Concept design evaluation by using Z-axiomatic design

AYDOĞAN S., Gunay E. E., AKAY D., Kremer G. E. O.

COMPUTERS IN INDUSTRY, cilt.122, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 122
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.compind.2020.103278
  • Dergi Adı: COMPUTERS IN INDUSTRY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Concept design evaluation, Z-numbers, Axiomatic design, Uncertainty and subjectivity, CONCEPT SELECTION, PRODUCT, EXTENSION, VIKOR, AHP
  • Hacettepe Üniversitesi Adresli: Hayır

Özet

Capturing the uncertainty associated with a decision maker (DM)'s judgments and preferences is one of the most challenging parts of concept design evaluation as it depends on subjective linguistic terms. To address this drawback, we propose a novel approach for concept design evaluation that incorporates Z-number and axiomatic design (AD) concepts. Although pertinent literature advocates for the capture of uncertain information originating from DMs, the relevant need for information reliability has not been addressed. By incorporating Z-numbers, the confidence level of a decision or its reliability is taken into consideration, thus a more comprehensive perception of the DM is recorded. Then, these judgments and preferences are incorporated to AD to select the best design concept. Using data from the published literature, a case study is conducted to assess the impact of information reliability and the DM's risk attitude with regards to available design options. The proposed approach is also compared with previously developed methods in order to show its benefits. The results demonstrate that the reliability of the information has a significant impact on final results; and assessment of confidence, or reliability of information, enhances the success for better decision-making. (c) 2020 Published by Elsevier B.V.