Modeling and optimization in turning of PA66-GF30% and PA66 using multi-criteria decision-making (PSI, MABAC, and MAIRCA) methods: a comparative study


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Haoues S., Yallese M. A., Belhadi S., Chihaoui S., UYSAL A.

International Journal of Advanced Manufacturing Technology, vol.124, no.7-8, pp.2401-2421, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 124 Issue: 7-8
  • Publication Date: 2023
  • Doi Number: 10.1007/s00170-022-10583-8
  • Journal Name: International Journal of Advanced Manufacturing Technology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, IBZ Online, Compendex, INSPEC, DIALNET
  • Page Numbers: pp.2401-2421
  • Keywords: MCDM methods, Modeling, PA66, PA66-GF30%, Taguchi
  • Yıldız Technical University Affiliated: Yes

Abstract

© 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.Semi-crystalline polymers are widely used in modern industry. Indeed, they are highly demanded because of their excellent compromise between advantageous mechanical properties, high lightness, good productivity, and low cost. In this work, a modeling study of performance parameters such as (Ra), (Fz), (Pc), and (MRR) was carried out using the response surface methodology (RSM). Dry machining operations were performed on two polyamides (PA66-GF30% and PA66) following the L9 (33) orthogonal array. The results were used to perform a mono-objective optimization based on the Taguchi signal-to-noise ratio (S/N). In addition, a comparative study between three multi-objective optimization methods MCDM (PSI, MABAC, and MAIRCA) coupled with the Taguchi approach was realized. The target objective is to reduce (Ra, Fz, and Pc) and maximize (MRR) simultaneously. The results found are original and can help researchers working in the field of machining polyamides with and without reinforcement.