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Many techniques have been developed to improve the machinability of aeronautical materials titanium and nickel-based alloys such as ultrasonic-assisted turning, laser-assisted turning, and cryogenic-assisted turning. This collaborative scientific investigation presents the steps taken to gain insight into the phenomena of machining Nimonic 90 (a nickel-based alloy) alloy using ultrasonically assisted turning. The cutting speed, feed rate, depth of cut, and frequency are taken as input parameters and average surface roughness ( R a ), power consumption ( P ), and chip formation are considered as output parameters. The experiments are carried out with the full factorial design. The UAT (ultrasonically assisted turning) process gives a significant improvement in average surface roughness and power consumption because of the intermittent cutting action of the cutting tool. UAT process shows a 70–80% reduction in average surface roughness ( R a ) and a 6–15% reduction in power consumption as compared with CT (conventional turning) process. Ultrasonically assisted turning also resulted in the thin and smoother chips as compared with CT process which helps to achieve a more superior machining effect. Finite element modeling shows that the quasi-static nature of the stress induced in the UAT process leads to lower force and ultimately lower power generation. Moreover, a sustainability assessment model is implemented to investigate the effect of UAT in terms of machining performance as well as sustainability effectiveness in a single integrated approach. The novelty of this work lies in providing an integrated concept that combines experimental analysis and sustainability assessment when using ultrasonic vibrational energy during turning of Nimonic 90.

To improve the machinability of Inconel 718, a lot of work has been done in the past decade by modifying tools and machining processes. However, a recently developed cryogenic-ultrasonic assisted turning (CUAT) process influencing the machinability of Inconel 718 as compared to the conventional turning process (CT) has not been conspicuously presented. This paper analyzes the machinability of Inconel 718 using indigenously developed ultrasonic assisted turning (UAT) and CUAT facilities. The influence of the UAT process of Inconel 718 on cutting parameters recommended by the industry has been investigated. Surface roughness ( R a ) and power consumption are measured under the UAT process and then compared with the CT process. Particle swarm optimization (PSO) algorithm is used to identify the optimum cutting parameters to achieve minimum R a and power consumption for UAT and CT processes. The optimized parameters are considered to confirm the usefulness of CUAT as compared to UAT and CT processes. Experimental results of this research work endorse positive effects of the CUAT process over UAT and CT processes in terms of R a and chip morphology. R a values under the CUAT process are reduced significantly in comparison to UAT and CT processes, respectively. UAT and CUAT processes resulted in discontinuous chips having smaller chip thickness in comparison to the CT process. The results are being shared with the local SMEs, and the industry is anticipated to be benefited in terms of improving cutting performance using CUAT and UAT. Moreover, a sustainability assessment model is implemented to investigate the effect of CUAT in terms of machining performance as well as sustainability effectiveness in a single integrated approach.

This work evaluates the machinability improvements in vastly used titanium alloy (Ti-6Al-4V) using alternate turning techniques. Detailed examination of flank and crater faces of inserts is carried out in this work to analyze tool wear under dry, wet, and cryogenic environments. Critical responses such as crater wear and energy consumption decide the machinability of materials, but these responses are less explored in the past using altered cutting conditions. This investigation analyzes the machinability in terms of industry-relevant responses such as tool wear, energy consumption, chip reduction coefficient, and average surface roughness under altered cutting conditions. Outcomes of this investigation show increase in tool life by 200% and 80% using cryogenic turning than in dry and wet turning techniques, respectively. Moreover, the findings of the study show up to 9% and 61% decline in energy consumption using cryogenic turning than in dry and wet turning, respectively. Surface roughness values also show a reduction by up to 71% and 64%, under cryogenic environment than in dry and wet environments, respectively. The results of this study advocate the suitability of cryogenic turning at industry-relevant parameters to establish this technique as a viable alternative to replace inefficient conventional turning techniques.

