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Predicting a component's fatigue life requires information on not only the number of stress cycles the component will undergo but also the kind and frequency of those stress cycles, as well as information about the surrounding environment and the intended purpose of the component. Models that can forecast lifespan by utilizing available experimental data are preferred since fatigue investigations are costly and time-consuming. Therefore, this work focuses on fatigue testing of S355 mild steel specimens under multiaxial loading conditions involving bending and torsion. The impact of phase-shifted loading conditions on material behavior, considering in-phase and with angles 0°, 45°, and 90°, has been studied. Then, the data of fatigue tests involve variations in loading amplitudes, and configurations used in different ML algorithms such as lazy k-nearest neighbors (Lazy-KNN), linear regression (LR), and random forest (RF) were employed for predictive modeling. These models are evaluated based on their ability to predict nominal stresses, torsion, and bending moments under varying loading configurations. The predictive modeling results are visually presented, showcasing the effectiveness of Lazy-KNN in accurately predicting material responses. Quantitative analyses further confirm the robustness of Lazy-KNN in predicting bending, nominal stress, and torsion under different loading conditions. The study provides valuable insights into the fatigue behavior of S355 mild steel and highlights the significance of considering multiaxial loading configurations in material testing and design. [ABSTRACT FROM AUTHOR]

Cryogenic cooling has gathered significant attention in the manufacturing industry. There are inherent difficulties in machining materials that are difficult to machine because of high levels of hardness, abrasiveness, and heat conductivity. Increased tool wear, diminished surface finish, and reduced machining efficiency are the results of these problems, and traditional cooling solutions are insufficient to resolve them. The application of cryogenic cooling involves the use of extremely low temperatures, typically achieved by employing liquid nitrogen or other cryogenic fluids. This study reviews the current state of cryogenic cooling technology and its use in machining difficult-to-machine materials. In addition, this review encompasses a thorough examination of cryogenic cooling techniques, including their principles, mechanisms, and effects on machining performance. The recent literature was used to discuss difficult-to-machine materials and their machining properties. The role of cryogenic cooling in machining difficult materials was then discussed. Finally, the latest technologies and methods involved in cryogenic cooling condition were discussed in detail. The outcome demonstrated that the exploration of cryogenic cooling methods has gained prominence in the manufacturing industry due to their potential to address challenges associated with the machining of exotic alloys. [ABSTRACT FROM AUTHOR]

Particularly in sectors where mechanisation is increasing, there has been persistent effort to maximise the use of existing assets. Since maintenance management is accountable for the accessibility of assets, it stands to acquire prominence in this setting. One of the most common methods for keeping equipment in good working order is predictive maintenance with machine learning methods. Failures can be spotted before they cause any downtime or extra expenses, and with this aim, the present work deals with the online detection of wear and friction characteristics of stainless steel 316L under lubricating conditions with machine learning models. Wear rate and friction forces were taken into account as reaction parameters, and biomedical-graded stainless steel 316L was chosen as the work material. With more testing, the J48 method's accuracy improves to 100% in low wear conditions and 99.27% in heavy wear situations. In addition, the graphic showed the accuracy values for several models. The J48 model is the most precise amongst all others, with a value of 100% (minimum wear) and an average of 98.92% (higher wear). Amongst all the models tested under varying machining conditions, the J48's 98.92% (low wear) and 98.92% (high wear) recall scores stand out as very impressive (higher wear). In terms of F1-score, J48 performs better than any competing model at 99.45% (low wear) and 98.92% (higher wear). As a result, the J48 improves the model's overall performance. [ABSTRACT FROM AUTHOR]

Information technology applications are crucial to the proper utilization of manufacturing equipment in the new industrial age, i.e., Industry 4.0. There are certain fundamental conditions that users must meet to adapt the manufacturing processes to Industry 4.0. For this, as in the past, there is a major need for modeling and simulation tools in this industrial age. In the creation of industry-driven predictive models for machining processes, substantial progress has recently been made. This paper includes a comprehensive review of predictive performance models for machining (particularly analytical models), as well as a list of existing models' strengths and drawbacks. It contains a review of available modeling tools, as well as their usability and/or limits in the monitoring of industrial machining operations. The goal of process models is to forecast principal variables such as stress, strain, force, and temperature. These factors, however, should be connected to performance outcomes, i.e., product quality and manufacturing efficiency, to be valuable to the industry (dimensional accuracy, surface quality, surface integrity, tool life, energy consumption, etc.). Industry adoption of cutting models depends on a model's ability to make this connection and predict the performance of process outputs. Therefore, this review article organizes and summarizes a variety of critical research themes connected to well-established analytical models for machining processes. [ABSTRACT FROM AUTHOR]

