Araştırma Makalesi
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Yapay Zeka Destekli Kavramsal Tasarım: Tekerlekli Sandalye Tasarım Seçenekleri Değerlendirmede Bulanık Mantık Kullanımı

Yıl 2021, Cilt: 7 Sayı: 3, 309 - 319, 31.12.2021

Öz

Mühendislik tasarım işlemi; işlevsellik, üretilebilirlik, estetik, maliyet gibi birçok parametreyi hesaba katma ve optimize etmeyi içerir. Tüm bu parametreleri özenli dikkate alabilmek için sistematik tasarım yaklaşımı kullanılabilir. Önce ihtiyaç ve sınırlayıcıları karşılayacak tasarım seçenekleri oluşturulur ve sonra da bunlar arasından ideali belirleyecek değerlendirme ve seçimler yapılır. Ancak, ürün yaşam döngüsündeki kısalmalar tasarım ve geliştirme süreçlerini de kısalmasını gerekli kılmıştır. Yapay zekâ teknolojileri, erken tasarım aşaması değerlendirme ve seçim işlemlerini hızlandırmaya yardımcı olabilir. Bu çalışmada Pahl ve Beitz’in Sistematik tasarım yaklaşımına dâhil edilen bulanık mantık yöntemi ile tasarım değerlendirmesi yapılmaktadır. Yöntemin geçerlilik ve etkinliği bir tekerlekli sandalye kavramsal tasarımı ile gösterilmiştir. Ayrıca kullanılan yöntem ve normal kavramsal tasarım yöntem sonuçları da karşılaştırılmıştır. Kavramsal tasarımda bulanık mantık kullanımı basit ve kolay anlaşılır olması yanında hızlı, hassas ve kapsamlı değerlendirmeler de sağlamaktadır.

Kaynakça

  • [1] M. Cantamessa, F. Montagna, S. Altavilla, and A. Casagrande-Seretti, "Data-driven design: The new challenges of digitalization on product design and development," Design Science, vol. 6, no. 27, pp. 1-33, September 2020. doi: https://doi.org/10.1017/dsj.2020.25.
  • [2] H. R. Börklü, N. Yüksel, K. Çavdar, and H. K. Sezer, "A practical application for machine design education," Journal of Advanced Mechanical Design, Systems, and Manufacturing, vol. 12, no. 2, pp. 1-11, March 2018. doi: https://doi.org/10.1299/jamdsm.2018jamdsm0036.
  • [3] H. R. Börklü, Mühendislik Tasarımı: Sistematik Yaklaşım. Ankara: Hatiboğlu Yayınları, 2010.
  • [4] G. Pahl and W. Beitz, Engineering Design: A systematic approach. Springer, London, 1997.
  • [5] S. Pugh, Total design: integrated methods for successful product engineering. Wokingham: Addison-Wesley, 1991, p. 278.
  • [6] D. G. Ullman, The Mechanical Design Process. McGraw: Hill Inc, 1991.
  • [7] Z. Ayağ, "A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment," IIE Transactions, vol. 37, no. 9, pp. 827-842, September 2005. doi: https://doi.org/10.1080/07408170590969852.
  • [8] Z. Ayağ and R. G. Özdemir, "A hybrid approach to concept selection through fuzzy analytic network process," Computers & Industrial Engineering, vol. 56, no. 1, pp. 368-379, February 2009. doi: https://doi.org/10.1016/j.cie.2008.06.011.
  • [9] H. Malekly, S. Meysam Mousavi, and H. Hashemi, "A fuzzy integrated methodology for evaluating conceptual bridge design," Expert Systems with Applications, vol. 37, no. 7, pp. 4910-4920, July 2010. doi: https://doi.org/10.1016/j.eswa.2009.12.024.
  • [10] K.-S. Chin, A. Chan, and J.-B. Yang, "Development of a fuzzy FMEA based product design system," The International Journal of Advanced Manufacturing Technology, vol. 36, no. 7, pp. 633-649, March 2008. doi: https://doi.org/10.1007/s00170-006-0898-3.
  • [11] A. Mohebbi, S. Achiche, and L. Baron, "Multi-criteria fuzzy decision support for conceptual evaluation in design of mechatronic systems: a quadrotor design case study," Research in Engineering Design, vol. 29, no. 3, pp. 329-349, July 2018. doi: https://doi.org/10.1007/s00163-018-0287-6.
  • [12] H.-Z. Huang, Y. Liu, Y. Li, L. Xue, and Z. Wang, "New evaluation methods for conceptual design selection using computational intelligence techniques," Journal of Mechanical Science and Technology, vol. 27, no. 3, pp. 733-746, March 2013. doi: https://doi.org/10.1007/s12206-013-0123-x.
  • [13] R. Belohlavek and G. J. Klir, Concepts and Fuzzy Logic. London: The MIT Press, 2011.
  • [14] R. Sarfaraz Khabbaz, B. Dehghan Manshadi, A. Abedian, and R. Mahmudi, "A simplified fuzzy logic approach for materials selection in mechanical engineering design," Materials & Design, vol. 30, no. 3, pp. 687-697, March 2009. doi: https://doi.org/10.1016/j.matdes.2008.05.026.
  • [15] L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, no. 3, pp. 338-353, June 1965. doi: https://doi.org/10.1016/S0019-9958(65)90241-X.
  • [16] C. R. Alavala, Fuzzy Logic and Neural Network: Basic Concept & Application. New Delhi: New Age International Limited, 2008.
  • [17] F. Dernoncourt, "Introduction to fuzzy logic," Massachusetts Institute of Technology, vol. 21, 2013.
  • [18] M. Mayda and H. R. Börklü, "An integration of TRIZ and the systematic approach of Pahl and Beitz for innovative conceptual design process," Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 36, no. 4, pp. 859-870, October 2014. doi: https://doi.org/10.1007/s40430-013-0106-y.

