The following list contains the literature references of the whitepaper series “Bio-intelligence in Additive Manufacturing”, which will appear in four installments. 

Agrawal, R. (2021). Sustainable material selection for additive manufacturing technologies: A critical analysis of rank reversal approach. Journal of Cleaner Production, 296, 126500. https://doi.org/10.1016/j.jclepro.2021.126500

Ashby, M. F., & Gibson, L. J. (2000). Cellular Solids: Structure and Properties (2nd ed.). Cambridge University Press.

Bhatia, A., & Sehgal, A. K. (2023). Additive manufacturing materials, methods and applications: A review. Materials Today: Proceedings, 81(Part 2), 1060–1067. https://doi.org/10.1016/j.matpr.2021.04.379

Boda, B., Panda, B., & Kumar, A. (2024). Nested isotropic lattice structures for mechanical property tuning. ArXiv Preprint ArXiv:2405.11596.

Byrne, G., Damm, O., Monostori, L., Teti, R., van Houten, F., Wegener, K., Wertheim, R., & Sammler, F. (2021). Towards high performance living manufacturing systems – A new convergence between biology and engineering. CIRP Journal of Manufacturing Science and Technology, 34, 6–21. https://doi.org/10.1016/j.cirpj.2020.10.009

Castelló-Pedrero, P., & others. (2024). Integrated computational modeling of large format additive manufacturing: Developing a digital twin for material extrusion with carbon fiber-reinforced acrylonitrile butadiene styrene. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, 238(2), 332–346. https://doi.org/10.1177/14644207231219856

Chang, J., He, J., Mao, M., Zhou, W., Lei, Q., Li, X., Li, D., Chua, C. K., & Zhao, X. (2018). Advanced Material Strategies for Next-Generation Additive Manufacturing. Materials 2018, Vol. 11, Page 166, 11(1), 166. https://doi.org/10.3390/MA11010166

Chen, C. W. (2025). Hybrid Framework for Evaluating and Selecting Sustainable Materials in Product Development. International Journal of Precision Engineering and Manufacturing-Green Technology. https://doi.org/10.1007/s40684-025-00699-z

CIRC-THREAD Project Consortium. (2020). CIRC-THREAD.

Colón Quintana, J. L., Slattery, L., Pinkham, J., Keaton, J., Lopez-Anido, R. A., & Sharp, K. (2022). Effects of Fiber Orientation on the Coefficient of Thermal Expansion of Fiber-Filled Polymer Systems in Large Format Polymer Extrusion-Based Additive Manufacturing. Materials, 15, 2764. https://doi.org/10.3390/ma15082764

Compton, B. G., Post, B. K., Duty, C. E., Love, L., & Kunc, V. (2017). Thermal analysis of additive manufacturing of large-scale thermoplastic polymer composites. Additive Manufacturing, 17, 77–86. https://doi.org/10.1016/j.addma.2017.07.006

Daareyni, A., Pagone, E., Thayapararajah, S., Mokhtarian, H., Tosello, G., & Flores Ituarte, I. (2025). Intelligent manufacturing paradigms: linking design optimization and sustainability in large-area

additive manufacturing. International Journal of Advanced Manufacturing Technology, 1–10. https://doi.org/10.1007/S00170-025-15832-0/TABLES/3

David, I., Shao, G., Gomes, C., Tilbury, D., & Zarkout, B. (2025). Interoperability of Digital Twins: Challenges, Success Factors, and Future Research Directions. Lecture Notes in Computer Science, 15223 LNCS, 27–46. https://doi.org/10.1007/978-3-031-75390-9_3

Deaton, J. D., & Grandhi, R. V. (2014). A survey of structural and multidisciplinary continuum topology optimization: Post 2000. Structural and Multidisciplinary Optimization, 49(1), 1–38. https://doi.org/10.1007/S00158-013-0956-Z/METRICS

Delva, L., Hubo, S., Cardon, L., & Ragaert, K. (2018). On the role of flame retardants in mechanical recycling of solid plastic waste. Waste Management, 82, 198–206. https://doi.org/10.1016/j.wasman.2018.10.030

Digital Intelligent MOdular FACtories | DIMOFAC | Project | Fact Sheet | H2020 | CORDIS | European Commission. (n.d.). Retrieved November 18, 2025, from https://cordis.europa.eu/project/id/870092