On-line monitoring of the machining processes provides to detect the amount and type of tool wear which is critical for the determination of remaining useful lifetime of cutting tool. According to Industry 4.0 revolution, the machining performance in terms of cutting forces, surface roughness, power consumptions, tool wear, tool life, etc. needs to be automatically monitored because the unfavorable conditions in machining cause chatter vibrations, tool breakage, and dimensional accuracy. Therefore, the usage of advanced sensor systems plays a key role in achieving the improved machining characteristics in terms of less human effort, errors, production time, etc. and fulfills the requirement of Industry 4.0. Hence, this review presents the holistic knowledge of online detection systems including sensors and signal processing software preferred in mechanical machining operations. Initially, this paper is starting with the up-to-date literature introduction section followed by type of sensors used in machining, online detection methods in machining, challenges and suggestions, etc. Eventually, the article concluded the findings and future remarks especially focused on the theme of Industry 4.0. In the end, it is worthy to mention that this review paper is very helpful for researchers and academicians working in the industrial sectors. [ABSTRACT FROM AUTHOR]

Being easily fabricated, welded, biocompatible, having a high strength-to-weight ratio, withstanding comparatively high temperatures up to 800 °C and low modulus of elasticity make grade titanium and its alloys an important choice for automotive, biomedical and aerospace industries. In contempt of the different pleasant assets of Ti–6Al–4V alloy, the operation of this alloy is restricted especially when it comes to tribological and surface morphological characteristics. Enhancing these properties is important, for this purpose, a diversity of attempts and studies have been conducted. This paper mounts a review of morphological and tribological behaviors of titanium alloys including Ti–6Al–4V against different materials counting with carbide tools and other types of materials under dry and lubricated sliding conditions. The surface morphological, wear, and other properties have been discussed in this review article. [ABSTRACT FROM AUTHOR]

The material steadily wears away from touching surfaces when two solid entities are constantly moving against one other. When more parameters and extreme materials are involved in tribological testing, then it is very difficult to analyze and observe the working phenomena. With this aim, this study uses the gaussian process regression (GPR) approach to estimate friction forces when testing SS 316 L against 100 Cr6 alloy under cryogenic and cryo + minimum amount lubrication conditions. The friction forces from ball-on test experiments were used to develop the prediction models. Then, the wear surfaces and surface morphology are analyzed under cryo and cryo+MQL conditions. The results demonstrated that the combination of MQL and CRYO cooling reduced the friction forces more than 10 times for sliding distances above ∼30 m and loads below ∼25 n. Hence, the cryo+MQL conditions are beneficial in enhancing the tribological features due to the dual cooling and lubricating effects. [ABSTRACT FROM AUTHOR]

Tool wear is intimately related to intelligent operation and maintenance of automated production, workpiece surface quality, dimension accuracy, and tool life. Therefore, it is necessary to improve the production efficiency and quality by predicting tool wear values. The purpose of this research is to use machine learning and image processing methods in estimating the tool wear values when turning AA7075 aluminum alloy. In addition, the in-depth analysis of cutting tools at different parameters were examined with SEM and EDS analysis. The results shown that there was a 44.40% increase in tool wear when the cutting speed was raised by 100% while feed rates were maintained at the same level. On the other hand, there was a 22.78% increase in tool wear seen when the cutting speed was maintained at the same level. In addition, the difference between the actual values and the image processing model is 3.5%, and the difference between the Multilayer Perception (MLP) model and the linear regression (LR) model is 5% and 7%, respectively. [ABSTRACT FROM AUTHOR]

• Machine learning based real time monitoring and measurement of energy consumption characteristics. • Energy characteristics at different stages of machine tools were monitored. • Classification were performed with different ML methods. • Random forest approach obtained higher efficacy with maximum overall accuracy. The development of cutting-edge monitoring technologies such as embedded devices and sensors has become necessary to ensure an industrial intelligence in modern manufacturing by recording machine, process, tool, and energy consumption conditions. Similarly, machine learning based real time systems are popular in the context of Industry 4.0 and are generally used for predicting energy needs and improving energy utilization efficiency and performance. In addition, sustainable and energy-efficient machining technologies that can reduce energy consumption and associated negative environmental effects have been the latest topic of much study in recent years. Concerning this regard, the present work firstly deals with the real time monitoring and measurement of energy characteristics while machining titanium alloys under dry, minimum quantity lubrication (MQL), liquid nitrogen (LN 2) and hybrid (MQL + LN 2) conditions. The energy characteristics at different stages of machine tools were monitored with the help of a high end energy analyser. Then, the energy signals from each stage of machining operation were predicted and classified with the help of different machine learning (ML) models. The experimental results showed that MQL, LN 2 , and hybrid conditions decreased the total energy consumption by averagely 2.6 %, 17.0 %, and 16.3 %, respectively, compared to dry condition. The ML results demonstrated that the accuracy of the random forest (RF) approach obtained higher efficacy with 96.3 % in all four conditions. In addition, it has been noticed that the hybrid cooling conditions are helpful in reducing the energy consumption values at different stages. [ABSTRACT FROM AUTHOR]

