Multi-objective optimization of AWJM parameters for Ti-6Al-4V hole production using polynomial regression modeling, MO-Jaya algorithm, and COCOSO MCDM


Abouhawa M., Eisa A., Fattouh M., SALUNKHE S. S.

Reviews on Advanced Materials Science, cilt.65, sa.1, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 65 Sayı: 1
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1515/rams-2025-0256
  • Dergi Adı: Reviews on Advanced Materials Science
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals, Academic Search Ultimate (EBSCO)
  • Anahtar Kelimeler: AWJM, COCOSO, hole quality, MO-Jaya, polynomial regression, Ti-6Al-4V
  • Gazi Üniversitesi Adresli: Evet

Özet

Ti-6Al-4V is a critical material in aerospace and biomedical industries, but its low thermal conductivity and high chemical reactivity make it difficult to machine conventionally. Abrasive Water Jet Machining (AWJM) offers a non-thermal alternative for high-quality processing. This study focuses on the multi-objective optimization of AWJM parameters for producing 15 mm diameter holes in 3 mm thick Ti-6Al-4V. The objectives were to simultaneously minimize three conflicting hole quality metrics: dimensional deviation (D dev ), out-of-roundness (R o ), and hole taper angle (θ H ). A 3-level full factorial design (L27) was conducted by varying jet pressure (P), traverse speed (V), and standoff distance (SOD). Robust second-order polynomial regression models were developed, achieving perfect R2 values for all three responses. Analysis of Variance (ANOVA) identified the significant contributions of each parameter, noting that R o was dominated by the linear effect of V (70.19 %). At the same time, D dev and θ H were governed by complex quadratic effects. The Multi-Objective Jaya (MO-Jaya) algorithm was applied to generate a Pareto front of 40 non-dominated solutions. The Combined Compromise Solution (COCOSO) method was then used to rank these solutions and select the single best compromise. The optimal parameters for the best-balanced performance were found to be P of approximately 365 MPa, V of 250 mm/min, and SOD of 3 mm. The successful integration of MO-Jaya and COCOSO provides a valuable framework for navigating conflicting objectives in advanced machining processes.