.3389/fict.2019.00017

    Article  Google Scholar 

  56. Gering P, Drange P (2019) Industry 4.0 out of the box. In: Enterprise Interoperability VIII. Proc I-ESA Conf 9:45–53. Springer, Cham. https://doi.org/10.1007/978-3-030-13693-2_4

  57. Brettel M, Friederichsen N, Keller M, Rosenberg M (2014) How virtualization, decentralization and network building change the manufacturing landscape: an Industry 4.0 perspective. Int J Mech Aerospace Ind Mechatron Manuf Eng 8(1):37–44

    Google Scholar 

  58. Popkova EG, Zmiyak KV (2019) Priorities of training of digital personnel for industry 4.0: social competencies vs technical competencies. Horizon 27(3/4):138–144. https://doi.org/10.1108/OTH-08-2019-0058

    Article  Google Scholar 

  59. Bautista-Moncada C, Buhangin JF, Angalan NQ (2020) Review of industry 4.0 competencies and virtual learning environment in engineering education. Int J Eng Educ 36(1A):40–47

    Google Scholar 

  60. Low SP, Gao S, Ng EW (2019) Future-ready project and facility management graduates in Singapore for industry 4.0. Eng Constr Archit Manag. https://doi.org/10.1108/ECAM-08-2018-0322

  61. Queiruga-Dios A, Bullón Pérez J, Hernández Encinas A, Rodríguez Sánchez G, Martín Rey A, Martín-Vaquero J (2017) Case study: engineering education, Industry 4.0, security, and competencies-based assessment. Proceedings of the 45th SEFI Annual Conference 2017 - Education Excellence for Sustainability, p 1410–1416

  62. Bermúdez MD, Juárez BF (2017) Competencies to adopt Industry 4.0 for operations management personnel at automotive parts suppliers in Nuevo Leon. In: Proceedings of the International Conference on Industrial Engineering and Operations Management, Bogota, Columbia, p 736–747

  63. Longo F, Nicoletti L, Padovano A (2017) Smart operators in industry 4.0: a human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Comp Ind Eng 113:144–159. https://doi.org/10.1016/j.cie.2017.09.016

    Article  Google Scholar 

  64. Boothroyd G, Knight WA (2006) Fundamentals of machining and machine tools, 3rd edn. CRC Press, Boca Raton

  65. Shaw MC, Cookson JO (2005) Metal cutting principles. Oxford university press, New York

    Google Scholar 

  66. Rao RV (2011) Modeling and optimization of modern machining processes. In: Advanced modeling and optimization of manufacturing processes: Springer series in Advanced Manufacturing. Springer-Verlag London Ltd, pp 177–284

  67. Trent EM, Wright PK (2000) Metal cutting, 4th edn Butterworth-Heinemann, Woburn

  68. Fortune Business Insights. Machining centers market size, share & industry analysis, by product (vertical machining center, horizontal machining center, others), by application (automotive, general machinery, precision machinery, transport machinery, others) and regional forecast, 2019–2026. Report ID.: FBI101770, Dec. 2019. https://www.fortunebusinessinsights.com/industry-reports/machining-centers-market-101770. Accessed 25 February 2020

  69. Kim YS, Wang E (2002) Recognition of machining features for cast then machined parts. Comput Aided Des 34(1):71–87. https://doi.org/10.1016/S0010-4485(01)00058-6

    Article  Google Scholar 

  70. Paul S, Chattopadhyay AB (2006) Environmentally conscious machining and grinding with cryogenic cooling. Mach Sci Technol 10(1):87–131. https://doi.org/10.1080/10910340500534316

    Article  Google Scholar 

  71. Benedict GF (2017) Nontraditional manufacturing processes. CRC Press, Boca Raton. https://doi.org/10.1201/9780203745410

  72. Gao S, Huang H (2017) Recent advances in micro-and nano-machining technologies. Front Mech Eng 12(1):18–32. https://doi.org/10.1007/s11465-017-0410-9

    Article  MathSciNet  Google Scholar 

  73. Woronko A, Huang J, Altintas Y (2003) Piezoelectric tool actuator for precision machining on conventional CNC turning centers. Precis Eng 27(4):335–345. https://doi.org/10.1016/S0141-6359(03)00040-0

    Article  Google Scholar 

  74. Mecomber JS, Hurd D, Limbach PA (2005) Enhanced machining of micron-scale features in microchip molding masters by CNC milling. Int J Mach Tools Manuf 45(12–13):1542–1550. https://doi.org/10.1016/j.ijmachtools.2005.01.016

    Article  Google Scholar 

  75. Fitzpatrick M (2019) Machining and CNC technology, 4th edn. McGraw-Hill Education, New York

  76. Sudo M (2007) Advanced control technologies for 5-axis machining. Int J Autom Technol 1(2):108–112

    Article  Google Scholar 

  77. Yang P, Ye SW, Peng YF (2017) Three-dimensional profile stitching measurement for large aspheric surface during grinding process with sub-micron accuracy. Precis Eng 47:62–71. https://doi.org/10.1016/j.precisioneng.2016.07.005