Grinding is one of the important machining processes that are widely applied in precision manufacturing. In the beginning, studies mostly focused on dry machining. In time, emerging technologies have led to change in the development of the machining process. New techniques and tools have been developed over the last decade that has brought the process to an advanced place. At first, flood cooling has removed the burning problems in the grinding process. After that, a new technique was developed which is known as minimum quantity lubrication (MQL). This technique is a recognized opportunity to eliminate environmental concerns. This paper reviews some of the common as well as advanced MQL systems specifically used in grinding operations. The effect of MQL and other cutting parameters on cutting forces, surface roughness of the machined workpiece, tool wear, temperature, specific cutting energy, and residual stress is outlined. This paper also addressees the recent trend of cooling systems in the grinding process. After reading this research paper, one can easily get an overview of the previously conducted research to find the output parameter trends in MQL condition. The reader can infer from this paper in which direction the development trend in grinding is in the machining process. [ABSTRACT FROM AUTHOR]

The recent step towards "Sustainable Manufacturing (SM)" and efforts to reduce the consumption of cutting fluids have become the hot topic of research these days. Various efforts and strategies have been employed in the modern manufacturing sector to control the environmental pollutions generated from the application of cutting fluids. Therefore, in this holistic work, one such effort of reducing the consumption of cutting fluid is employed with the application of minimum quantity lubrication (MQL) and tool texturing. The turning trials were made on titanium alloy:Ti3Al2.5V alloy under dry and MQL conditions using textured and non-textured tools. The tool life, average surface roughness, specific cutting energy, air quality, and chip morphology were studied with the aid of the above-subjected conditions. In the end, the socio-economic aspects of all cooling conditions were studied and analyzed in the context of sustainable manufacturing. The outcomes of this study reveal that the combination of textured tools and minimum quantity lubrication considerably enhance the machining and sustainability performance as contended with other conditions. However, the air quality factor, i.e., PM2.5 particle generation, was less in the case of a textured tool with MQL conditions. Overall, it is worthy to mention that the combination of tool texturing and MQL cooling conditions has been considered as one of the potential combinations in the area of green machining. [ABSTRACT FROM AUTHOR]

Carbon fiber–reinforced polymers (CFRPs) are vulnerable to damage locally through machining operations due to an applied cutting force and high-temperature generation. Though traditional lubri-cooling medium will reduce the heat-generated damage of CFRPs, the use of synthetic fluids, however, significantly affects the environment and public health equally. Therefore, this paper aims to explore the milling performance of CFRPs in sustainable lubri-cooling mediums, i.e., dry, minimal lubrication (MQL), cryogenic-liquid nitrogen (N2liquid), and carbon dioxide (CO2ice). Furthermore, the correct choice of process parameters and lubri-cooling environments influences the cutting mechanism in any metal cutting operations. Accordingly, response surface methodology (RSM) is used to create a relationship between responses to machining inputs. In addition, two evolutionary techniques named Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) were used to execute parametric optimization. Eventually, the performances of the adopted approaches are compared in this manuscript, which reveals the prediction made by NSGA-II and PSO is quite consistent with the experimental results. However, in view of convergence characteristics and computational time, the PSO is shown to surpass the NSGA-II approach. Moreover, empirical cumulative distribution–based data analysis indicates that all responses are good compatible with the function of the normal distribution. At the 95% confidence level, the established ANOVA models were found to be substantial. Furthermore, lubri-cooling medium was the most critical factor affecting the response parameters with a 49% contribution in minimizing Fr, 46% contribution in decreasing VB, 38.89% contribution in Ra, and 50.21% contribution in reducing the T value. [ABSTRACT FROM AUTHOR]

