Smart Additive Manufacturing: The Path to the Digital Value Chain
2. Digital Manufacturing, Digital Supply Chains, and Digital Value Chains
- AR can improve the fabrication speed in a SAM process, through the communication of the layout information between a reconfigurable AM system made of robotic arms and its corresponding digital twin for toolpath planning and simulation, allowing the introduce of multiple independent actuators for concurrent deposition of materials without collision among them .
- AR can also support the detection of problems in an AM process caused by inaccessible measurements or parts movements that are difficult to anticipate, through an AR-based application that allows evaluating individually engineered parts based on virtual three-dimensional (3D)-computer-aided design models (CAD) projected to the intended installation-site .
3. Smart Manufacturing, Additive Manufacturing, and Smart Additive Manufacturing
3.1. Smart Manufacturing
- Pillar 1—The emergence of manufacturing technology and processes: AM is an example of a new technology that has inspired the development of new materials, impacted the design and the manufacture of products, and opened doors to new applications.
- Pillar 2—Materials: Smart manufacturing is open to all types of materials including organic-based materials and biomaterials. However, the emergence of new materials requires their incorporation into smart manufacturing and the development of new processes.
- Pillar 3—Data: We are witnessing a significant increase in data collected from various sources, some of which have been triggered by the deployment of smart sensors, wireless technologies, and data analysis. The data will be used to shape the development of future programs and applications as well as in building predictive models.
- Pillar 4—Predictive engineering: Predictive engineering creates high-fidelity digital models of the phenomena of interest, which will inform decisions about future production and market conditions.
- Pillar 5—Sustainability: The development of products and processes should be guided by a sustainability criterion including sustainable product design, manufacturing processes, and materials.
- Pillar 6—Resource sharing and networking: As manufacturing engages more digital and virtual technologies, many of the creative and decision-making activities will require resource sharing and networking.
3.2. Additive Manufacturing
- Principle 1—Innovation: AM technology promotes the creation of new business models based on localized production, mass production customization, and/or the diversification of products and services.
- Principle 2—Performance: AM technology enables the creation of parts with optimized material distribution, resulting in better performance.
- Principle 3—Sustainability: AM technology can produce parts using recycled materials or materials that are reintroduced into the production process. For this reason, this technology facilitates a circular economy by minimizing the ecological footprint. In addition, lighter and more durable products are created with this technology, as compared to production using conventional technologies. It also supports reduced fuel costs and emissions, namely in activities and sectors linked to mobility.
- Principle 4—Competitiveness: AM technology reduces the time to market as it reduces the time between conception and production and allows production to be decentralized (i.e., the end product can be produced at multiple locations rather than from a single factory or plant, reducing transportation costs).
- Effect 1—Reduction in supply chain complexity: AM technology can often produce a complete unit, eliminating the need to assemble multiple components. It also reduces the need for replacement parts, shortens the flow of production, allows for better monitoring of the materials used, and reduces internal production costs (e.g., internal transport, labor, etc.).
- Effect 2—Flexible logistics and inventory management: The integration of AM technology can significatively influence logistics and transportation activities and, consequently, global value chains since production can take place close to the final consumption location. This can reduce costs on several fronts, including configuration and reprocessing, inventories, spare parts, and other associated costs, including transportation costs. We may be facing a new trend in manufacturing that is focused on replacing physical products and raw material stock with digital stock stored in a 3D file format.
- Effect 3—Mass customization: AM technology has encouraged mass (production) customization, as opposed to mass production, as it facilitates the production of customizable products and design flexibility at a reasonable cost while being environmentally responsible.
- Effect 4—Decentralization of manufacturing: AM technology can bring several benefits to global supply chains, such as on-site production and consumption. This can shorten the response time to changes in demand and reduce overall time to market.
- Effect 5—Design freedom and rapid prototyping: AM technology enables the production of parts with complex geometries, overcoming some of the restrictions associated with product design, such as higher costs when using traditional subtractive processes. In turn, this technology is associated with a new era in global production through the digitization of production, where a wide range of fundamentally different items can be made, quickly and easily, according to end users’ specifications.
