Browsing by Author "Osman, Khaled Ali"
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Item SUSTAINABLE MACHINING Of DIFFICULT-TO-CUT MATERIALS USING MQL TECHNIQUE(2022-02-15) Osman, Khaled Ali; Kılıç, Sadık Engin; Ünver, Hakkı ÖzgürGlobal industrial trends are leaning towards making machining processes eco-friendly and acceptable for sustainable manufacturing. In this regard, reduction strategies for cutting fluid (CF) consumption have been widely discussed in the literature as a highly challenging issue. Numerous effective strategies have been proposed as an alternative to the use of cutting fluids. Minimum quantity lubrication (MQL) is one of them which promises to be both economical and environmentally friendly. Despite the high expectations from MQL applications in machining processes, there is still a number of limitations to MQL application especially in machining difficult-to-cut materials such as titanium alloys (Ti-6Al-4V). Insufficiency of MQL under such extreme conditions has led to other works focusing on exploring different methods to improve the properties of MQL applications of the cutting fluids. In this respect, much effort has been devoted in recent years to achieving an improvement in MQL by adopting nanotechnology. This study proposes a novel approach to an eco-friendly lubrication/cooling strategy by integrating MQL with hexagonal boron nitride (hBN) for use in slot milling of Ti-6Al-4V. The novelty here lies in increasing the lubrication/cooling effect and enhancing the thermal conductivity of the MQL technique by means of nanofluids to improve Ti-6Al-4V machinability. For this purpose, the research specifically focuses on the effects of dispersed hBN into a fatty oil (cutting fluid). Therefore, to build a comprehensive understanding of the effect of using MQL with hBN on responses during the slot milling of Ti-6Al-4V, all results were compared with dry, flood and MQL conditions. Based upon the response surface method (RSM), the central composite design (CCD) has been utilized to create the design of experiments using 5 levels and 5 factors for cutting force (Fc) and surface roughness (Ra) measurements according to combinations of control parameters, i.e., cutting speed (v), feed per tooth (ft), axial depth (ap), flow rate of cutting fluid (Q) and concentrations of hBN (NPs). The study was then focused on a Multi-Objective Particle Swarm Optimization (MOPSO) utilizing RSM models in terms of Ra and the specific cutting energy (SEC). The results reveal that all responses are sensitive to changes in the feed per tooth, axial depth of cut and cutting fluid flow rate. However, these responses are not sensitive to changes in the cutting speed. In addition, utilizing MQL with hBN nanoparticles can reduce Fc and Ra. In conclusion, MQL with hBN nanoparticles is found to be an effective alternative technique for conventional flood lubrication when machining Ti-6Al-4V.