    Article  Google Scholar 

  78. Egashira K, Kumagai R, Okina R, Yamaguchi K, Ota M (2014) Drilling of microholes down to 10 μm in diameter using ultrasonic grinding. Precis Eng 38(3):605–610. https://doi.org/10.1016/j.precisioneng.2014.02.010

    Article  Google Scholar 

  79. Lee BE, Exir H, Weck A, Grandfield K (2018) Characterization and evaluation of femtosecond laser-induced sub-micron periodic structures generated on titanium to improve osseointegration of implants. App Surf Sci 441:1034–1042. https://doi.org/10.1016/j.apsusc.2018.02.119

    Article  Google Scholar 

  80. Black JT, Kohser RA (2019) DeGarmo’s materials and processes in manufacturing, 13th edn. Wiley Publishing, Hoboken

  81. Schneider G (2009) Cutting tool applications. In: Machinability of metals. American Machinist. https://www.americanmachinist.com/cutting-tools/media-gallery/21895130/chapter-3-machinability-of-metals-cutting-tool-applications

  82. Ezugwu EO, Bonney J, Yamane Y (2003) An overview of the machinability of aeroengine alloys. J Mater Process Technol 134(2):233–253. https://doi.org/10.1016/S0924-0136(02)01042-7

    Article  Google Scholar 

  83. Keresztes R, Kalácska G, Zsidai L, Dobrocsi Z (2011) Machinability of engineering polymers. Sustaain Construct Des 2(1):106

    Google Scholar 

  84. Karataş MA, Gökkaya H (2018) A review on machinability of carbon fiber reinforced polymer (CFRP) and glass fiber reinforced polymer (GFRP) composite materials. Def Technol 14(4):318–326. https://doi.org/10.1016/j.dt.2018.02.001

    Article  Google Scholar 

  85. Iqbal A, Dar NU, He N, Khan I, Li L (2009) Optimizing cutting parameters in minimum quantity of lubrication milling of hardened cold work tool steel. Proc Inst Mech Eng B J Eng Manuf 223(1):43–54. https://doi.org/10.1243/09544054JEM1231

    Article  Google Scholar 

  86. Axinte DA, Dewes RC (2002) Surface integrity of hot work tool steel after high speed milling-experimental data and empirical models. J Mater Process Technol 127(3):325–335. https://doi.org/10.1016/S0924-0136(02)00282-0

    Article  Google Scholar 

  87. Cheng C, Wang Z, Hung W, Bukkapatnam ST, Komanduri R (2015) Ultra-precision machining process dynamics and surface quality monitoring. Process Manuf 1:607–618. https://doi.org/10.1016/j.promfg.2015.09.044

    Article  Google Scholar 

  88. Brinksmeier E, Mutlugünes Y, Klocke F, Aurich JC, Shore P, Ohmori H (2010) Ultra-precision grinding. CIRP Ann 59(2):652–671. https://doi.org/10.1016/j.cirp.2010.05.001

    Article  Google Scholar 

  89. Stephenson DJ, Veselovac D, Manley S, Corbett J (2001) Ultra-precision grinding of hard steels. Precis Eng 25(4):336–345. https://doi.org/10.1016/S0141-6359(01)00087-3

    Article  Google Scholar 

  90. Evans J, Paul E, Dornfeld D, Lucca D, Byrne G, Tricard M, Klocke F, Dambon O, Mullany B (2003) Material removal mechanisms in lapping and polishing, STC “G” keynote. CIRP Ann 52(2):611–633

    Article  Google Scholar 

  91. Saraswathamma K (2014) Magnetorheological finishing: a review. Int J Curr Eng Technol (Special Issue-2). https://doi.org/10.14741/ijcet/spl.2.2014.30

  92. Venkatakrishnan K, Tan B, Sivakumar NR (2002) Sub-micron ablation of metallic thin film by femtosecond pulse laser. Opt Laser Technol 34(7):575–578. https://doi.org/10.1016/S0030-3992(02)00074-9

    Article  Google Scholar 

  93. Karimi S, Mehrdel P, Casals-Terré J, Farré-Llados J (2020) Cost-effective microfabrication of sub-micron-depth channels by femto-laser anti-stiction texturing. Biofabrication. 12(2):025021. https://doi.org/10.1088/1758-5090/ab6665

    Article  Google Scholar 

  94. Nasrollahi V, Penchev P, Jwad T, Dimov S, Kim K, Im C (2018) Drilling of micron-scale high aspect ratio holes with ultra-short pulsed lasers: critical effects of focusing lenses and fluence on the resulting holes’ morphology. Opt Lasers Eng 110:315–322. https://doi.org/10.1016/j.optlaseng.2018.04.024

    Article  Google Scholar 

  95. Mourtzis D, Vlachou E, Milas N, Xanthopoulos N (2016) A cloud-based approach for maintenance of machine tools and equipment based on shop-floor monitoring. Proc CIRP 41:655–660. https://doi.org/10.1016/j.procir.2015.12.069

    Article  Google Scholar 

  96. Liu C, Li Y, Hao X (2017) An adaptive machining approach based on in-process inspection of interim machining states for large-scaled and thin-walled complex parts. Int J Adv Manuf Technol 90(9–12):3119–3128. https://doi.org/10.1007/s00170-016-9647-4

