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Makale detayı · 2024 · article

Cylinder and piston: Material selection in the design phase

YÖKSİS OpenAlex Açık erişim · gold
Yıl2024
Atıf3OpenAlex
Yüzdelik%53,3
FWCI0,421,00 = dünya ortalaması
Scopus (SJR)Q3

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıJournal of Applied Engineering Science
  • Katalog eşleşmesi (ISSN)Journal of Applied Engineering Science
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

The piston and cylinder constitute an inseparable pair, playing a crucial role in both the mechanical and hydraulic industries. They are frequently employed to convert linear motion into rotational motion in various types of engines and are especially valuable for heavy-duty applications. Material selection for these components is conducted during the product design phase. This study aimed to identify the optimal material for each type of product. To determine the best material, a ranking of materials was carried out using the CoCoSo (Combined Compromise Solution) method, with scores for criteria calculated using the Entropy method. Nine materials for cylinder construction were evaluated, including S355JR, S275JR, S235JR, BS97007M20, R35, R45, IS1030GRADE, AISI304, and 60-40-18. Additionally, seven materials for piston construction were considered: 332-T5, A336, 242-T5, 333.0-F, A213.0 F, AISI308, and A319.0F. The Entropy-CoCoSo approach was employed to rank the materials for each case (cylinder material and piston material). The results indicated that AISI304 is the optimal material for cylinder manufacturing, while A336 is the best material for piston manufacturing. Furthermore, the study extensively examined the impact of different weighting methods (Entropy, WENSLO, CRITIC, ROC, RS, EW) and normalization techniques (sum, vector, max, max-min, peldschus, decimal) on CoCoSo method results using an innovative sensitivity analysis approach, analyzing the techniques according to their sensitivity levels.

Konular

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  1. 2026 SD–MCRAT: Standard deviation–multiple criteria ranking by alternative trace for multi-attribute decision-makingAtıf 0 · OpenAlex

Yazarlar

3
  1. Do Duc Trung 1
  2. NAZLI ERSOY OSMANİYE KORKUT ATA ÜNİVERSİTESİ 2
  3. Vo Thi Nhu Uyen 3