Slot milling of titanium alloy with hexagonal boron nitride and minimum quantity lubrication and multi-objective process optimization for energy efficiency

Osman K. A. , YILMAZ V., ÜNVER H. Ö. , ŞEKER U., KILIÇ S. E.

JOURNAL OF CLEANER PRODUCTION, vol.258, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 258
  • Publication Date: 2020
  • Doi Number: 10.1016/j.jclepro.2020.120739
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Chimica, Communication Abstracts, Compendex, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Titanium alloy, Milling, Minimum quantity lubrication, Hexagonal boron nitride nanoparticles, Particle swarm optimization, ENHANCED THERMAL-CONDUCTIVITY, NANO-CUTTING FLUIDS, PERFORMANCE EVALUATION, TOOL WEAR, NANOFLUIDS, MQL, PARAMETERS, DRY
  • Gazi University Affiliated: Yes


The implementation of sustainable manufacturing techniques to make machining processes more eco-friendly is a challenging topic that has attracted significant attention from the industrial sector for many years. As one of the dominant manufacturing processes, machining can have a considerable impact in terms of ecology, society, and economics. In certain areas, this impact is a result of using certain cutting fluids, especially during the machining of difficult-to-cut alloys such as titanium, where a large amount of cutting fluid is wasted to ease the cutting process. In such scenarios, identifying suitable machining conditions to supply cutting fluids using eco-friendly techniques is currently a major focus of academic and industrial sector research. In this study, effects of minimum quantity lubrication with different concentrations of hexagonal boron nitride nanoparticles on the surface roughness and cutting force of slot-milled titanium alloy is investigated using analysis of variance and response surface methodology. The results reveal that all responses are sensitive to changes in the feed per tooth, cutting depth, and cutting fluid flow rate. The regression functions generated were combined with particle swarm optimization in order to improve energy-efficiency, as well. Possible sectorial scenarios were generated for wider industrial adoption. With this study, it was proven that utilizing minimum quantity lubrication with hexagonal boron nitride nanoparticles can reduce both cutting force and surface roughness, which makes it to be a promising alternative as a nanoparticle augmented minimum quantity lubrication method for machining titanium alloys. (C) 2020 Elsevier Ltd. All rights reserved.