- Effect 6—Resource efficiency and sustainability: AM processes generally consume less energy compared to conventional manufacturing processes. On the other hand, the reconfiguration of shorter, more collaborative supply chains extends the life of a product via repair, remanufacturing, and reconditioning.
- Effect 7—Discussions surrounding regulations, safety, and security: The current legal framework for AM or 3D printing does not regulate the digitization of physical objects. Therefore, the proliferation of digital files containing physical scanned products is not adequately monitored or regulated at this time. In addition, given the vast range of goods that can be 3D printed, guidelines and regulations regarding safety and intellectual property rights are essential.
3.3. Smart Additive Manufacturing
- Smart Processes. SAM technology improves smart processes. For example, it facilitates communication between smart 3D printing machines and other equipment in a factory. In addition, if a problem occurs with production, the collected data will highlight the issue and machines involved, and then AI support can be dispatched to resolve the problem. This allows for flexible and adaptable production systems .
4. Smart Additive Manufacturing and Digital Value Chains
- Stage 1—Idea and design: It marks the beginning of the digital wire. As mentioned earlier, SAM technology can support design geometries and features that could not be achieved using subtractive techniques. The design phase supports the product from its conception, production, and distribution until the end of its useful life or it is decommissioned.
- Stage 2—Speed to market: After designing the product, it proceeds to production, which involves the identification of materials and processes required. At this stage, issues of rapid prototyping, the use of new or smart materials, and new processes (including their integration across processes and technologies) and production close to the market are particularly important. Within this context, new possibilities and new opportunities arise. As already mentioned, SAM allows the use of smart materials and production close to the market.
- Stage 3—Optimized production: optimization through “Digital Twin” (DT) reduces the complexity surrounding production and assembly in manufacturing as it allows the simulation, monitoring and control of the process, as well as the reduction of material waste, machine operator time and printer depreciation. This virtual representation can help to understand the functions of various manufacturing parameters and the sensitivity of product quality to those parameters. The implementation of DT technology in smart additive manufacturing systems has shown great potential in enabling advanced manufacturing data management, developing simulation and prediction models, reducing development times and costs, and improving product quality and production efficiency [82,83].
- Stage 4—On-demand supply: On-demand supply corresponds to a new stage in the DVC: the digital inventory. Since manufacturers can produce a physical product on demand from a digital inventory, they have greater supply chain security and significantly reduced costs. Commonly associated with production flexibility, SAM allows the production directly from digital files, available in digital inventories, without the need for tools or molds, enabling on-demand production and allowing SCs to quickly deal with demand fluctuations .
- Stage 5—Controlled phase-out: The controlled phase-out eliminates the costs associated with storage and inventory, replacing the latter with a digital inventory of digital spare parts to be printed on demand. As mentioned in the previous point, by allowing production on demand, using digital files and digital inventories, SAM will avoid unnecessary storage and inventory costs .