Eclipse BaSyxTM. (n.d.). Retrieved November 18, 2025, from https://basyx.org/

El Hami, A., & Radi, B. (2021a). Constrained Nonlinear Optimization. Optimizations and Programming, 193–227. https://doi.org/10.1002/9781119818243.CH7

El Hami, A., & Radi, B. (2021b). Optimizations and programming: Linear, non-linear, dynamic, stochastic and applications with matlab. Optimizations and Programming: Linear, Non-Linear, Dynamic, Stochastic and Applications with Matlab, 1–262. https://doi.org/10.1002/9781119818243

ElMaraghy, H., & ElMaraghy, W. (2022). Adaptive Cognitive Manufacturing System (ACMS) – a new paradigm. International Journal of Production Research, 1–14. https://doi.org/10.1080/00207543.2022.2078248

Emera, A., De Marchi, M., Hofer, A., Mark, B. G., Kerschbaumer, W., Rauch, E., & Matt, D. T. (2025). Examples of potential applications of bio-intelligent manufacturing. Procedia Computer Science, 253(1), 2196–2205. https://doi.org/10.1016/j.procs.2025.01.280

European Commission. (2019). The European Green Deal. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640

European Commission. (2020). A new Circular Economy Action Plan – For a cleaner and more competitive Europe. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020DC0098

European Commission. (2021a). Fit for 55. https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal/delivering-european-green-deal_en

European Commission. (2021b). Pathway to a Healthy Planet for All – EU Action Plan: “Towards Zero Pollution for Air, Water and Soil.” https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52021DC0400

European Commission. (2021c). Updating the 2020 New Industrial Strategy: Building a stronger Single Market for Europe’s recovery. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52021DC0350

European Commission. (2022). REPowerEU Plan. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:52022DC0230

European Commission. (2023). European Climate Pact. https://climate-pact.europa.eu

European Union. (2023). Directive (EU) 2023/2413 of the European Parliament and of the Council of 18 October 2023 on the promotion of the use of energy from renewable sources (recast). https://eur-lex.europa.eu/eli/dir/2023/2413/oj

European Union. (2024). Regulation (EU) 2024/1252 of the European Parliament and of the Council of 11 April 2024 establishing a framework for ensuring a secure and sustainable supply of critical raw materials and amending Regulations (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1724 and (EU) 2019/1020 (Critical Raw Materials Act). https://eur-lex.europa.eu/eli/reg/2024/1252/oj

Fang, Q., Xiong, G., Zhou, M. C., Tamir, T. S., Yan, C. B., Wu, H., Shen, Z., & Wang, F. Y. (2024). Process Monitoring, Diagnosis and Control of Additive Manufacturing. IEEE Transactions on Automation Science and Engineering, 21(1), 1041–1067. https://doi.org/10.1109/TASE.2022.3215258

Freeman, F. S. H. B., Chechik, L., & Todd, I. (2020). Beat the machine (learning): metal additive manufacturing and closed loop control. Physics Education, 55(5), 055012. https://doi.org/10.1088/1361-6552/AB9957

GAIA-X AISBL. (2023). Architecture Document (latest edition). https://docs.gaia-x.eu/

Galos, J., Das, R., Michael, P., & Mouritz, A. P. (2022). Review of balsa core sandwich composite structures. Materials & Design, 221, 111013. https://doi.org/10.1016/j.matdes.2022.111013

Goh, G. D., Wong, K. K., Tan, N., Seet, H. L., & Nai, M. L. S. (2024). Large-format additive manufacturing of polymers: a review of fabrication processes, materials, and design. Virtual and Physical Prototyping, 19(1), e2336160. https://doi.org/10.1080/17452759.2024.2336160

GRETA. (n.d.). Retrieved November 21, 2025, from https://greta.test.spslab.ch/info/

Gu, G. X., Su, I., Sharma, S., Voros, J. L., Qin, Z., & Buehler, M. J. (2016). Three-Dimensional-Printing of Bio-Inspired Composites. Journal of Biomechanical Engineering, 138(2). https://doi.org/10.1115/1.4032423

Haber, R. E., Juanes, C., Del Toro, R., & Beruvides, G. (2015). Artificial cognitive control with self-x capabilities: A case study of a micro-manufacturing process. Computers in Industry, 74, 135–150. https://doi.org/10.1016/J.COMPIND.2015.05.001

Ha, C. S., & others. (2023). Rapid Inverse Design of Metamaterials via Machine Learning. Nature Communications, 14, 5765.

