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

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–4 V and Ti–6Al–7Nb alloys. The uncoated inserts yielded the best surface roughness and cutting force results when used with both titanium alloys.publishe

Energy consumption analysis in turning Ti-6Al-4V alloy.

One of the major concerns in manufacturing industries include the amount of energy consumed during machining processes. Therefore, the study of the specific energy during machining must be analyzed in relation to the process parameters (feed rate, speed and depth of cut). This work demonstrates the analysis of specific cutting energy (SCE) and cutting power during titanium alloys machining under dry conditions. Turning experiments with uncoated carbide inserts were performed applying Taguchi Design of Experiments technique and analyzed the effect of speed, feed and depth of cut during turning Ti-6Al-4V titanium alloys. ANOVA was done to find out the influence of the machining parameters on energy consumption. The outcome of this analysis indicates that feed rate is the highly dominant factor responsible for the SCE of a machine tool, whereas, cutting speed was found as the influential factor affecting the power during the machining process. The environmental and economic performance for a machining process may be significantly improved by reducing energy consumption using appropriate machining conditions

Development and analysis of tool wear and energy consumption maps for turning of titanium alloy (Ti6Al4V).

Machine tools are the main source of electric power consumption in industrial operations. Thus, in manufacturing, energy-efficient and cleaner production methods are preferred to mitigate production costs. Titanium alloys are known for their poor machinability and are generally characterized by low tool life, high energy consumption and poor surface quality due to its unique physical and mechanical properties. This research aims to evaluate the tool wear rate (R) and the specific cutting energy (SCE) at varying cutting conditions by developing tool wear and energy maps using unified cutting tests. Uncoated H13A tools were used during single-point turning of Ti-6Al-4V alloy by employing Full Factorial Design of Experiments. Based on experimental data, comprehensive process maps were developed for monitoring wear and energy data. These maps showed regions of (low moderate and high) wear and specific energy consumption. It was observed that while machining Ti-6Al-4V alloy the recommended cutting condition (V=100 m/min and f =0.16 mm/rev) enhances the tool life and reduces energy consumption together with high material removal rate. It was also deduced that instead of low speed, using a higher speed of 125 m/min will increase MRR by 127 % and SCE by 16 %, which is more feasible in a production environment. From tool-chip contact length and chip morphology analysis, a strong correlation indicated the reason behind the occurrence of various zones on the maps. It has been found that high wear and energy zone occurred due to the larger contact length and higher chip compression ratio when machining at high speed. The developed maps can be used to help the manufacturers achieve the economic and energy-efficient goal of machining

Multi-objective optimization for sustainable turning Ti6Al4V alloy using grey relational analysis (GRA) based on analytic hierarchy process (AHP).

Sustainable machining necessitates energy-efficient processes, longer tool lifespan, and greater surface integrity of the products in modern manufacturing. However, when considering Ti6Al4V alloy, these objectives turn out to be difficult to achieve as titanium alloys pose serious machinability challenges, especially at elevated temperatures. In this research, we investigate the optimal machining parameters required for turning of Ti6Al4V alloy. Turning experiments were performed to optimize four response parameters, i.e., specific cutting energy (SCE), wear rate (R), surface roughness (Ra), and material removal rate (MRR) with uncoated H13 carbide inserts in the dry cutting environment. Grey relational analysis (GRA) combined with the analytic hierarchy process (AHP) was performed to develop a multi-objective function. Response surface optimization was used to optimize the developed multi-objective function and determine the optimal cutting condition. As per the ANOVA, the interaction of feed rate and cutting speed (f × V) was found to be the most significant factor influencing the grey relational grade (GRG) of the multi-objective function. The optimized machining conditions increased the MRR and tool life by 34% and 7%, whereas, reducing the specific cutting energy and surface roughness by 6% and 2% respectively. Using Taguchi-based GRA by analytic hierarchy process (AHP) weights method, the benefits of high-speed machining Ti6Al4V through multi-response optimization were achieved

Tool wear progression and its effect on energy consumption in turning of titanium alloy (Ti-6Al-4V).

To achieve greater productivity, titanium alloy requires cutting at higher speeds (above 100 m min−1) that affects the tool life and energy consumption during the machining process. This research work correlates the wear progression and Specific Cutting Energy (SCE) in turning Ti-6Al-4V alloy using H13 tools (uncoated carbide) in dry conditions from low to high cutting speeds. Cutting condition employed in this study were selected from published wear map developed for titanium (Ti-6Al-4V alloy) with the same tool. Flank wear growth of the tool has been investigated at different length of cuts in correlation with the SCE under different cutting conditions. The useful tool life was found to be shorter at high-speed machining conditions, thus the end of useful tool life criteria (ISO 3685) was reached at a much shorter length of cuts as compared to low-speed machining conditions. The cutting conditions corresponding to high wear rate also resulted in high SCE. Finally, SCE and wear have been related by a linear relationship that can be used to monitor wear and/or SCE utilization during machining. The results help in the selection of appropriate cutting conditions that will enhance the tool life and minimize SCE consumption during machining titanium alloy

Sustainable machining of Ti-6Al-4V using cryogenic cooling: an optimized approach

Abstract Cryogenic machining is an effective, sustainable cooling approach in machining hard-to-cut materials. In this work, two multi-objective optimization techniques, namely; non-dominated sorting genetic algorithm, and grey relational analysis, were used to optimize the cutting performance during turning Ti-6Al-4V alloys under flood and cryogenic cooling. The machining performance was optimized in terms of surface roughness, material removal rate, tool performance and cutting forces. The optimal solutions, including cutting conditions and cooling technique, were determined for different machining strategies (i.e. roughing, finishing, and productivity). It was found that cryogenic cooling offers better cutting performance with a higher optimization index than flood approach

Impact of Palm Oil based Minimum Quantity of Lubrication on Machinability of Ti and its Alloy (Ti-6AI-4V)

This project investigates the usage of palm oil as a metal cutting fluid in minimum quantity lubrication assisted turning operations and its effect on surface roughness, tool wear and cutting temperature for Titanium alloy Ti-6Al-4V. Artificial Neural Network models were developed to determine the optimum cutting parameters considering the sustainability of palm oil in titanium alloy machining to improve future manufacturing costs and qualities