Comparison between the machinability of different titanium alloys (Ti–6Al–4V and Ti–6Al–7Nb) employing the multi-objective optimization

Abstract

Titanium and its alloys are amongst the most important metallic materials used by many industries, such as those pertaining to the aerospace, automotive, and biomedical sectors. This is due to the reliability and functionality of titanium components, in addition to their high strength-to-weight ratio and corrosion resistance. Thus, titanium and its alloys are of great importance to the challenging operations of these sectors. The manufacturing of titanium requires great accuracy to ensure that resulting products meet quality requirements, due to its difficult machinability. In this study, the cutting forces and surface roughness of the turning were analysed to compare different titanium alloys, Ti-6Al-4V and Ti-6Al-7Nb, with CVD-coated and uncoated inserts. The effect of control factors on the response variables was measured using ANOVA. Response surface methodology was applied to the creation of a model of responses and to a bi-objective optimization process via the normalized normal constraint method. The Pareto-optimal sets of both alloys were achieved, which may be applied to practical situations to achieve optimal results for these responses. The models and optimization results confirmed the similarity of machinability values between the Ti-6Al-4V and Ti-6Al-7Nb alloys. The uncoated inserts yielded the best surface roughness and cutting force results when used with both titanium alloys.

The role of roughness parameters in grading the machined surface quality in Ti-alloys

“…Therefore, the alloys behave similarly for some roughness parameters ( R a , R mD , R pm , R p ) and differently for others ( R q , R zD , R zI , R t , P t ). The R a result was consistent with the findings from Mello et al, 11 as they concluded, through paired t -test, that Ti6Al7Nb and Ti6Al4V alloys presented a similar roughness.…”

“…Therefore, the recommended cutting conditions can be the same. To some extent, these outcomes agree with the findings from other authors, as the optimal conditions for improving the surface finish 11 and the specific cutting energy 12 when machining Ti6Al4V and Ti6AL7Nb were the same.…”

“…While the previous work, 9 suggested a better surface finish in Ti6Al7Nb micro-milled surfaces, reports for turning 10,11 showed the opposite trend. Nevertheless, Mello et al 11 found that the turning conditions required to achieve the same (and optimal) surface roughness in both alloys were identical, indicating that they exhibit similar machinability. An analogous inference was found in Filho et al, 12 as the optimal machining conditions for minimum specific cutting energy for both alloys were the same.…”

Experimental investigation and optimization of hybrid turning of Ti6Al7Nb alloy under nanofluid based MQL by TOPSIS method

“…Added graphene nanoparticle increased the MQL-specific heat capacity by 11%. Based on the literature review, the MQL method used in this study was conducted with a vegetable-based cutting oil with a thermal conductivity of 0.5-1 W/m.K [18]. In contrast, graphene is produced from synthetic graphite powder [19] and graphene nanoparticles can exhibit an impressive thermal conductivity of up to 3000-5500 W/m.K [20,21].…”

“…[16]. These properties lead to rapid tool wear and plastic deformation of cutting tools reported by researchers [17,18]. For instance, Risco-Alfonso et al [19] conducted turning exper-iments on Ti-6Al-7Nb alloy using ceramic tools under dry cutting conditions.…”