    Article  Google Scholar 

  97. Liu C, Vengayil H, Zhong RY, Xu X (2018) A systematic development method for cyber-physical machine tools. J Manuf Syst 48:13–24. https://doi.org/10.1016/j.jmsy.2018.02.001

    Article  Google Scholar 

  98. Boljanovic V (2010) Metal shaping processes: casting and molding, particulate processing, deformation processes, and metal removal. Industrial Press Inc., New York

  99. Boothroyd G, Dewhurt P, Knight WA (2011) Product design for manufacture and assembly, 3rd edn. CRC Press, Boca Raton

  100. Iqbal A, Zhang HC, Kong LL, Hussain G (2015) A rule-based system for trade-off among energy consumption, tool life, and productivity in machining process. J Intell Manuf 26(6):1217–1232. https://doi.org/10.1007/s10845-013-0851-x

    Article  Google Scholar 

  101. Jain NK, Jain VK (2001) Modeling of material removal in mechanical type advanced machining processes: a state-of-art review. Int J Mach Tools Manuf 41(11):1573–1635. https://doi.org/10.1016/S0890-6955(01)00010-4

    Article  Google Scholar 

  102. Sculz B (2017) Aluminum material removal rate new world record? Modern Machine Shop. https://www.mmsonline.com/blog/post/aluminum-material-removal-rate-new-world-record. Accessed 29 March 2020

  103. Jha SK (2014) Optimization of process parameters for optimal MRR during turning steel bar using Taguchi method and ANOVA. Int J Mech Eng Robot Res 3(3):231–243

    Google Scholar 

  104. Uhlmann E, Frost T (2001) Cutting and drilling of metals and other materials: a comparison. In: Encyclopedia of materials: science and technology, 2nd edn, pp 1928–1933. https://doi.org/10.1016/B0-08-043152-6/00351-X

    Chapter  Google Scholar 

  105. Hegab HA, Darras B, Kishawy HA (2018) Towards sustainability assessment of machining processes. J Clean Prod 170:694–703. https://doi.org/10.1016/j.jclepro.2017.09.197

    Article  Google Scholar 

  106. Al-Ghamdi KA, Iqbal A (2015) A sustainability comparison between conventional and high-speed machining. J Clean Prod 108:192–206. https://doi.org/10.1016/j.jclepro.2015.05.132

    Article  Google Scholar 

  107. Iqbal A, Al-Ghamdi KA, Hussain G (2016) Effects of tool life criterion on sustainability of milling. J Clean Prod 139:1105–1117. https://doi.org/10.1016/j.jclepro.2016.08.162

    Article  Google Scholar 

  108. Gutowski T, Dahmus J, Thiriez A (2006) Electrical energy requirements for manufacturing processes. In: 13th CIRP International Conference on Life Cycle Engineering. Leuven, Belgium; 31(1): 623–638

  109. Zhao GY, Liu ZY, He Y, Cao HJ, Guo YB (2017) Energy consumption in machining: classification, prediction, and reduction strategy. Energy 133:142–157. https://doi.org/10.1016/j.energy.2017.05.110

    Article  Google Scholar 

  110. Yoon HS, Lee JY, Kim HS, Kim MS, Kim ES, Shin YJ, Chu WS, Ahn SH (2014) A comparison of energy consumption in bulk forming, subtractive, and additive processes: review and case study. Int J Precis Eng Manuf Green Technol 1(3):261–279. https://doi.org/10.1007/s40684-014-0033-0

    Article  Google Scholar 

  111. Dahmus JB, Gutowski TG (2004) An environmental analysis of machining. In: ASME 2004 International mechanical engineering congress and exposition, pp 643-652. ASME Digital Collection

  112. Newman ST, Nassehi A (2007) Universal manufacturing platform for CNC machining. CIRP Ann 56(1):459–462. https://doi.org/10.1016/j.cirp.2007.05.110

    Article  Google Scholar 

  113. Elbestawi MA, Veldhuis SC, Deiab IM, Habel MJ, Roberts C (2002) Development of a novel modular and agile face machining technology. CIRP Ann 51(1):307–310. https://doi.org/10.1016/S0007-8506(07)61523-6

    Article  Google Scholar 

  114. Guergov S (2018) A review and analysis of the historical development of machine tools into complex intelligent mechatronic systems. J Mach Eng 18(1):107–119. https://doi.org/10.5604/01.3001.0010.8828

    Article  Google Scholar 

  115. Nakamoto K, Takeuchi Y (2017) Recent advances in multiaxis control and multitasking machining. Int J Autom Technol 11(2):140–154. https://doi.org/10.20965/ijat.2017.p0140

    Article  Google Scholar 

  116. Chen XS, Zhang DL, Yuan SM, Zhang X, Chen JY, Du RX (2013) A precision CNC turn-mill machining center with gear hobbing capability. Appl Mech Mater 300:1241–1249. https://doi.org/10.4028/www.scientific.net/AMM.300-301.1241

    Article  Google Scholar 

  117. Vinodh S, Sundararaj G, Devadasan SR, Rajanayagam D (2009) Agility through CAD/CAM integration. J Manuf Technol Manag 20(2):197–217. https://doi.org/10.1108/17410380910929628

