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    Influence of hybrid Cryo-MQL lubri-cooling strategy on the machining and tribological characteristics of Inconel 718
    (Elsevier Sci Ltd, 2021) Danish, Mohd; Gupta, Munish Kumar; Rubaiee, Saeed; Ahmed, Anas; Korkmaz, Mehmet Erdi
    The poor thermal conductivity of Inconel 718 leads to higher cutting temperatures and, as a consequence, rapid tool degradation is a common phenomenon. As a result, a hybrid lubri-cooling environment for turning Inconel 718 alloys is proposed, incorporating the theory of cryogenic cooling and minimum quantity lubrication (CryoMQL). For improved lubri-cooling effect, Cryo-MQL integrates the application of a minimum quantity of vegetable oil and liquid nitrogen from two distinct nozzles in the cutting zone. Surface roughness, cutting temperature, tool wear, chip morphology, and micro-structure of the machined surface were evaluated for different lubri-cooling mediums: dry, MQL, Cryogenic, and Cryo-MQL. In comparison to a dry medium, the Cryo-MQL environment decreases surface roughness, cutting temperature, and tool wear by 60.6%, 37%, and 19.5%, respectively. Adhesion and abrasion were patented to be common tool wear types, as per SEM micro-graphs. Eventually, in the Cryo-MQL environment, a spike in micro-hardness value has been reported. However, during processing with Cryo-MQL, the grain structure of the working material is found to be smaller as compared to other mediums.
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    Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization
    (Elsevier, 2022) Rubaiee, Saeed; Danish, Mohd; Gupta, Munish Kumar; Ahmed, Anas; Yahya, Syed Mohd; Yildirim, Mehmet Bayram; Sarikaya, Murat
    Inconel 718 is a heat-resistant Ni-based superalloy widely used, particularly, in aircraft and aero-engineering applications. It has poor machinability due to its unique thermal and mechanical properties. For this reason, studies have been carried out from past to present to improve the machinability of Nickel-based (Ni) alloys. Further improvement can be achieved by applying hybrid multi-objective optimization strategies to ensure that cutting parameters and cooling/lubrication strategies are also adjusted effectively. That is why, in this research, the machinability of Inconel 718 is optimized under various sustainable lubricating environments i.e., dry medium, minimum quantity lubrication (MQL), nano-MQL, and cryogenic conditions at different machining parameters during end-milling process. Subsequently, the analysis of variance (ANOVA) approach was implanted to apprehend the impact of each machining parameter. Finally, to optimize machining en-vironments, two advanced optimization algorithms (non-dominated sorting genetic algo-rithm II (NSGA-II) and the Teaching-learning-based optimization (TLBO) approach) were introduced. As a result, both methods have demonstrated remarkable efficiency in ma-chine response prediction. Both methodologies demonstrate that a cutting speed of 90 m/ min, feed rate of 0.05 mm/rev, and CO2 snow are the optimal circumstances for minimizing machining responses during milling of Inconel 718. (C) 2022 The Author(s). Published by Elsevier B.V.