Yazar "Ahmed, Anas" seçeneğine göre listele

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    Environmental, technological and economical aspects of cryogenic assisted hard machining operation of inconel 718: A step towards green manufacturing
    (Elsevier Sci Ltd, 2022) Danish, Mohd; Gupta, Munish Kumar; Rubaiee, Saeed; Ahmed, Anas; Sarikaya, Murat; Krolczyk, Grzegorz M.
    It is critical in today's modern manufacturing era to have a machining system that is both environmentally and economically beneficial. It is therefore necessary in many ways to illustrate a relationship between technological, economic and sustainability measures in the machining of Inconel 718. In present investigation, the experimental studies are incorporated by the use of the dry and MQL (minimum quantity lubrication) environments, as well as cryogenic-LN2 and cryogenic-CO2 environments. In terms of technological, sustainability, and economic metrics, the results show that cryogenic-LN2 performed better, followed by cryogenic-CO2, MQL, and dry conditions. As turning Inconel 718, LN2 assisted machining reduce total machining costs and energy usage considerably when compared to dry, MQL, cryogenic-CO2 environments. In addition, the LN2 cooling environment has been shown to significantly reduce machining outputs such as cutting force, tool wear, and surface roughness. LN2 conditions was found to be most promising as it has decreased the cutting force by 32.1%, tool flank wear by 33.33% and total energy consumption by 18% compared to dry machining conditions. It's worth noting that modern lubricooling technologies help the aerospace sector be more sustainable by decreasing resource consumption, enhancing environmental advantages, and improving machining features.
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    Influence of graphene reinforced sunflower oil on thermo-physical, tribological and machining characteristics of inconel 718
    (Elsevier, 2021) Danish, Mohd; Gupta, Munish Kumar; Rubaiee, Saeed; Ahmed, Anas; Sarikaya, Murat
    Owing to the extreme heat generated during Inconel 718 machining, the application of a minimum quantity lubrication (MQL) strategy is restricted to mild cutting conditions. By incorporating vegetable-based cutting oils reinforced by nanoparticles as possible addi-tives, the effectiveness of MQL can be improved in high-speed machining. In this study, hybrid nano-green oils were developed by combining graphene nanoparticles in various volume concentrations with sunflower oil. Subsequently, dispersion stability, thermal conductivity, viscosity, and wetting angle of nano-green oils were measured. An MQL de -vice is used to disperse the smallest amount of nano-green oils throughout the machining area. Later, the experimentally optimized graphene-based green oil is used for milling experiments. Furthermore, hard machining experiments were conducted with cutting speed of 80 m/min, feed rate of 0.2 mm/rev, and depth of cut of 0.5 mm under four different lubricating mediums: dry, flooded, sunflower oil, and 0.7% graphene reinforced sunflower oil. Comparative results show that 0.7% graphene reinforced sunflower oil performs better and reduces surface roughness by 49%, cutting force by 25%, cutting temperature by 31%, and tool wear by 20% as compared to dry machining environment. Finally, elemental analysis of cutting insert reports that adhesion is the major wear mechanism in all mediums. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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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.