    Article  Google Scholar 

  118. Revolutionizing customer service in manufacturing (Special Report) (2016) Salesforce Research. https://c1.sfdcstatic.com/content/dam/web/en_us/www/images/form/pdf/pdf/state-of-service-manufacturing.pdf. Accessed 31 March 2020

  119. Fountain M (2017) Some clever ways companies use agile manufacturing to compete. SAGE Automation. https://www.sageautomation.com/blog/four-clever-ways-companies-use-agile-manufacturing-to-compete. Accessed 31 March 2020

  120. Al-Saedi IR, Mohammed FM, Obayes SS (2017) CNC machine based on embedded wireless and internet of things for workshop development. In: International Conference on Control, Automation and Diagnosis (ICCAD), pp 439-444. IEEE. https://doi.org/10.1109/CADIAG.2017.8075699

  121. Yu H, Yu D, Hu Y, Wang C (2019) Research on CNC machine tool monitoring system based on OPC UA. In: Chinese Control and Decision Conference (CCDC), pp 3489-3493. IEEE. https://doi.org/10.1109/CCDC.2019.8832877

  122. Cai Y, Starly B, Cohen P, Lee YS (2017) Sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing. Proc Manuf 10:1031–1042. https://doi.org/10.1016/j.promfg.2017.07.094

    Article  Google Scholar 

  123. Bagheri B, Yang S, Kao HA, Lee J (2015) Cyber-physical systems architecture for self-aware machines in Industry 4.0 environment. IFAC-Papers OnLine 48(3):1622–1627. https://doi.org/10.1016/j.ifacol.2015.06.318

    Article  Google Scholar 

  124. Liu C, Cao S, Tse W, Xu X (2017) Augmented reality-assisted intelligent window for cyber-physical machine tools. J Manuf Syst 44:280–286. https://doi.org/10.1016/j.jmsy.2017.04.008

    Article  Google Scholar 

  125. Herwan J, Kano S, Oleg R, Sawada H, Kasashima N (2018) Cyber-physical system architecture for machining production line. In: IEEE Industrial Cyber-Physical Systems (ICPS), pp 387-391. IEEE. https://doi.org/10.1109/ICPHYS.2018.8387689

  126. Li XX, He FZ, Li WD (2019) A cloud-terminal-based cyber-physical system architecture for energy efficient machining process optimization. J Ambient Intell Humaniz Comput 10(3):1049–1064. https://doi.org/10.1007/s12652-018-0832-1

    Article  Google Scholar 

  127. Caggiano A, Segreto T, Teti R (2016) Cloud manufacturing framework for smart monitoring of machining. Proc CIRP 55:248–253. https://doi.org/10.1016/j.procir.2016.08.049

    Article  Google Scholar 

  128. Zhu K, Zhang Y (2018) A cyber-physical production system framework of smart CNC machining monitoring system. IEEE/ASME Trans Mechatron 23(6):2579–2586. https://doi.org/10.1109/TMECH.2018.2834622

    Article  Google Scholar 

  129. Armendia M, Cugnon F, Berglind L, Ozturk E, Gil G, Selmi J (2019) Evaluation of machine tool digital twin for machining operations in industrial environment. Proc CIRP 82:231–236. https://doi.org/10.1016/j.procir.2019.04.040

    Article  Google Scholar 

  130. Calderón Godoy AJ, González PI (2018) Integration of sensor and actuator networks and the scada system to promote the migration of the legacy flexible manufacturing system towards the industry 4.0 concept. J Sens Actuator Netw 7(2):23. https://doi.org/10.3390/jsan7020023

    Article  Google Scholar 

  131. Ye X, Hong SH (2018) An AutomationML/OPC UA-based Industry 4.0 solution for a manufacturing system. In 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), vol. 1, pp 543-550. IEEE. https://10.1109/ETFA.2018.8502637

  132. Cheng FT, Tieng H, Yang HC, Hung MH, Lin YC, Wei CF, Shieh ZY (2016) Industry 4.1 for wheel machining automation. IEEE Robot Auto Let 1(1):332–339. https://doi.org/10.1109/LRA.2016.2517208

    Article  Google Scholar 

  133. Liu C, Vengayil H, Lu Y, Xu X (2019) A cyber-physical machine tools platform using OPC UA and MTConnect. J Manuf Syst 51:61–74. https://doi.org/10.1016/j.jmsy.2019.04.006

    Article  Google Scholar 

  134. Nazarczuk M, Cader M, Kowalik M, Jankowski M (2019) Proposition of the methodology of the robotised part replication implemented in Industry 4.0 paradigm. In: Conference on Automation, pp 457–472. Springer, Cham. pp 457–472. https://doi.org/10.1007/978-3-030-13273-6_43

  135. de Araujo PR, Lins RG (2020) Computer vision system for workpiece referencing in three-axis machining centers. Int J Adv Manuf Technol 106(5):2007–2020. https://doi.org/10.1007/s00170-019-04626-w

    Article  MathSciNet  Google Scholar 

  136. Huang R, Yan B (2019) Development of wire electrical discharge machining control system based on cloud service. In: IEEE International Conference on Robotics and Biomimetics (ROBIO), pp 2849-2854. IEEE. https://doi.org/10.1109/ROBIO49542.2019.8961407