The usage of cryogenic fluid is increasing in the machining industries especially to cut the materials having a lower machinability like Nimonic 90, a nickel-based alloy. However, the comparison of flood coolant and LCO 2 as a cryogenic fluid based on machining performance has not been found for machining Nimonic 90. In this regard, this study compares LCO 2 and conventional mineral oil-based flood coolant on the basis of machining performance while turning Nimonic 90. The effect of turning process parameters (cutting speed ( v c ), feed ( f ), and depth of cut ( a p )) and cutting fluids has been identified by analyzing machinability indicators like cutting force, flank tool wear, power consumption, surface roughness in terms of R a , and chip morphology. Increment of 34%, 25%, and 24% in cutting forces has been observed for cryogenic turning using LCO 2 in comparison with wet machining when the values of a p are 0.75, 0.50, and 0.25 mm, respectively. A decrement of 63% tool wear has been seen in LCO 2 cryogenic fluid in contrast to wet machining at higher values of v c , f , and a p . The superior surface finish has been found in wet machining, while lesser power consumption was recorded for LCO 2 as a cutting fluid. Cryogenic machining provided better chip breakability in comparison with wet machining.

Additive manufacturing (AM) is increasingly used for fabricating parts directly from digital models, usually by depositing and bonding successive layers of various materials such as polymers, metals, ceramics, and composites. The design freedom and reduced material consumption for producing near-net-shaped components have made AM a popular choice across various industries, including the automotive and aerospace sectors. Despite its growing popularity, the accurate estimation of production time, productivity and cost remains a significant challenge due to the ambiguity surrounding the technology. Hence, reliable cost estimation models are necessary to guide decisions throughout product development activities. This paper provides a thorough analysis of the state of the art in cost models for AM with a specific focus on metal Directed Energy Deposition (DED) and Powder Bed Fusion (PBF) processes. An overview of DED and PBF processes is presented to enhance the understanding of how process parameters impact the overall cost. Consequently, suitable costing techniques and significant cost contributors in AM have been identified and examined in-depth. Existing cost modelling approaches in the field of AM are critically evaluated, leading to the suggestion of a comprehensive cost breakdown including often-overlooked aspects. This study aims to contribute to the development of accurate cost prediction models in supporting decision making in the implementation of AM.

This work presents a comprehensive structure for evaluating the sustainability of machining processes. Industries can contribute towards developing a sustainable future by using algorithms that evaluate the sustainability of their processes. Inspired by the literature, the proposed model involves a set of metrics that are critical in evaluating the impact of a process on society, environment, and economy. The flexibility of this model allows decision-makers to use the available responses to identify the most favorable process. The entropy weight method was suggested for objectively calculating the weights of each indicator. A multi-criteria decision-making method i.e., Technique for Order Preference based on Similarity to Ideal Solution (TOPSIS), was used to rank processes in the decreasing order of their sustainability. The proposed algorithm was successfully validated with case studies from the published literature. A MATLAB code was also created so that industries may expeditiously apply this method to evaluate the sustainability of machining processes.

The machining of Ti-6Al-4V alloys is challenging due to their high strength, poor thermal conductivity, and high chemical reactivity. When used in traditional machining, cryogenic coolants can reduce tool wear, thus extending tool life, improving surface finish, and requiring less power with reduced environmental effects. In this context, this study aimed to perform a machinability analysis of the surface roughness, power consumption, tool wear, and specific energy consumption of a Ti-6Al-4V titanium alloy and to comprehend the performance of dry and cryogenic machining in turning operations. A comprehensive analysis of tool wear and specific cutting energy (SCE) under dry and cryogenic machining was conducted. It was found that the machining time under a cryogenic environment was increased by 83% and 39% at 80 and 90 m/min compared to a cutting speed at 100 m/min. The higher cutting speed (100 m/min) in cryogenic environments produced an improved surface finish. Compared to dry machining, the cooling effect of liquid CO2 helped dissipate heat and reduce thermal damage, improving surface finish. The findings revealed that in dry conditions, approximately 5.55%, 26.45%, and 27.61% less power was consumed than in cryogenic conditions at 80, 90, and 100 m/min cutting speeds, respectively. Based on the outcomes of the work, the application of cryogenic cooling can be considered an alternative to dry and flood cooling for improving the machinability of Ti-6Al-4V alloys.

