A fuzzy mixed-integer robust design optimization model to obtain optimum settings of both qualitative and quantitative input variables under uncertainty

ÖZDEMİR A.

ENGINEERING OPTIMIZATION, cilt.55, sa.4, ss.599-614, 2023 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 55 Sayı: 4
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1080/0305215x.2021.2016733
  • Dergi Adı: ENGINEERING OPTIMIZATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.599-614
  • Anahtar Kelimeler: Quality, fuzzy modelling, robust design, qualitative and quantitative input variables, optimization, SURFACE OPTIMIZATION, GENETIC ALGORITHM
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Quality improvement is the most effective activity for the process and product development cycle, while minimizing the process and product variation. For this particular purpose, robust design models are proposed to reduce the process and product variance. However, the majority of robust design models in the literature deals with certain situations. This article has four objectives. First, an experimental design matrix is generated for both qualitative and quantitative input variables under uncertainty. Secondly, triangular fuzzy numbers are used to measure the values of a response variable while dealing with an alpha-level cut strategy. Fitted fuzzy mean, standard deviation and variance response functions are also obtained. Thirdly, a fuzzy mixed-integer robust design optimization model is proposed to obtain the optimum operating conditions of input variables under uncertainty. Finally, a numerical example is presented to show the effectiveness of the proposed fuzzy-based methodology development for an uncertain environment.