  137. Attaran M (2017) The rise of 3-D printing: the advantages of additive manufacturing over traditional manufacturing. Bus Horiz 60(5):677–688. https://doi.org/10.1016/j.bushor.2017.05.011

    Article  Google Scholar 

  138. Gibson I, Rosen DW, Stucker B (2014) Additive manufacturing technologies. Springer, New York

    Google Scholar 

  139. Standard AS (2012) Standard terminology for additive manufacturing technologies. ASTM International F2792-12a. West Conshohocken, PA

  140. Hull CW (1984) Apparatus for production of three-dimensional objects by stereolithography. United States Patent, Appl., No. 638905, Filed

  141. Lopez A, Andrade E (2017) Vat photopolymerisation. Prezi online learning. https://prezi.com/bysanqpooizv/vat-photopolymerisation/. Accessed 26 Apr 2020

  142. McIlroy C, Harlen OG, Morrison NF (2013) Modelling the jetting of dilute polymer solutions in drop-on-demand inkjet printing. J Non-Newtonian Fluid Mech 201:17–28. https://doi.org/10.1016/j.jnnfm.2013.05.007

    Article  Google Scholar 

  143. Yap YL, Wang C, Sing SL, Dikshit V, Yeong WY, Wei J (2017) Material jetting additive manufacturing: an experimental study using designed metrological benchmarks. Precis Eng 50:275–285. https://doi.org/10.1016/j.precisioneng.2017.05.015

    Article  Google Scholar 

  144. Le Néel TA, Mognol P, Hascoët JY (2018) A review on additive manufacturing of sand molds by binder jetting and selective laser sintering. Rapid Prototyp J 24(8):1325–1336. https://doi.org/10.1108/RPJ-10-2016-0161

    Article  Google Scholar 

  145. Gokuldoss PK, Kolla S, Eckert J (2017) Additive manufacturing processes: selective laser melting, electron beam melting and binder jetting—selection guidelines. Materials 10(6):672. https://doi.org/10.3390/ma10060672

    Article  Google Scholar 

  146. Worldwide most used 3D printing technologies, as of July 2018; Statista Research Department; March 2020. https://www.statista.com/statistics/756690/worldwide-most-used-3d-printing-technologies/. Accessed 26 Apr 2020

  147. Gebhardt A, Hötter JS (2016) Additive manufacturing: 3D printing for prototyping and manufacturing. Hanser Publications, Cincinnati

  148. Himmer T, Nakagawa T, Anzai M (1999) Lamination of metal sheets. Comput Ind 39(1):27–33. https://doi.org/10.1016/S0166-3615(98)00122-5

    Article  Google Scholar 

  149. Deckers J, Vleugels J, Kruth JP (2014) Additive manufacturing of ceramics: a review. J Ceram Sci Technol 5(4):245–260. https://doi.org/10.4416/JCST2014-00032

    Article  Google Scholar 

  150. Varotsis AB. Introduction to SLS 3D printing. 3D HUBS. https://www.3dhubs.com/knowledge-base/introduction-sls-3d-printing/#pros-cons. Accessed 28 APR 2020

  151. Flynt J (2019) All about SLS printing: advantages, disadvantages, history, and more; 3D Insider. https://3dinsider.com/sls-printing/. Accessed 28 APR 2020

  152. Bikas H, Stavropoulos P, Chryssolouris G (2016) Additive manufacturing methods and modelling approaches: a critical review. Int J Adv Manuf Technol 83(1–4):389–405. https://doi.org/10.1007/s00170-015-7576-2

    Article  Google Scholar 

  153. Baumers M, Dickens P, Tuck C, Hague R (2016) The cost of additive manufacturing: machine productivity, economies of scale and technology-push. Technol Forecast Soc Chang 102:193–201. https://doi.org/10.1016/j.techfore.2015.02.015

    Article  Google Scholar 

  154. Fera M, Macchiaroli R, Fruggiero F, Lambiase A (2018) A new perspective for production process analysis using additive manufacturing—complexity vs production volume. Int J Adv Manuf Technol 95(1–4):673–685. https://doi.org/10.1007/s00170-017-1221-1

    Article  Google Scholar 

  155. Gusarov AV, Grigoriev SN, Volosova MA, Melnik YA, Laskin A, Kotoban DV, Okunkova AA (2018) On productivity of laser additive manufacturing. J Mater Process Technol 261:213–232. https://doi.org/10.1016/j.jmatprotec.2018.05.033

    Article  Google Scholar 

  156. Pradel P, Bibb R, Zhu Z, Moultrie J (2018) Exploring the impact of shape complexity on build time for material extrusion and material jetting. In: Industrializing Additive Manufacturing-Proceedings of Additive Manufacturing in Products and Applications-AMPA 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-66866-6_3

  157. Rajaguru K, Karthikeyan T, Vijayan V (2020) Additive manufacturing–state of art. Mater Today Proc 21:628–633. https://doi.org/10.1016/j.matpr.2019.06.728