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
- Napoleone, A.; Macchi, M.; Pozzetti, A. A review on the characteristics of cyber-physical systems for the future smart factories. J. Manuf. Syst. 2020, 54, 305–335. [Google Scholar] [CrossRef]
- Grabowska, S. Smart factories in the age of industry 4.0. Manag. Syst. Prod. Eng. 2020, 28, 90–96. [Google Scholar] [CrossRef]
- Kagermann, H.; Wahlster, W.; Helbig, J. Recommendations for Implementing the Strategic Initiative Industrie 4.0: Final Report of the Industrie 4.0 Working Group; Acatec–National Academy of Science and Engineering: Munich, Germany, 2011. [Google Scholar]
- Tu, M.; Lim, M.; Yang, M. IoT-based production logistics and supply chain. Ind. Manag. Data Syst. 2018, 118, 96–125. [Google Scholar] [CrossRef][Green Version]
- Khajavi, S.H.; Ituarte, I.F.; Jaribion, A.; An, J.; Kai, C.C.; Holmstrom, J. Impact of additive manufacturing on supply chain complexity. In Proceedings of the 53rd Hawaii International Conference on System, Maui, HI, USA, 7–10 January 2020. [Google Scholar] [CrossRef][Green Version]
- Devi, A.; Mathiyazhagan, K.; Kumar, H. Additive manufacturing in supply chain management: A systematic review. In Advances in Manufacturing and Industrial Engineering. Lecture Notes in Mechanical Engineering; Springer: Singapore, 2021; pp. 455–464. [Google Scholar] [CrossRef]
- Baryshnikova, A.; Taratukhin, V. Digital transformation framework for smart factory. In Proceedings of the AMCIS 2017 Workshops, Boston, MA, USA, 10 August 2017. [Google Scholar]
- Rejeb, A.; Keogh, J.G.; Wamba, S.F.; Treiblmaier, H. The potentials of augmented reality in supply chain management: A state-of-the-art review. Manag. Rev. Q. 2020. [Google Scholar] [CrossRef]
- Rejeb, A.; Keogh, J.G.; Leong, G.K.; Treiblmaier, H. Potentials and challenges of augmented reality smart glasses in logistics and supply chain management: A systematic literature review. Int. J. Prod. Res. 2021, 59, 3747–3776. [Google Scholar] [CrossRef]
- Cai, Y.; Wang, Y.; Burnett, M. Using augmented reality to build digital twin for reconfigurable additive manufacturing system. J. Manuf. Syst. 2020, 56, 598–604. [Google Scholar] [CrossRef]
- Kutej, D.; Vorraber, W. Fostering additive manufacturing of special parts with augmented-reality on-site visualization. Procedia Manuf. 2019, 39, 13–21. [Google Scholar] [CrossRef]
- Özkanlısoy, O.; Akkartal, E. Digital transformation in supply chains: Current applications, contributions and challenges. Bus. Manag. Stud. Int. J. 2021, 9, 32–55. [Google Scholar] [CrossRef]
- Gillani, F.; Chatha, K.A.; Jajja, M.S.S.; Farooq, S. Implementation of digital manufacturing technologies: Antecedents and consequences. Int. J. Prod. Econ. 2020, 229, 107748. [Google Scholar] [CrossRef]
- Do Chung, B.; Kim, S.I.; Lee, J.S. Dynamic supply chain design and operations plan for connected smart factories with additive manufacturing. Appl. Sci. 2018, 8, 583. [Google Scholar] [CrossRef][Green Version]
- Hofmann, E.; Rüsch, M. Industry 4.0 and the current status as well as future prospects on logistics. Comput. Ind. 2017, 89, 23–34. [Google Scholar] [CrossRef]
- Ward, M.; Halliday, S.; Uflewska, O.; Wong, T. Three dimensions of maturity required to achieve future state, technology-enabled manufacturing supply chains. Proc. Inst. Mech. Eng. Part B J. Eng. 2018, 232, 605–620. [Google Scholar] [CrossRef][Green Version]
- Junge, A.L.; Straube, F. Sustainable supply chains—Digital transformation technologies’ impact on the social and environmental dimension. Procedia Manuf. 2020, 43, 736–742. [Google Scholar] [CrossRef]
- Kehoe, D.; Boughton, M. Internet based supply chain management: A classification of approaches to manufacturing planning and control. Intern. J. Oper. Prod. Manag. 2001, 21, 516–524. [Google Scholar] [CrossRef]
- Lee, H.; Billington, C. Managing supply chain inventory: Pitfalls and opportunities. Sloan Emanag. Rev. 1992, 33, 65–73. [Google Scholar]
- Min, S.; Zacharia, Z.G.; Smith, C.D. Defining supply chain management: In the past, present, and future. J. Bus. Logist. 2019, 40, 44–55. [Google Scholar] [CrossRef][Green Version]
- MacCarthy, B.; Blome, C.; Olhager, J.; Srai, J.; Zhao, X. Supply chain evolution—Theory. Int. J. Oper. Prod. Manag. 2016, 36, 213–244. [Google Scholar] [CrossRef]
