Optimising cutting conditions for minimising cutting time in multi-pass milling via weighted superposition attraction-repulsion (WSAR) algorithm

Baykasoğlu A.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, cilt.59, sa.15, ss.4633-4648, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 59 Sayı: 15
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/00207543.2020.1767313
  • Dergi Adı: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.4633-4648
  • Anahtar Kelimeler: Multi-pass milling, cutting conditions, weighted superposition attraction-repulsion algorithm, SWARM INTELLIGENCE ALGORITHM, PARAMETER OPTIMIZATION, DYNAMIC OPTIMIZATION, PRISMATIC PARTS, PERFORMANCE, OPERATIONS
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Milling is one of the most frequently used machining operations in manufacturing industry. In order to remove cutting stocks economically and effectively, it is typically necessary to employ a multi-pass milling plan. Nevertheless, an optimisation practice is desirable in order to decide the most appropriate cutting plan (cutting speeds and feed rates) in each cutting pass to minimise the total machining time. In this study, optimisation of cutting conditions in multi-pass milling is achieved by utilising an improved version of a recently developed swarm intelligence based metaheuristic algorithm, which is known as a weighted superposition attraction algorithm. All of the cutting constraints are successfully satisfied and the results obtained from the proposed optimisation algorithm are compared with other optimisation approaches. The proposed optimisation algorithm is able to provide the best solutions for all test cases with reasonable computational time.