Opti-Waffle: A Technological Furniture Design and Manufacturing Model

Year 2023, Volume: 6 Issue: 4, 589 - 599, 15.10.2023

Erdem Yıldırım

https://doi.org/10.34248/bsengineering.1344142

Abstract

Parametric design allows the use of computers and systems that can make decisions beyond human capacity, such as machine learning, through optimization in design and manufacturing. From this point of view, it is aimed to shape and manufacture the design by minimizing the subjective decisions of the designers by using various algorithmic methods and structural optimization to provide ergonomics in a furniture design. As the subject of the study, a meeting table for 8 people was discussed. In the process, 'artificial intelligence supported inspiration board', 'parametric design', 'human-computer interaction and sensors', 'topology optimization', 'observation in augmented reality' and 'computer-aided manufacturing' techniques were used sequentially. After the assembly was completed, the product obtained was finally evaluated in terms of structure-function relationship.

Keywords

Parametric design, Topology optimization, Waffle structure, Computer-Aided ergonomics

References

• Agassi J, Wiezenbaum J. 1976. Computer power and human reason: from judgment to calculation. Technol Culture, 17(4): 813–816.
• Arpak A, Sass L, Knight T. 2009. A meta-cognitive inquiry into digital fabrication exploring the activity of designing and making of a wall screen. Proceedings of the 27th Conference on Education and Research in Computer Aided Architectural Design in Europe, September 16-19, Istanbul, Türkiye, pp: 475–48.
• Bañón C, Raspall F. 2021. 3D Printing architecture workflows applications and trends. Springer, London, UK, pp: 127.
• Bickel B, Cignoni P, Malomo L, Pietroni N. 2018. State of the art on stylized fabrication. Comput Graphics Forum, 37(6): 325–342.
• Bikas H, Stavridis J, Stavropoulos P, Chryssolouris G. 2015. Design and topology optimization for additively manufactured structural parts: a formula student case study. Proceedings of the 6th BETA CAE International Conference, Jun 10-12, Thessaloniki, Greece, 1-6.
• Cui Q, Zhang H, Pawar S. S, Yu C, Feng X, Qiu S. 2022. Topology optimization for 3D- printable large-scale metallic hollow structures with self-supporting. Proceedings of the 27th Conference on Computer Aided Architectural Design Research in Asia (CAADRIA), 19-21 April, Nanjing, China, pp: 101–110.
• Davis D, Peters B. 2013. Design ecosystems: Customising the architectural design environment with software plug-ins. Architectural Design, 83(2): 124–131.
• Dumitraşcu AI, Hapurne TM, Bliuc I, Corduban CG, Nica RM. 2018. Waffle structure optimization in terms of energy efficiency and spatial geometry for a single family house. Mater Sci Eng, 444: 082013.
• Eloy S, Dias MS, Lopes PF, Vilar E. 2016. Digital technologies in architecture and engineering: exploring an engaged interaction within curricula. In Fonseca D, Redondo E, ediors. Handbook of Research on Applied E-Learning in Engineering and Architecture Education. IGI Global PA, Hershey, USA, 368–402.
• Food4Rhino. 2023. URL: https://www.food4rhino.com/en/browse?lang=enandf[0]=im_field_unified_type%3A773andf[1] =im_field_platform_app%3A720 (accessed date: February 17, 2023).
• Goodfellow IJ, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Bengio Y. 2014. Generative adversarial nets. Advances Neural Inform Proc Syst, 3(1): 2672–2680.
• Halle A, Campanile LF, Hasse A. 2021. An artificial intelligence–assisted design method for topology optimization without pre-optimized training data. Applied Sci, 11(19): 1–17.
• Indrawan SE. 2016. Design for environment and form findings through digital fabrication. J Architect Built Environ, 44(2): 171–178.