Harish, A., Li, Z., & Zhang, Y. (2022). Bio-Inspired TPMS Lattices for Lightweight Structural Applications. Additive Manufacturing, 55, 102879.

IDTA – working together to promote the Digital Twin. (n.d.). Retrieved November 21, 2025, from https://industrialdigitaltwin.org/en/

International Data Spaces Association (IDSA). (2023). Reference Architecture Model 4.0. https://internationaldataspaces.org/publications/ids-ram/

Ituarte, I. F., Pagone, E., Daareyni, A., Thayapararajah, S., & Tosello, G. (2025). Enabling sustainability-by-design with multi-disciplinary computer aided systems. CIRP Annals, 74(1), 209–213. https://doi.org/10.1016/J.CIRP.2025.03.019

Jin, Z., Zhang, Z., Demir, K., & Gu, G. X. (2020). Machine Learning for Advanced Additive Manufacturing. Matter, 3(5), 1541–1556. https://doi.org/10.1016/J.MATT.2020.08.023

Kawalkar, Dubey, & Lokhande. (2022). A review for advancements in standardization for additive manufacturing. Materials Today: Proceedings, 50(5), 1983–1990. https://doi.org/10.1016/j.matpr.2021.09.333

Kellens, K., Renaldi, R., Dewulf, W., Kruth, J.-P., & Duflou, J. R. (2017). Environmental impact of additive manufacturing processes: Does AM contribute to a more sustainable way of part manufacturing? CIRP Annals, 66(1), 583–586.

Kephart, J. O., & Chess, D. M. (2003). The vision of autonomic computing. Computer, 36(1), 41–50. https://doi.org/10.1109/MC.2003.1160055

Kim, H., Lin, Y., & Tseng, T. L. B. (2018). A review on quality control in additive manufacturing. Rapid Prototyping Journal, 24(3), 645–669. https://doi.org/10.1108/RPJ-03-2017-0048/FULL/XML

Kravchenko, M., Pigosso, D. C. A., & McAloone, T. C. (2020). Circular economy enabled by additive manufacturing: potential opportunities and key sustainability aspects. Proceedings of NordDesign. https://doi.org/10.35199/NORDDESIGN2020.4

Laycock, B., Pratt, S., & Halley, P. (2023). A perspective on biodegradable polymer biocomposites – from processing to degradation. Functional Composite Materials, 4, 10. https://doi.org/10.1186/s42252-023-00048-w

Libonati, F., Vergani, L., & Brugo, T. (2019). Bone-Inspired Fibre-Reinforced Composites with Enhanced Fracture Toughness. Composites Science and Technology, 181, 107702.

Lim, B., & Zohren, S. (2021). Time-series forecasting with deep learning: a survey. Philosophical Transactions of the Royal Society A, 379(2194). https://doi.org/10.1098/RSTA.2020.0209

Liu, H., Antwi-Afari, M. F., Mi, H., & Liu, C. (2023). Research on the feasibility of polyethylene terephthalate foam used in wind turbine blades. Environmental Progress & Sustainable Energy, 42(1), e13956. https://doi.org/10.1002/ep.13956

Liu, X., & others. (2024). High Energy Absorption Nacre-Like Calcium Silicate Hydrate (C-S-H) Composite Toward Elastic Cementitious Materials. Advanced Functional Materials, 34, 2307437. https://doi.org/10.1002/adfm.202307437

Manikandan, S., Vickram, S., Deena, S. R., Subbaiya, R., & Karmegam, N. (2024). Critical review on fostering sustainable progress: An in-depth evaluation of cleaner production methodologies and pioneering innovations in industrial processes. Journal of Cleaner Production, 452, 142207. https://doi.org/10.1016/J.JCLEPRO.2024.142207

McKay, I., Vargas, J., Yang, L., & Felfel, R. M. (2024). A Review of Natural Fibres and Biopolymer Composites: Progress, Limitations, and Enhancement Strategies. Materials, 17(19), 4878. https://doi.org/10.3390/ma17194878

Mishnaevsky Jr., L. (2017). Materials for Wind Turbine Blades: An Overview. Materials, 10(11), 1285. https://doi.org/10.3390/ma10111285

Modrak, V., Bednar, S., Onofrejova, D., & Trojanova, M. (2024). A Review on Reinforcement Learning in Production Scheduling: An Inferential Perspective. Algorithms, 17(8), 343.