- Yu, Z.; Razzaq, A.; Rehman, A.; Shah, A.; Jameel, K.; Mor, R.S. Disruption in global supply chain and socio-economic shocks: A lesson from COVID-19 for sustainable production and consumption. Oper. Manag. Res. 2021. [Google Scholar] [CrossRef]
- Llaguno, A.; Mula, J.; Campuzano-Bolarin, F. State of the art, conceptual framework and simulation analysis of the ripple effect on supply chains. Int. J. Prod. Res. 2021, 1–23. [Google Scholar] [CrossRef]
- Nazir, A.; Azhar, A.; Nazir, U.; Liu, Y.-F.; Qureshi, W.S.; Chen, J.-E.; Alanazi, E. The rise of 3D Printing entangled with smart computer aided design during COVID-19 era. J. Manuf. Syst. 2021, 60, 774–786. [Google Scholar] [CrossRef]
- Illahi, U.; Mir, M.S. Maintaining efcient logistics and supply chain management operations during and after coronavirus (COVID-19) pandemic: Learning from the past experiences. Environ. Dev. Sustain. 2021, 23, 11157–11178. [Google Scholar] [CrossRef] [PubMed]
- Ivanov, D.; Das, A. Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: A research note. Int. J. Integr. Supply Manag. 2020, 13, 90–102. [Google Scholar] [CrossRef]
- Burgos, D.; Ivanov, D. Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions. Transp. Res. Part E Logist. Transp. Rev. 2021, 152, 102412. [Google Scholar] [CrossRef]
- Hanley, T.; Daecher, A.; Cotteleer, M.; Sniderman, B. The Industry 4.0 Paradox: Overcoming Disconnects on the Path to Digital Transformation. Available online: https://www2.deloitte.com/global/en/pages/energy-and-resources/articles/the-industry-4-0-pa (accessed on 4 June 2021).
- Orzes, G.; Rauch, E.; Bednar, S.; Poklemba, R. Industry 4.0 implementation barriers in small and medium-sized enterprises: A focus group study. In Proceedings of the 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bangkok, Thailand, 16–19 December 2018. [Google Scholar]
- Albukhitan, S. Developing digital transformation strategy for manufacturing. Procedia Comput. Sci. 2020, 170, 664–671. [Google Scholar] [CrossRef]
- Kusiak, A. Smart manufacturing. Int. J. Prod. Res. 2018, 56, 508–517. [Google Scholar] [CrossRef]
- Büchi, G.; Cugno, M.; Castagnoli, R. Smart factory performance and Industry 4.0. In Technological Forecasting and Social Change; Elsevier: Torino, Italy, 2020; Volume 150. [Google Scholar]
- Evjemo, L.; Gjerstad, T.; Grøtli, E.; Sziebig, G. Trends in smart manufacturing: Role of humans and industrial robots in smart factories. In Robotics in Manufacturing; Springer: Singapore, 2020; pp. 35–41. [Google Scholar]
- Wang, B.; Tao, F.; Fang, X.; Liu, C.; Liu, Y.; Freiheit, T. Smart manufacturing and intelligent manufacturing: A comparative review. Engineering 2020, 7, 738–757. [Google Scholar] [CrossRef]
- Waibel, M.; Steenkamp, L.; Moloko, N.; Oosthuizen, G. Investigating the effects of smart production systems on sustainability elements. Procedia Manuf. 2017, 8, 731–737. [Google Scholar] [CrossRef]
- Lee, J.; Singh, J.; Azamfar, M.; Pandhare, V. Industrial AI and predictive analytics for smart manufacturing systems. In Smart Manufacturing; Elsevier: Amsterdam, The Netherlands, 2020. [Google Scholar]
- Druzgalski, C.; Ashby, A.; Guss, G.; King, W.; Roehling, T.; Matthews, M. Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing. Addit. Manuf. 2020, 34, 101169. [Google Scholar] [CrossRef]
- Advincula, R.C.; Dizon, J.R.C.; Chen, Q.; Niu, I.; Chung, J.; Kilpatrick, L.; Newman, R. Additive manufacturing for COVID-19: Devices, materials, prospects, and challenges. MRS Commun. 2020, 10, 413–427. [Google Scholar] [CrossRef]
- Larrañeta, E.; Dominguez-Robles, J.; Lamprou, D.A. Additive manufacturing can assist in the fight against COVID-19 and other pandemics and impact on the global supply chain. 3D Print. Addit. Manuf. 2020, 7, 100–103. [Google Scholar] [CrossRef]
- Patel, P.; Gohil, P. Role of additive manufacturing in medical application COVID-19 scenario: India case study. J. Manuf. Syst. 2021, 60, 811–822. [Google Scholar] [CrossRef] [PubMed]
- Srinivasan, R.; Mian, A.; Gockel, J.; Luehrmann, L. Additive Manufacturing and How 3D Printing Is Fighting COVID-19. 2020. Available online: https://corescholar.libraries (accessed on 2 July 2021).