    Article  Google Scholar 

  158. Mani M, Lyons KW, Gupta SK (2014) Sustainability characterization for additive manufacturing. J Res NIST 119:419. https://doi.org/10.6028/jres.119.016

    Article  Google Scholar 

  159. Ford S, Despeisse M (2016) Additive manufacturing and sustainability: an exploratory study of the advantages and challenges. J Clean Prod 137:1573–1587. https://doi.org/10.1016/j.jclepro.2016.04.150

    Article  Google Scholar 

  160. Leino M, Pekkarinen J, Soukka R (2016) The role of laser additive manufacturing methods of metals in repair, refurbishment and remanufacturing–enabling circular economy. Phys Procedia 83:752–760. https://doi.org/10.1016/j.phpro.2016.08.077

    Article  Google Scholar 

  161. Chu C, Graf G, Rosen DW (2008) Design for additive manufacturing of cellular structures. Comput Aided Des Appl 5(5):686–696. https://doi.org/10.3722/cadaps.2008.686-696

    Article  Google Scholar 

  162. Kellens K, Mertens R, Paraskevas D, Dewulf W, Duflou JR (2017) Environmental impact of additive manufacturing processes: does AM contribute to a more sustainable way of part manufacturing? Proc CIRP. 61:582–587. https://doi.org/10.1016/j.procir.2016.11.153

    Article  Google Scholar 

  163. Anderson IE, White EM, Dehoff R (2018) Feedstock powder processing research needs for additive manufacturing development. Curr Opin Solid State Mater Sci 22(1):8–15. https://doi.org/10.1016/j.cossms.2018.01.002

    Article  Google Scholar 

  164. Bogers M, Hadar R, Bilberg A (2016) Additive manufacturing for consumer-centric business models: implications for supply chains in consumer goods manufacturing. Technol Forecast Soc Chang 102:225–239. https://doi.org/10.1016/j.techfore.2015.07.024

    Article  Google Scholar 

  165. Yao X, Lin Y (2016) Emerging manufacturing paradigm shifts for the incoming industrial revolution. Int J Adv Manuf Technol 85(5–8):1665–1676. https://doi.org/10.1007/s00170-015-8076-0

    Article  Google Scholar 

  166. Rauch E, Unterhofer M, Dallasega P (2018) Industry sector analysis for the application of additive manufacturing in smart and distributed manufacturing systems. Manuf Lett 15:126–131. https://doi.org/10.1016/j.mfglet.2017.12.011

    Article  Google Scholar 

  167. Bogers M, Hadar R, Bilberg A (2015) Business models for additive manufacturing: exploring digital technologies, consumer roles, and supply chains . Technological Forecasting & Social Change, 2015, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2638054

  168. Sealy MP, Madireddy G, Williams RE, Rao P, Toursangsaraki M (2018) Hybrid processes in additive manufacturing. J Manuf Sci Eng 140(6):060801. https://doi.org/10.1115/1.4038644

    Article  Google Scholar 

  169. Perez KB, Williams CB (2014) Design considerations for hybridizing additive manufacturing and direct write technologies. In: ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASME Digital Collection. https://doi.org/10.1115/DETC2014-35408

  170. Raynaud J, Pateloup V, Bernard M, Gourdonnaud D, Passerieux D, Cros D, Madrangeas V, Chartier T (2020) Hybridization of additive manufacturing processes to build ceramic/metal parts: example of LTCC. J Eur Ceram Soc 40(3):759–767. https://doi.org/10.1016/j.jeurceramsoc.2019.10.019

    Article  Google Scholar 

  171. Driscoll D, Sofie S (2018) Hybridization of freeze casting with additive manufacturing for simplified production of high performance SOFCs. Glacigen Materials, Inc., Bozeman

    Google Scholar 

  172. Jones JB (2014) The synergies of hybridizing CNC and additive manufacturing. Hybrid Manufacturing Technologies Ltd. http://www.hybridmanutech.com/uploads/2/3/6/9/23690678/2014_jones_hybridizing_cnc___am__authors_version_of_sme_tp14pub77_.pdf. Accessed 23 MAY 2020

  173. Müller M, Wings E (2016) An architecture for hybrid manufacturing combining 3D printing and CNC machining. Int J Manuf Eng 8609108:1–12. https://doi.org/10.1155/2016/8609108

    Article  Google Scholar 

  174. Yamazaki T (2016) Development of a hybrid multi-tasking machine tool: integration of additive manufacturing technology with CNC machining. Proc CIRP 42:81–86. https://doi.org/10.1016/j.procir.2016.02.193

    Article  Google Scholar 

  175. Yan L, Cui W, Newkirk JW, Liou F, Thomas EE, Baker AH, Castle JB (2018) Build strategy investigation of Ti-6Al-4V produced via a hybrid manufacturing process. JOM. 70(9):1706–1713. https://doi.org/10.1007/s11837-018-3009-7

    Article  Google Scholar 

  176. Williams SW, Martina F, Addison AC, Ding J, Pardal G, Colegrove P (2016) Wire+ arc additive manufacturing. Mater Sci & Technol 32(7):641–647. https://doi.org/10.1179/1743284715Y.0000000073