• Machining performance is improved using machine learning in traditional methods. • The environmentally friendly lubricants MQL and nano-MQL has also been utilized. • The Ridge regression and Decision tree are utilized to anticipate the data. Machine learning has numerous advantages, especially in the rapid digitization of the manufacturing industry that combines data from manufacturing processes and quality measures. Predictive quality allows manufacturers to make informed predictions about the quality of their products by analyzing data gathered during production. The quality of the machining, the total cost and the computation time need to be improved using contemporary production processes. With this concern, a series of experiments were carried out on Bohler steel both in dry, Minimum Quantity Lubrication (MQL) and nano-MQL conditions in varying quantities to explore the tool wear. In comparison to dry conditions, the utilization of MQL in machining processes demonstrates significantly enhanced efficacy in mitigating flank wear. The reduction in flank wear ranges from around 5% to 20% to 25%, contingent upon the application of MQL on the flank face, rake face, or both faces simultaneously. After that, the results of the tests were evaluated with the models of machine learning (ML) to determine which environment was optimal for cutting under both real and artificial circumstances. [ABSTRACT FROM AUTHOR]

• Hybrid lubri-coolant is proposed by mixing ethanol-biodegradable ester oil. • Dry ice (solid CO 2) added (−76 °C) to this novel hybrid cooling mixture. • Thermophysical properties of lubri-coolants are investigated experimentally. Recent pandemics played a cardinal role in developing health-conscious behavior and pushed the industries to seek eco-benign cutting fluids to improve machinability. Therefore, a sustainable hybrid lubri-coolant is proposed by mixing ethanol-biodegradable ester oil in varying proportions (1:0.25, 1:0.5, and 1:1). In this work, dry ice (solid CO 2) has been added (−76 °C) to improve the cooling capabilities by sublimation. The thermophysical properties along with the surface hardening of machined Ti-6Al-4V alloy was investigated experimentally and the results were compared to without dry ice. Experimental findings showed a reduction in specific heat, density, and viscosity while an enhancement in thermal conductivity by mixing dry ice. After dry ice was added, the specific heat of ethanol dropped by 40%. When ester oil was combined with dry ice, its specific heat also decreased by 50.4%. Therefore it is worthy to mention that the hybrid lubri coolant based on dry ice-based ethanol/ester oil could be an alternative to achieve high-speed machining parameters in machining hard to cut materials for aerospace Industry. [ABSTRACT FROM AUTHOR]

Under different working conditions, the tribological characteristics of materials show a complicated and non-linear relation. As a result, it is crucial to advance tribology by prioritising a data-driven strategy to estimate service capability in order to expedite the material design and preparation. With this aim, the present work firstly deals with the implementation of novel deep learning technologies in predicting tribological characteristics of additively manufactured and casted 316 stainless steel against 100 cr6 alloy. The coefficient of friction and frictional forces data from ball-on-flat experiments were used to develop the different deep learning models i.e., CNN, CNN-LSTM, and ATTENTION based CNN. Then, the wear tracks of tested samples were analysed with the SEM analysis. According to the findings of the wear rate, the AM material wears with an average of 58% less intensity than the casted material. In addition, the performance of the CNN Attention model demonstrated higher levels of accuracy and lower loss metrics in comparison to the CNN and CNN-LSTM classifiers. [ABSTRACT FROM AUTHOR]

The proper implementation of sustainable manufacturing processes is an effective step towards a clean environment. The modern cooling strategies applied in the manufacturing sector have presented promising solutions that enable economic growth and ecological environment. In machining operations, cryogenic cooling and minimum quantity lubrication (MQL) have been extensively utilized to replace conventional cooling techniques. Thus, this work offers a detailed review of major works focused on manufacturing processes that use some of these sustainable cooling/lubrication modes (i.e., MQL, nanocutting fluids, nanofluid-based MQL strategy, and other miscellaneous MQL upgrades). The main driver of this study is to create a bridge between the past and present studies related to MQL and MQL upgrades. In this way, a new guideline can be established to offer clear directions for a better economic vision and a cleaner manufacturing process. Thus, this review has mainly focused on the machining of the most commonly used materials under MQL-related methods in conventional operations including turning, milling, drilling, and grinding. Current work provides a detailed insight into the major benefits, limitations, as well as mechanisms of cooling strategies that directly affects the machinability performance from a sustainable point of view. In summary, further potential upgrades are indicated so that it will help to drive more sustainable approaches in terms of cooling and lubrication environment during machining processes. [ABSTRACT FROM AUTHOR]

