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    Experimental investigation and optimization of hybrid turning of Ti6Al7Nb alloy under nanofluid based MQL by TOPSIS method
    (Yildiz Technical University, 2023) Duman, Erkin; Yapan, Yusuf Furkan; Sofuoğlu, Mehmet Alper
    The present work aims to decide on machining parameters and enhance machinability of the biomedical Ti6Al7Nb alloy using nanofluid MQL with nanoparticles of graphene (NMQL) and ultrasonic vibration assisted (UVA) machining methods were applied both separately and in a hybrid manner. Consequently, for the chosen cutting parameters, when compared to the conventional turning (CT) with vegetable cutting oil-based MQL, the UVA-NMQL hybrid method has achieved a reduction in cutting forces ranging from approximately 11% to 23%, a decrease in cutting temperatures by around 9% to 17%, and an enhancement in average surface roughness by roughly 15% to 53% across all the analyzed results compare to vegetable oil based conventional MQL turning conditions. Additionally, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the optimum cutting parameters were determined as UVA-NMQL cutting condition, 130 m/min cutting speed, and 0.1 mm feed value.
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    Investigation of ultrasonic vibration assisted orthogonal turning under dry and minimum quantity lubrication conditions and performing sustainability analyses
    (Elsevier Sci Ltd, 2024) Duman, Erkin; Yapan, Yusuf Furkan; Salvi, Harsh; Sofuoglu, Mehmet Alper; Khanna, Navneet; Uysal, Alper
    Recently, increasing pressure on industries to innovate and adopt sustainable techniques has sparked investigations into machining strategies that have minimal carbon emissions, minimal energy consumption by machine tools, and low machining costs. The primary aim of this paper is to identify the machining conditions that can fulfill the criteria of clean production and sustainable chip forming for low-alloy steel which is extensively used in the many industrial field. To achieve this goal, experiments were done under both dry and Minimum Quantity Lubrication (MQL) conditions, aided by ultrasonic vibration assisted hybrid machining conditions at various cutting speeds (100 and 140 m/min) and uncut chip thicknesses (0.1, 0.14, and 0.18 mm). The study was conducted in two stages. In the first part, machining experiments were performed afterward, cutting forces, cutting temperature, chip morphology, surface roughness, and texture were examined. The second part of this study evaluates the sustainability of various machining parameters and cutting environments. The analysis of economic feasibility or rather the total machining costs were estimated by evaluating the costs incurred due to investment of machine tools, lubricant/coolant delivery systems and ultrasonic vibration system costs, waste processing and management costs, cutting tool and labor costs, cost of cutting fluid and energy consumed. On the other hand, environmental viability was evaluated by estimating the carbon emissions (CE) due to the power consumed, material utilization (i.e., the cutting tool and cutting fluid), and the waste processing and management (i.e., disposal of cutting tool, cutting fluid and chip recycling). Results indicate that both dry and MQL ultrasonic-assisted machining processes resulted in improved chip breakability, and produced shortcomma chips. Additionally, it reduced cutting force by 28% and the cutting temperature was lowered by 30 %. Besides, Minimum Quantity Lubrication + Ultrasonic Vibration Assisted Machining (MQL + UVAM) hybrid method prevented surface defects and reduced average surface roughness by 24%-35% compared to dry conditions. While utilizing the MQL + UVAM method, the overall machining cost decreased in the range of about 20-30 % as compared to dry and dry + UVAM conditions. From an environmental standpoint, the MQL + UVAM hybrid machining process was found to be a significant contribution to the overall CE due to use of cutting fluids and increased machine tool utilization. This paper contributed to the understanding of sustainability and cleaner production to mitigate CO2 emissions by using the MQL + UVAM hybrid method.