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Obtaining high surface quality with minimum tool wear values is one of the most important goals of turning process. Moreover, when it comes to process costs, the volume of material removed is very important and should be considered when optimizing cutting variables. In this work, gray relational analysis was employed with the aim of simultaneously optimizing surface roughness, tool wear and volume of material removed. Cutting speed, feed rate and depth of cut were chosen as process control factors. Optimization results showed that cutting speed of 80 m/min, feed rate of 0.1 mm/rev and depth of cut of 1.5 mm were the optimum set of cutting parameters. Scanning electron microscope images of worn cutting edges revealed that depth-of-cut notch, built-up edge, and adhesion are dominant wear mechanisms. Finally, confirmation test proved the accuracy of the prediction carried out by the optimization process.

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Tribological behaviour of Ti-6Al-4V alloy sliding against WC-Co was evaluated by employing WS 2 nanoparticles blended in a cutting fluid used for machining of this alloy. Pin-on disk tests were carried out under boundary-lubricated condition using a cutting fluid (70% water and 30% oil) blended with WS 2 nanoparticles (CF + WS 2 ). When a cutting fluid with ≥ 0.5 wt.% WS 2 was used, the COF of the tribosystem was reduced compared to CF + 0%WS 2 . The lowest COF of 0.05 was obtained when 1.0 wt.% WS 2 was used. Low and stable COF values were accompanied by the formation of a tribolayer incorporating WS 2 and WO 3 on the WC-Co surfaces. During orthogonal machining of Ti-6Al-4V using CF + 1.0%WS 2 , a tribolayer with the similar composition was formed on the cutting edge of the WC-Co tool and the average cutting force was reduced by 35% compared to cutting with CF + 0%WS 2 . Machining with CF + 1.0%WS 2 produced thinner chips. Other improvements in machining performance attained using CF + 1.0%WS 2 included reduction of adhesive wear on the tool and a lower roughness of the machined surface.