Artifical Intelligence Asisted Conceptual Design: Using Fuzzy Logic For the Evaluation of Design Variants of A Wheelchair

Yıl 2021, Cilt: 7 Sayı: 3, 309 - 319, 31.12.2021

Öz

The engineering design process is a comprehensive process in which many parameters such as functionality, manufacturability, aesthetics, and cost are considered and optimized. Systematic design methods can be used to take into account these parameters and not to overlook the details. First of all, design options are created in line with the determined goals, and then some selection and evaluation processes are made to determine the ideal design among these options. However, the shortening of the product lifetimes has made it necessary to shorten the design and development processes. Artificial intelligence technologies can help designers speed up selection and evaluation processes in the early design phase. This study, it is aimed to evaluate the design options by including the fuzzy logic method in the systematic design approach of Pahl and Beitz. The validity and effectiveness of the method were demonstrated by a wheelchair conceptual design. In addition, the presented method has been compared with the traditional conceptual design method in terms of its results. The use of the fuzzy logic method in conceptual design provides fast, sensitive, and comprehensive evaluation besides being simple and easy to understand.

Kaynakça

  • [1] M. Cantamessa, F. Montagna, S. Altavilla, and A. Casagrande-Seretti, "Data-driven design: The new challenges of digitalization on product design and development," Design Science, vol. 6, no. 27, pp. 1-33, September 2020. doi: https://doi.org/10.1017/dsj.2020.25.
  • [2] H. R. Börklü, N. Yüksel, K. Çavdar, and H. K. Sezer, "A practical application for machine design education," Journal of Advanced Mechanical Design, Systems, and Manufacturing, vol. 12, no. 2, pp. 1-11, March 2018. doi: https://doi.org/10.1299/jamdsm.2018jamdsm0036.
  • [3] H. R. Börklü, Mühendislik Tasarımı: Sistematik Yaklaşım. Ankara: Hatiboğlu Yayınları, 2010.
  • [4] G. Pahl and W. Beitz, Engineering Design: A systematic approach. Springer, London, 1997.
  • [5] S. Pugh, Total design: integrated methods for successful product engineering. Wokingham: Addison-Wesley, 1991, p. 278.
  • [6] D. G. Ullman, The Mechanical Design Process. McGraw: Hill Inc, 1991.
  • [7] Z. Ayağ, "A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment," IIE Transactions, vol. 37, no. 9, pp. 827-842, September 2005. doi: https://doi.org/10.1080/07408170590969852.
  • [8] Z. Ayağ and R. G. Özdemir, "A hybrid approach to concept selection through fuzzy analytic network process," Computers & Industrial Engineering, vol. 56, no. 1, pp. 368-379, February 2009. doi: https://doi.org/10.1016/j.cie.2008.06.011.