In the electrical discharge machining (EDM) process, especially during the machining of hardened steels, changes in tool shape have been identified as one of the major problems. To understand the aforesaid dilemma, an initiative was undertaken through this experimental study. To assess the distortion in tool shape that occurs during the machining of EN31 tool steel, variations in tool shape were examined by monitoring the roundness of the tooltip before and after machining with a coordinate measuring machine. The change in out-of-roundness of the tooltip varied from 5.65 to 37.8 µm during machining under different experimental conditions. It was revealed that the input current, the pulse on time, and the pulse off time had most significant effect in terms of changes in the out-of-roundness values during machining. Machine learning techniques (decision tree, random forest, generalized linear model, and neural network) were applied for the prediction of changes in tool shape. It was observed that the results predicted by the random forest technique were more convincing. Subsequently, it was gathered from this examination that the usage of the random forest technique for the prediction of changes in tool shape yielded propitious outcomes, with high accuracy (93.67%), correlation (0.97), coefficient of determination (0.94), and mean absolute error (1.65 µm) values. Hence, it was inferred that the random forest technique provided better results in terms of the prediction of tool shape.

Nickel-based superalloys are widely used in the aerospace, automotive, marine and medical sectors, owing to their high mechanical strength and corrosion resistance. However, they exhibit poor machinability due to low thermal conductivity, high shear modulus, strain hardening, etc. Various modifications have been incorporated into existing machining techniques to address these issues. One such modification is the incorporation of ultrasonic assistance to turning operations. The assisted process is popularly known as ultrasonic assisted turning (UAT), and uses ultrasonic vibration to the processing zone to cut the material. The present article investigates the effect of ultrasonic vibration on coated carbide tool wear for machining Nimonic-90 under dry and wet conditions. UAT and conventional turning (CT) were performed at constant cutting speed, feed rate and depth of cut. The results show that the main wear mechanisms were abrasion, chipping, notch wear and adhesion of the built-up edge in both processes. However, by using a coolant, the formation of the built-up edge was reduced. CT and UAT under dry conditions showed an approximate reduction of 20% in the width of flank wear compared to CT and UAT under wet conditions. UAT showed approximate reductions of 6–20% in cutting force and 13–27% in feed force compared to the CT process. The chips formed during UAT were thinner, smoother and shorter than those formed during CT.

The growing need to increase productivity and pressures for more sustainable manufacturing processes lead to a shift to less harmful lubrication systems that are less harmful to nature and the people involved. The minimal quantity lubrication system (MQL) stands out in this respect, especially in interrupted cutting processes such as milling, due to the cutting interface’s highly dynamic and chaotic nature. Using graphene sheets in cutting fluids also increases the efficiency of machining processes. This work investigates the influence on thermophysical and tribological properties of concentrations of 0.05 wt% and 0.1 wt% of graphene sheets in two vegetable-based and one mineral-based cutting fluids. The fluids are first characterized (viscosity, thermal conductivity, diffusivity, and wettability) and tested in reciprocating and ramp milling tests; all experiments are based on norms. The results show that the experiments with cutting fluids (with and without graphene) showed better tribological behavior than those in dry conditions. The graphene sheets alter the thermo-physical and tribological properties of the cutting fluids. The MQL15 vegetable-based fluid showed better lubricating properties in the milling tests, with better conditions for tribosystem chip–tool–workpiece interfaces, which makes the friction coefficient, and wear rate stable. Vegetable-based cutting fluids, even in minimum quantities and with graphene nanoparticles, have a high potential for increasing the efficiency and sustainability of the milling process.