Monostori, L., Kádár, B., Bauernhansl, T., Kondoh, S., Kumara, S., Reinhart, G., Sauer, O., Schuh, G., Sihn, W., & Ueda, K. (2016). Cyber-physical systems in manufacturing. CIRP Annals, 65(2), 621–641.

Moreno Nieto, D., & Molina, S. I. (2020). Large-format fused deposition additive manufacturing: a review. Rapid Prototyping Journal, 26(5), 793–799. https://doi.org/10.1108/RPJ-05-2018-0126

Murdy, P., & Hughes, S. (2020). Investigating Core Gaps and the Development of Subcomponent Validation Methods for Wind Turbine Blades (Preprint) (Issue CP-5000-75249).

Musthafa, H. S. N., Singh, P., & Gokhale, A. M. (2024). Voronoi-Based Trabecular Bone-Mimicking Lattices: Design, Fabrication and Mechanical Characterisation. Materials & Design, 230, 112058.

Naboni, R., & Kunic, A. (2019). Functionally Graded Trabecular Tectonics: Bone-Inspired 3D-Printed Structures. Gestão & Tecnologia de Projetos, 14(2).

Nievas, N., Pagès-Bernaus, A., Bonada, F., Echeverria, L., & Domingo, X. (2024). Reinforcement Learning for Autonomous Process Control in Industry 4.0: Advantages and Challenges. Applied Artificial Intelligence, 38(1). https://doi.org/10.1080/08839514.2024.2383101

NREL. (2023). Using Large-Scale Additive Manufacturing for Wind-Turbine Blade Core Structures.

Owens, Das, & Bortner. (2022). Accelerating heat transfer modeling in material extrusion AM: From desktop to big area. Additive Manufacturing, 55, 102853. https://doi.org/10.1016/j.addma.2022.102853

Panzer, M., & Bender, B. (2022). Deep reinforcement learning in production systems: a systematic literature review. International Journal of Production Research, 60(13), 4316–4341. https://doi.org/10.1080/00207543.2021.1973138

Pappas, J. M., Thakur, A. R., Leu, M. C., & others. (2021). A parametric study and characterization of additively manufactured continuous carbon fiber reinforced composites for high-speed 3D printing. International Journal of Advanced Manufacturing Technology, 113, 2137–2151. https://doi.org/10.1007/s00170-021-06723-1

Patel, A., & Taufik, M. (2024). Extrusion-Based Technology in Additive Manufacturing: A Comprehensive Review. Arabian Journal for Science and Engineering, 49, 1309–1342. https://doi.org/10.1007/s13369-022-07539-1

Peckham, O., & others. (2024). Investigating and Characterizing the Systemic Variability When Using Generative Design for Additive Manufacturing. Applied Sciences, 14(11), 4750. https://doi.org/10.3390/app14114750

Pender, K., Romoli, F., Bacharoudis, K., & others. (2025). Evaluating priority strategies for decarbonising offshore wind turbine blades through lifecycle assessment. Clean Technologies and Environmental Policy, 27, 2919–2936. https://doi.org/10.1007/s10098-024-03033-4

Pignatelli, F., & Percoco, G. (2022). An application- and market-oriented review on large format additive manufacturing, focusing on polymer pellet-based 3D printing. Progress in Additive Manufacturing, 7, 1363–1377. https://doi.org/10.1007/s40964-022-00309-3

Ramful, R. (2025). A review on development of eco-friendly natural fiber-reinforced composite filaments for 3D printing: Fabrication and characteristics. Materials Science in Additive Manufacturing 2025, 4(1), 8533, 4(1), 8533. https://doi.org/10.36922/MSAM.8533

Ren, H., & others. (2024). Concurrent optimization of structural topology and toolpath for additive manufacturing of continuous fiber-reinforced polymer composites. Computer Methods in Applied Mechanics and Engineering, 430, 117227. https://doi.org/10.1016/j.cma.2024.117227

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