    Article  Google Scholar 

  177. Al-Tarifi MA, Filipovic DS (2017) On the design and fabrication of W-band stabilised-pattern dual-polarised horn antennas with DMLS and CNC. IET Microwaves Antennas Propag 11(14):1930–1935. https://doi.org/10.1049/iet-map.2017.0167

    Article  Google Scholar 

  178. Nyamekye P, Leino M, Piili H, Salminen A (2015) Overview of sustainability studies of CNC machining and LAM of stainless steel. Phys Proc 78:367–376. https://doi.org/10.1016/j.phpro.2015.11.051

    Article  Google Scholar 

  179. Karunakaran KP, Suryakumar S, Pushpa V, Akula S (2009) Retrofitment of a CNC machine for hybrid layered manufacturing. Int J Adv Manuf Technol 45(7–8):690–703. https://doi.org/10.1007/s00170-009-2002-2

    Article  Google Scholar 

  180. Yang Y, Gong Y, Qu S, Xie H, Cai M, Xu Y (2020) Densification, mechanical behaviors, and machining characteristics of 316L stainless steel in hybrid additive/subtractive manufacturing. Int J Adv Manuf Technol 107(1):177–189. https://doi.org/10.1007/s00170-020-05033-2

    Article  Google Scholar 

  181. Li S, Zhang B, Bai Q (2020) Effect of temperature buildup on milling forces in additive/subtractive hybrid manufacturing of Ti-6Al-4V. Int J Adv Manuf Technol 107(9–10):4191–4200. https://doi.org/10.1007/s00170-020-05309-7

    Article  Google Scholar 

  182. Li P, Gong Y, Xu Y, Qi Y, Sun Y, Zhang H (2019) Inconel-steel functionally bimetal materials by hybrid directed energy deposition and thermal milling: microstructure and mechanical properties. Arch Civ Mech Eng 19(3):820–831. https://doi.org/10.1016/j.acme.2019.03.002

    Article  Google Scholar 

  183. Nagamatsu H, Sasahara H, Mitsutake Y, Hamamoto T (2020) Development of a cooperative system for wire and arc additive manufacturing and machining. Addit Manuf 31:100896. https://doi.org/10.1016/j.addma.2019.100896

    Article  Google Scholar 

  184. Zhang S, Zhang Y, Gao M, Wang F, Li Q, Zeng X (2019) Effects of milling thickness on wire deposition accuracy of hybrid additive/subtractive manufacturing. Sci Technol Weld Join 24(5):375–381. https://doi.org/10.1080/13621718.2019.1595925

    Article  Google Scholar 

  185. Hong Y, Lei J, Heim M, Song Y, Yuan L, Mu S, Bordia RK, Xiao H, Tong J, Peng F (2019) Fabricating ceramics with embedded microchannels using an integrated additive manufacturing and laser machining method. J Am Ceram Soc 102(3):1071–1082. https://doi.org/10.1111/jace.15982

    Article  Google Scholar 

  186. Boschetto A, Bottini L, Veniali F (2016) Finishing of fused deposition modeling parts by CNC machining. Robot Comput Integr Manuf 41:92–101. https://doi.org/10.1016/j.rcim.2016.03.004

    Article  Google Scholar 

  187. Zhao Y, Sun J, Li J, Wang P, Zheng Z, Chen J, Yan Y (2018) The stress coupling mechanism of laser additive and milling subtractive for FeCr alloy made by additive–subtractive composite manufacturing. J Alloys Compd 769:898–905. https://doi.org/10.1016/j.jallcom.2018.08.079

    Article  Google Scholar 

  188. Heigel JC, Phan TQ, Fox JC, Gnaupel-Herold TH (2018) Experimental investigation of residual stress and its impact on machining in hybrid additive/subtractive manufacturing. Procedia Manuf 26:929–940. https://doi.org/10.1016/j.promfg.2018.07.120

    Article  Google Scholar 

  189. Alexander I, Vladimir G, Petr P, Mihail K, Yuriy I, Andrey V (2016) Machining of thin-walled parts produced by additive manufacturing technologies. Proc CIRP 41:1023–1026. https://doi.org/10.1016/j.procir.2015.08.088

    Article  Google Scholar 

  190. Ye ZP, Zhang ZJ, Jin X, Xiao MZ, Su JZ (2017) Study of hybrid additive manufacturing based on pulse laser wire depositing and milling. Int J Adv Manuf Technol 88(5–8):2237–2248. https://doi.org/10.1007/s00170-016-8894-8

    Article  Google Scholar 

  191. Zheng Y, Qureshi AJ, Ahmad R (2018) Algorithm for remanufacturing of damaged parts with hybrid 3D printing and machining process. Manuf Lett 15:38–41. https://doi.org/10.1016/j.mfglet.2018.02.010

    Article  Google Scholar 

  192. Le VT, Mandil HPG (2017) Extraction of features for combined additive manufacturing and machining processes in a remanufacturing context. In: Eynard B, Nigrelli V, Oliveri S, Peris-Fajarnes G, Rizzuti S (eds) Advances on mechanics, design engineering and manufacturing. Lecture notes in mechanical engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-45781-9_19