  • [9] H. Malekly, S. Meysam Mousavi, and H. Hashemi, "A fuzzy integrated methodology for evaluating conceptual bridge design," Expert Systems with Applications, vol. 37, no. 7, pp. 4910-4920, July 2010. doi: https://doi.org/10.1016/j.eswa.2009.12.024.
  • [10] K.-S. Chin, A. Chan, and J.-B. Yang, "Development of a fuzzy FMEA based product design system," The International Journal of Advanced Manufacturing Technology, vol. 36, no. 7, pp. 633-649, March 2008. doi: https://doi.org/10.1007/s00170-006-0898-3.
  • [11] A. Mohebbi, S. Achiche, and L. Baron, "Multi-criteria fuzzy decision support for conceptual evaluation in design of mechatronic systems: a quadrotor design case study," Research in Engineering Design, vol. 29, no. 3, pp. 329-349, July 2018. doi: https://doi.org/10.1007/s00163-018-0287-6.
  • [12] H.-Z. Huang, Y. Liu, Y. Li, L. Xue, and Z. Wang, "New evaluation methods for conceptual design selection using computational intelligence techniques," Journal of Mechanical Science and Technology, vol. 27, no. 3, pp. 733-746, March 2013. doi: https://doi.org/10.1007/s12206-013-0123-x.
  • [13] R. Belohlavek and G. J. Klir, Concepts and Fuzzy Logic. London: The MIT Press, 2011.
  • [14] R. Sarfaraz Khabbaz, B. Dehghan Manshadi, A. Abedian, and R. Mahmudi, "A simplified fuzzy logic approach for materials selection in mechanical engineering design," Materials & Design, vol. 30, no. 3, pp. 687-697, March 2009. doi: https://doi.org/10.1016/j.matdes.2008.05.026.
  • [15] L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, no. 3, pp. 338-353, June 1965. doi: https://doi.org/10.1016/S0019-9958(65)90241-X.
  • [16] C. R. Alavala, Fuzzy Logic and Neural Network: Basic Concept & Application. New Delhi: New Age International Limited, 2008.
  • [17] F. Dernoncourt, "Introduction to fuzzy logic," Massachusetts Institute of Technology, vol. 21, 2013.
  • [18] M. Mayda and H. R. Börklü, "An integration of TRIZ and the systematic approach of Pahl and Beitz for innovative conceptual design process," Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 36, no. 4, pp. 859-870, October 2014. doi: https://doi.org/10.1007/s40430-013-0106-y.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Makine Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Nurullah Yüksel 0000-0003-4593-6892

Hüseyin Rıza Börklü 0000-0001-5104-9195

Yayımlanma Tarihi 31 Aralık 2021
Gönderilme Tarihi 20 Mayıs 2021
Kabul Tarihi 30 Kasım 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 7 Sayı: 3

Kaynak Göster

IEEE N. Yüksel ve H. R. Börklü, “Yapay Zeka Destekli Kavramsal Tasarım: Tekerlekli Sandalye Tasarım Seçenekleri Değerlendirmede Bulanık Mantık Kullanımı”, GMBD, c. 7, sy. 3, ss. 309–319, 2021.

Gazi Journal of Engineering Sciences (GJES) publishes open access articles under a Creative Commons Attribution 4.0 International License (CC BY) 1366_2000-copia-2.jpg