• Jain AK, Mao J. 1996. Artificial neural networks: A Tutorial. Comput, 29(3): 31–44.
• Jain A, Mildenhall B, Barron JT, Abbeel P, Poole B. 2022. Zero-shot text-guided object generation with dream fields. Comput Sci, 2022: 857–866.
• Kazakis G, Kanellopoulos I, Sotiropoulos S, Lagaros ND. 2017. Topology optimization aided structural design: Interpretation computational aspects and 3D printing. Heliyon 3(10): 1-33.
• Liu Z, Wang Y, Qi X, Fu C.-W. 2022. Towards implicit text-guided 3d shape generation. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 14-19, Seattle, WA, USA, 17896–17906.
• Lun R, Zhao W. 2015. A survey of applications and human motion recognition with microsoft kinect. Inter J Pattern Recog Artificial Intel, 5: 1555008.
• Lynn G. 1998. Folds bodies, blobs : collected essays. Bruxelles: La Lettre Volée, New Jersey, USA, 240.
• Lynn G. 1999. Animate form. Princeton Architectural Press, New Jersey, USA, 128.
• Ma J, Li Z, Zhao ZL, Xie YM. 2021. Creating novel furniture through topology optimization and advanced manufacturing. Rapid Prototyping J, 27(9): 1749–1758.
• Michell AGM. 1904. The limits of economy of material in frames structures. Philosophical Magazine, 6(8): 589–597.
• Milgram P, Kishino F. 1994. A Taxonomy of mixed reality visual displays. IEICE Transactions Inform Syst, E77-D(12): 1–15.
• Nadkarni PM, Ohno-Machado L, Chapman WW. 2011. Natural language processing: An introduction. J American Medl Inform Assoc, 18: 544–551.
• Niemann S, Kolesnikov B, Lohse-Busch H, Hühne C, Querin O, Toropov VV, Liu D. 2013. The use of topology optimisation in the conceptual design of next generation lattice composite aircraft fuselage structures. Aeronautical J, 117(3978): 1139–1154.
• Rade J, Balu A, Herron E, Pathak J, Ranade R, Sarkar S, Krishnamurthy A. 2021. Algorithmically-consistent deep learning frameworks for structural topology optimization. Engin Applicat Artificial Intell 106(11): 104483.
• Rutten D, McNeel R. 2007. Grasshopper3D. Seattle: Robert McNeel, Associates, Seattle, WA, USA, 251.
• Schmid V. 2010. Metropol parasol: A new plaza and a unique timber mega structure right in the heart of Seville. Large Struct Infrastructures Environment Constr Urban Areas, 2010: 196–197.
• Schumacher P. 2009. Parametricism: A new global style for architecture and urban design. Architectural Design, 79(4): 14–23.
• Schumacher P. 2011. The Autopoiesis of architecture volume I: a new framework for architecture. John Wiley, Sons Ltd, London, UK, 480.
• Schumacher P. 2017. Tectonism in architecture design and fashion: Innovations in digital fabrication as stylistic drivers. Architectural Design, 87(6): 106–113.
• Sun Y, Liu Y, Xu L, Lueth TC. 2019. Design of a disposable compliant medical forceps using topology optimization techniques. Proceedings of IEEE International Conference on Robotics and Biomimetics ROBIO, December 6-8, Dali, China, 1-6.
• Tyflopoulos E, Steinert M. 2022. A comparative study of the application of different commercial software for topology optimization. Applied Sci, 12(2): 1– 23.
• Vinyals O, Toshev A, Bengio S, Erhan D. 2015. Show and tell: a neural image caption generator. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, Boston, MA, USA, 3156–3164.
• Wynne Z, Buchanan C, Kyvelou P, Gardner L, Kromanis R, Stratford T, Reynolds TPS. 2022. Dynamic testing and analysis of the world’s first metal 3d printed bridge. Case Stud Construct Mater, 17(e01541): 1–15.
• Zhou M, Rozvany GIN. 1991. The COC algorithm Part II: Topological geometrical and generalized shape optimization. Comput Methods Appl Mechan Engin, 89: 309–336.
• Zhuang X, Ju Y, Yang A, Luisa Caldas. 2023. Synthesis and generation for 3D architecture volume with generative modeling. Inter J Architect Comput, 1(1): 1–18.