- Yadav, A.; Srivastav, A.; Singh, A.; Mushtaque, M.; Khan, S.; Kumar, H.; Arora, P. Investigation on the materials used in additive manufacturing: A study. Mater. Today Proc. 2021, 43, 154–157. [Google Scholar] [CrossRef]
- CECIMO—European Association of the Machine Tool Industries. What Is Additive Manufacturing? 2021. Available online: https://www.cecimo.eu/machine-tools/additive (accessed on 20 April 2021).
- Begoc, S.; Palerm, S.; Salapete, R.; Theron, M.; Dehouve, J. Additive manufacturing at french space agency with industry paternship. In Advances in 3D Printing & Additive Manufacturing Technologies; Springer: Singapore, 2017; pp. 111–120. [Google Scholar] [CrossRef]
- Dogan, E.; Bhusal, A.; Cecen, B.; Miri, A. 3D Printing metamaterials towards tissue engineering. Appl. Mater. Today 2020, 20, 100752. [Google Scholar] [CrossRef]
- Kosic, B.; Dragicevic, A.; Jeli, Z.; Marinescu, G. Application of 3D printing in the metamaterials designing. In Computational and Experimental Approaches in Materials Science and Engineering; Springer: Cham, Switzerland, 2018; Volume 90. [Google Scholar]
- Shie, M.-Y.; Shen, Y.-F.; Astuti, S.D.; Lee, A.K.-X.; Lin, S.-H.; Dwijaksara, N.L.B.; Chen, Y.-W. Review of polymeric materials in 4D printing biomedical applications. Polymers 2019, 11, 1864. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Subeshan, B.; Baddam, Y.; Asmatulu, E. Current progress of 4D-printing technology. Prog. Addit. Manuf. 2021, 6, 495–516. [Google Scholar] [CrossRef]
- Wan, Z.; Zhang, P.; Liu, Y. Four-dimensional bioprinting: Current developments and applications in bone tissue engineering. Acta Biomater. 2019, 101, 26–42. [Google Scholar] [CrossRef]
- Teng, X.; Zhang, M.; Mujumdar, A.S. 4D printing: Recent advances and proposals in the food sector. Trends Food Sci. Technol. 2021, 110, 349–363. [Google Scholar] [CrossRef]
- Chu, H.; Yang, W.; Sun, L.; Cai, S.; Yang, R.; Liang, W.; Yu, H.; Liu, L. 4D printing: A review on recent progresses. Micromachines 2020, 11, 796. [Google Scholar] [CrossRef]
- Manen, T.V.; Janbaz, S.; Jansen, K.M.B.; Zadpoor, A.A. 4D printing of reconfigurable metamaterials and devices. Comun. Mater. 2021, 2, 56. [Google Scholar] [CrossRef]
- Haleem, A.; Javaid, M.; Singh, R.P.; Suman, R. Significant roles of 4D printing using smart materials in the field of manufacturing. Adv. Ind. Eng. Polym. Res. 2021, 4, 301–311. [Google Scholar] [CrossRef]
- Reddy, S. Smart materials for 4D printing: A review on developments, challenges and applications. Recent Adv. Manuf. Autom. Des. Energy Technol. Lect. Notes Mech. Eng. 2021, 3–10. [Google Scholar] [CrossRef]
- Pei, E.; Loh, G.H. Technological considerations for 4D printing: An overview. Prog. Addit. Manuf. 2018, 3, 95–107. [Google Scholar] [CrossRef][Green Version]
- Gao, W.; Zhang, Y.; Ramanujan, D.; Ramani, K.; Chen, Y.; Williams, C.; Wang, C.; Shin, Y.; Zhang, S.; Zavattieri, P. The status, challenges, and future of additive manufacturing in engineering. Comput.-Aided Des. 2015, 69, 65–89. [Google Scholar] [CrossRef]
- Guessasma, S.; Zhang, W.; Zhu, J.; Belhabib, S.; Nouri, H. Challenges of additive manufacturing technologies from an optimization perspective. Int. J. Simul. Multidiscip. Des. Optim. 2015, 6, A9. [Google Scholar] [CrossRef][Green Version]