    Chapter  Google Scholar 

  193. Wippermann A, Gutowski TG, Denkena B, Dittrich MA, Wessarges Y (2020) Electrical energy and material efficiency analysis of machining, additive and hybrid manufacturing. J Clean Prod 251:119731. https://doi.org/10.1016/j.jclepro.2019.119731

    Article  Google Scholar 

  194. Fullenwider B, Kiani P, Schoenung JM, Ma K (2019) from recycled machining waste to useful powders for metal additive manufacturing. In: Gaustad G, et al. (eds) REWAS. The minerals, metals & materials series. Springer, Cham. https://doi.org/10.1007/978-3-030-10386-6_1

  195. Faludi J, Bayley C, Bhogal S, Iribarne M (2015) Comparing environmental impacts of additive manufacturing vs traditional machining via life-cycle assessment. Rapid Prototyp J 21(1):14–33. https://doi.org/10.1108/RPJ-07-2013-0067

    Article  Google Scholar 

  196. Jiang Q, Liu Z, Li T, Cong W, Zhang HC (2019) Emergy-based life-cycle assessment (Em-LCA) for sustainability assessment: a case study of laser additive manufacturing versus CNC machining. Int J Adv Manuf Technol 102(9–12):4109–4120. https://doi.org/10.1007/s00170-019-03486-8

    Article  Google Scholar 

  197. Ingarao G, Priarone PC, Deng Y, Paraskevas D (2018) Environmental modelling of aluminium based components manufacturing routes: additive manufacturing versus machining versus forming. J Clean Prod 176:261–275. https://doi.org/10.1016/j.jclepro.2017.12.115

    Article  Google Scholar 

  198. Manogharan G, Wysk RA, Harrysson OL (2016) Additive manufacturing–integrated hybrid manufacturing and subtractive processes: economic model and analysis. Int J Comput Integr Manuf 29(5):473–488. https://doi.org/10.1080/0951192X.2015.1067920

    Article  Google Scholar 

  199. Kerbrat O, Mognol P, Hascoët JY (2011) A new DFM approach to combine machining and additive manufacturing. Comput Ind 62(7):684–692. https://doi.org/10.1016/j.compind.2011.04.003

    Article  Google Scholar 

  200. Chen N, Frank M (2019) Process planning for hybrid additive and subtractive manufacturing to integrate machining and directed energy deposition. Proc Manuf 34:205–213. https://doi.org/10.1016/j.promfg.2019.06.140

    Article  Google Scholar 

  201. Chen N, Barnawal P, Frank MC (2018) Automated post machining process planning for a new hybrid manufacturing method of additive manufacturing and rapid machining. Rapid Prototyp J 24(7):1077–1090. https://doi.org/10.1108/RPJ-04-2017-0057

    Article  Google Scholar 

  202. Li L, Haghighi A, Yang Y (2018) A novel 6-axis hybrid additive-subtractive manufacturing process: design and case studies. J Manuf Proc 33:150–160. https://doi.org/10.1016/j.jmapro.2018.05.008

    Article  Google Scholar 

  203. Manogharan G, Wysk R, Harrysson O, Aman R (2015) AIMS–a metal additive-hybrid manufacturing system: system architecture and attributes. Process Manuf 1:273–286. https://doi.org/10.1016/j.promfg.2015.09.021

    Article  Google Scholar 

  204. Du W, Bai Q, Wang Y, Zhang B (2018) Eddy current detection of subsurface defects for additive/subtractive hybrid manufacturing. Int J Adv Manuf Technol 95(9–12):3185–3195. https://doi.org/10.1007/s00170-017-1354-2

    Article  Google Scholar 

  205. Wang Z, Liu R, Sparks T, Liu H, Liou F (2015) Stereo vision based hybrid manufacturing process for precision metal parts. Precis Eng 42:1–5. https://doi.org/10.1016/j.precisioneng.2014.11.012

    Article  Google Scholar 

  206. Boccella AR, Piera C, Cerchione R, Murino T (2020) Evaluating centralized and heterarchical control of smart manufacturing systems in the era of Industry 4.0. Appl Sci 10(3):755. https://doi.org/10.3390/app10030755

    Article  Google Scholar 

  207. Ye SX, Qiu RG (2003) An architecture of configurable equipment connectivity in a future manufacturing information system. In: Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No. 03EX694), vol 3, pp 1144-1149. IEEE. https://doi.org/10.1109/CIRA.2003.1222158

  208. Rojas RA, Rauch E, Vidoni R, Matt DT (2017) Enabling connectivity of cyber-physical production systems: a conceptual framework. Proc Manuf 11:822–829. https://doi.org/10.1016/j.promfg.2017.07.184

    Article  Google Scholar 

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Funding

The work presented in the article is financially supported by Universiti Brunei Darussalam, Brunei through its University Research Grant scheme (Grant number: UBD/RSCH/URC/RG(b)/2018/003) and the 111 Project on Key Technology in Sustainable Manufacturing (Grant number: B16024).

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Iqbal, A., Zhao, G., Suhaimi, H. et al. Readiness of subtractive and additive manufacturing and their sustainable amalgamation from the perspective of Industry 4.0: a comprehensive review. Int J Adv Manuf Technol 111, 2475–2498 (2020). https://doi.org/10.1007/s00170-020-06287-6

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