ArticleMaterials (Basel, Switzerland)2023
Comparison of Tool Wear, Surface Roughness, Cutting Forces, Tool Tip Temperature, and Chip Shape during Sustainable Turning of Bearing Steel.
Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Study on D6AC Steel PCBN Hard Turning and Optimization.Materials (Basel, Switzerland) · 2026Article
- Implementing a novel TOPSIS-sine cosine algorithm-based hybrid optimization in machining medium-hardened steel.Scientific reports · 2025Article
- Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms.Heliyon · 2024Article
- Analysis of Chip Morphology in Heavy Milling of 508III Steel Considering Different Tool Wear Conditions.Materials (Basel, Switzerland) · 2024Article
- A State of the Art on Cryogenic Cooling and Its Applications in the Machining of Difficult-to-Machine Alloys.Materials (Basel, Switzerland) · 2024Review
- Understanding the Relationship between Surface Quality and Chip Morphology under Sustainable Cutting Environments.Materials (Basel, Switzerland) · 2024Article
- The Effect of Cellulose Nanocrystal-Based Nanofluid on Milling Performance: An Investigation of Dillimax 690T.Polymers · 2023Article
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5 authors.
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Abstract
In this study, a comparison of measured cutting parameters is discussed while machining AISI 52100 low-alloy hardened steel under two different sustainable cutting environments, those in which a dry and minimum quantity lubrication (MQL) medium are used. A two-level full factorial design method has been utilized to specify the effect of different experimental inputs on the turning trials. Experiments were carried out to investigate the effects of three basic defining parameters of turning operation which are namely cutting speed, cutting depth, feed rate effects and also the effects of the cutting environment. The trials were repeated for the combination of different cutting input parameters. The scanning electron microscopy imaging method was used to characterize the tool wear phenomenon. The macro-morphology of chips was analyzed to define the influence of cutting conditions. The optimum cutting condition for high-strength AISI 52100 bearing steel was obtained using the MQL medium. The results were evaluated with graphical representations and they indicated the superiority of the pulverized oil particles on tribological performance of the cutting process with application of the MQL system.
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