- Ben-Ner, A.; Siemsen, E. Decentralization and localization of production: The organizational and economic consequences of additive manufacturing (3D printing). Calif. Manag. Rev. 2017, 59, 5–23. [Google Scholar] [CrossRef]
- Huang, S.H.; Liu, P.; Mokasdar, A.; Hou, L. Additive manufacturing and its societal impact: A literature review. Int. J. Adv. Manuf. Technol. 2012, 67, 1191–1203. [Google Scholar] [CrossRef]
- Janssen, G.R.; Blankers, I.; Moolenburgh, E.; Posthumus, A. TNO: The Impact of 3d Printing on Supply Chain Management. Available online: https://repository.tudelft.nl/view/tno/uuid%3Acc288b1a-837c-4f24-8504-a45bb9636b70 (accessed on 4 June 2021).
- Velázquez, D.; Simon, A.; Helleno, A.; Mastrapa, L. Implications of additive manufacturing on supply chain and logistics. Indep. J. Manag. Prod. IJMP 2020, 11, 1279–1302. [Google Scholar] [CrossRef]
- Pereira, T.; Kennedy, J.V.; Potgieter, J. A comparison of traditional manufacturing vs additive manufacturing, the best method for the job. Procedia Manuf. 2019, 30, 11–18. [Google Scholar] [CrossRef]
- Diegel, O.; Singamneni, S.; Reay, S.; Withell, A. Tools for sustainable product design: Additive manufacturing. J. Sustain. Dev. 2010, 3, 68–75. [Google Scholar] [CrossRef]
- Newman, S.T.; Zhu, Z.; Dhokia, V.; Shokrani, A. Process planning for additive and subtractive manufacturing technologies. CIRP Ann. 2015, 64, 467–470. [Google Scholar] [CrossRef]
- Araújo, N. A manufatura aditiva uma tecnologia disruptiva no processo de desenvolvimento e fabrico de produtos. Tecnometal 2017, 230, 18–29. [Google Scholar]
- Wang, Z.; Zheng, P.; Peng, T.; Zou, J. Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives. Sci. China Technol. Sci. 2020, 63, 1600–1611. [Google Scholar] [CrossRef]
- Gardan, J. Smart materials in additive manufacturing: State of the art and trends. Virtual Phys. Prototyp. 2019, 14, 1–18. [Google Scholar] [CrossRef]
- Ryan, K.R.; Down, M.P.; Banks, C.E. Future of additive manufacturing: Overview of 4D and 3D printed smart and advanced materials and their applications. Chem. Eng. J. 2021, 403, 126162. [Google Scholar] [CrossRef]
- Zhang, Z.; Demir, K.G.; Gu, G.X. Developments in 4D-printing: A review on current smart materials, technologies, and applications. Int. J. Smart Nano Mater. 2019, 10, 205–224. [Google Scholar] [CrossRef][Green Version]
- Lee, S.M.; Lim, S. Advent of living innovation. In Living Innovation; Emerald Publishing Limited: Bingley, UK, 2018; pp. 51–62. [Google Scholar] [CrossRef]
- Müller, J.M. Business model innovation in small- and medium-sized enterprises. J. Manuf. Technol. Manag. 2019, 30, 1127–1142. [Google Scholar] [CrossRef]
- Sony, M.; Naik, S. Key ingredients for evaluating Industry 4.0 readiness for organizations: A literature review. Benchmark. Int. J. 2019, 27, 2213–2232. [Google Scholar] [CrossRef]
- Srai, J.S.; Lorentz, H. Developing design principles for the digitalisation of purchasing and supply management. J. Purch. Supply Manag. 2018, 25, 78–98. [Google Scholar] [CrossRef]
