Laser-Assisted High Speed Machining of 316 Stainless Steel: The Effect of Water-Soluble Sago Starch Based Cutting Fluid on Surface Roughness and Tool Wear - Université de Picardie Jules Verne Accéder directement au contenu
Article Dans Une Revue Materials Année : 2021

Laser-Assisted High Speed Machining of 316 Stainless Steel: The Effect of Water-Soluble Sago Starch Based Cutting Fluid on Surface Roughness and Tool Wear

Farhana Yasmin
  • Fonction : Auteur
Khairul Fikri Tamrin
  • Fonction : Auteur
Nadeem Ahmed Sheikh
  • Fonction : Auteur
Abdullah Yassin
  • Fonction : Auteur
Amir Azam Khan
  • Fonction : Auteur
Shahrol Mohamaddan
  • Fonction : Auteur

Résumé

Laser-assisted high speed milling is a subtractive machining method that employs a laser to thermally soften a difficult-to-cut material's surface in order to enhance machinability at a high material removal rate with improved surface finish and tool life. However, this machining with high speed leads to high friction between workpiece and tool, and can result in high temperatures, impairing the surface quality. Use of conventional cutting fluid may not effectively control the heat generation. Besides, vegetable-based cutting fluids are invariably a major source of food insecurity of edible oils which is traditionally used as a staple food in many countries. Thus, the primary objective of this study is to experimentally investigate the effects of water-soluble sago starch-based cutting fluid on surface roughness and tool's flank wear using response surface methodology (RSM) while machining of 316 stainless steel. In order to observe the comparison, the experiments with same machining parameters are conducted with conventional cutting fluid. The prepared water-soluble sago starch based cutting fluid showed excellent cooling and lubricating performance. Therefore, in comparison to the machining using conventional cutting fluid, a decrease of 48.23% in surface roughness and 38.41% in flank wear were noted using presented approach. Furthermore, using the extreme learning machine (ELM), the obtained data is modeled to predict surface roughness and flank wear and showed good agreement between observations and predictions.

Dates et versions

hal-03627112 , version 1 (01-04-2022)

Identifiants

Citer

Farhana Yasmin, Khairul Fikri Tamrin, Nadeem Ahmed Sheikh, Pierre Barroy, Abdullah Yassin, et al.. Laser-Assisted High Speed Machining of 316 Stainless Steel: The Effect of Water-Soluble Sago Starch Based Cutting Fluid on Surface Roughness and Tool Wear. Materials, 2021, 14 (5), ⟨10.3390/ma14051311⟩. ⟨hal-03627112⟩
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