- Tulder, R.; Verbeke, A.; Piscitello, L. International business in the information and digital age. Prog. Int. Bus. Res. 2018, 13, 91–121. [Google Scholar] [CrossRef]
- Kunovjanek, M.; Knofius, N.; Reiner, G. Additive manufacturing and supply chains—A systematic review. Prod. Plan. Control. 2020, 1–21. [Google Scholar] [CrossRef]
- Montero, J.; Paetzold, K.; Bleckmann, M.; Holtmannspoetter, J. Re-design and re-manufacturing of discontinued spare parts implementing additive manufacturing in the military field. Proc. Des. 2018, 15, 1269–1278. [Google Scholar] [CrossRef]
- Boer, J.; Lambrechts, W.; Krikke, H. Additive manufacturing in military and humanitarian missions: Advantages and challenges in the spare parts supply chain. J. Clean. Prod. 2020, 257, 120301. [Google Scholar] [CrossRef]
- Akmal, J.S.; Salmi, M.; Mäkitie, A.; Björkstrand, R.; Partanen, J. Implementation of Industrial additive manufacturing: Intelligent implants and drug delivery systems. J. Funct. Biomater. 2018, 9, 41. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Zhang, J.; Zhang, J.; Vo, A.Q.; Feng, X.; Bandari, S.; Repka, M.A. Pharmaceutical additive manufacturing: A novel tool for complex and personalized drug delivery systems. AAPS PharmSciTech. 2018, 19, 3388–3402. [Google Scholar] [CrossRef] [PubMed]
- Oladapo, B.; Ismail, S.O.; Afolalu, T.D.; Olawade, D.B. Review on 3D printing: Fight against COVID-19. Mater. Chem. Phys. 2021, 258, 123943. [Google Scholar] [CrossRef] [PubMed]
- Fletcher, G. Smarter Manufacturing: Additive Manufacturing and the Digital Value Chain. 2019. Available online: https://www.engineering.com/story/smarter-manufacturing-additive-manufacturing-and-the-digital-value-chain (accessed on 4 June 2021).
- Liu, C.; Le Roux, L.; Körner, C.; Tabaste, O.; Lacan, F.; Bigot, S. Digital twin-enabled collaborative data management for metal additive manufacturing systems. J. Manuf. Syst. J. 2020, in press. [Google Scholar] [CrossRef]
- Stavropoulos, P.; Papacharalampopoulos, A.; Michail, C.K.; Chryssolouris, G. Robust additive manufacturing performance through a control oriented digital twin. Metals 2021, 11, 708. [Google Scholar] [CrossRef]
- Alogla, A.A.; Baumers, M.; Tuck, C.; Elmadih, W. The impact of additive manufacturing on the flexibility of a manufacturing supply chain. Appl. Sci. 2021, 11, 3707. [Google Scholar] [CrossRef]
- Barroqueiro, B.; Andrade-Campos, A.; Valente, R.A.F.; Neto, V. Metal additive manufacturing cycle in aerospace industry: A comprehensive review. J. Manuf. Mater. Process. 2019, 3, 52. [Google Scholar] [CrossRef][Green Version]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Araújo, N.; Pacheco, V.; Costa, L. Smart Additive Manufacturing: The Path to the Digital Value Chain. Technologies 2021, 9, 88. https://doi.org/10.3390/technologies9040088
Araújo N, Pacheco V, Costa L. Smart Additive Manufacturing: The Path to the Digital Value Chain. Technologies. 2021; 9(4):88. https://doi.org/10.3390/technologies9040088Chicago/Turabian Style
Araújo, Nuno, Vânia Pacheco, and Leonardo Costa. 2021. "Smart Additive Manufacturing: The Path to the Digital Value Chain" Technologies 9, no. 4: 88. https://doi.org/10.3390/technologies9040088