Excessive use of coolant is undesirable in machining due to environmental consciousness; thereby, small but efficacious (improved thermal and tribological properties) amount of coolant has been implemented using minimum quantity lubrication (MQL). In this study, attention was focused on the experimental investigations on tool flank wear, chip morphology, surface roughness (Ra and Rq) and chip-tool interface temperature in the machining of hardened steel (~ 40 HRC) under olive oil-assisted MQL spray system. As investigating factors, the cutting speed, feed rate, and depth of cut were oriented by following the Taguchi orthogonal array. Then, the cooling and lubrication mechanism of the olive oil-assisted MQL system has been discussed. Outcomes of this study showed that MQL is capable of generating favorable machining outcomes, i.e., lower tool flank wear, reduced temperature, and surface roughness in comparison with dry cutting. The reductions in Ra, Rq, and cutting temperature were about 23.4%, 23.8%, and 24% respectively in terms of mean values. The two types of dominant chip shapes, i.e., (1) continuous tubular and (2) discontinuous small diameter chips, were produced under the dry and MQL-assisted cooling method. In the nutshell, it is appropriate to claim that the overall thermal and tribological properties of olive oil-assisted MQL system are responsible for fruitful results during turning of hardened steel. [ABSTRACT FROM AUTHOR]

The constant pressure on the manufacturers to innovate and implement sustainable processes has triggered researching on machining with low carbon footprint, minimum energy consumption by machine tools, and improved products at the lowest cost—this is exactly done in this paper. Herein, the advanced cooling lubrication, i.e., nanofluid assistance, besides dry and flood cooling, during machining has been experimented, and used as the basis for sustainability assessment. This assessment is carried out in respect of surface quality and power consumption as well as the impact on environment, cost of machining, management of waste, and finally the safety and health issues of operators. For a better sustainability, a systematic optimization has been performed. In addition, the solution for an improved machinability has been proposed along with the statistically verified mathematical models of machining responses. Results showed that the nanofluid minimum quantity lubrication showed the most sustainable performance with a total weighted sustainability index 0.7, and it caused the minimum surface roughness and power consumption. The highest desirable (desirability = 0.9050) optimum results are the cutting speed of 116 m/min, depth of cut 0.25 mm, and feed rate of 0.06 mm/rev. Furthermore, a lower feed rate is suggested for better surface quality while for reduced power consumption the lower control factors are better. [ABSTRACT FROM AUTHOR]

Based on these judging criteria, it is clear that though PSO and BFO revealed identical results, the PSO is more attractive with respect to aforementioned comparative advantages. Although the results obtained by both techniques are the same, the success rate of PSO is 83.4% as compared to the 65.8% success rate for BFO. [Extracted from the article]

In machining of soft alloys, the sticky nature of localized material instigated by tool-work interaction exacerbates the tribological attitude and ultimately demeans it machinability. Moreover, the endured severe plastic deformation and originated thermal state alter the metallurgical structure of machined surface and chips. Also, the used tool edges are worn/damaged. Implementation of cooling-lubrication (C/L) agents to reduce friction at faying surfaces can ameliorate overall machinability. That is why, this paper deliberately discussed the influence of pure C/L methods, i.e., such as dry cutting (DC) and nitrogen cooling (N2), as well as hybrid C/L strategies, i.e., nitrogen minimum quantity lubrication (N2MQL) and Ranque-Hilsch vortex tube (RHVT) N2MQL conditions in turning of Al 7075-T6 alloy, respectively. With respect to the variation of cutting speed and feed rate, at different C/Ls, the surface roughness, tool wear, and chips are studied by using SEM and 3D topographic analysis. The mechanism of heat transfer by the cooling methods has been discussed too. Furthermore, the new chip management model (CMM) was developed under all C/L conditions by considering the waste management aspects. It was found that the R-N2MQL has the potential to reduce the surface roughness up to 77% and the tool wear up to 118%. This significant improvement promotes sustainability in machining industry by saving resources. Moreover, the CMM showed that R-N2MQL is more attractive for cleaner manufacturing system due to a higher recyclability, remanufacturing, and lower disposal of chips. [ABSTRACT FROM AUTHOR]

Abstract Modern manufacturing industries thrive for energy efficient, clean and sustainable machining processes. However, achieving these objectives becomes difficult especially in machining Ti-6Al-4V as it retains its properties at high temperature. Cryogenic liquid nitrogen (LN 2) is a clean machining environment that has potential to improve the machinability performance for Ti-6Al-4V. LN 2 promotes sustainability and facilitates low carbon emission. Orientation and number of employed LN 2 jets influence the cutting energy, quality and productivity. Moreover, a balance between energy consumption and quality-productivity is required for sustainable production. In this respect, this research work studies the cutting force, specific energy, temperature, surface quality (i.e. surface roughness), and material removal rate under the impingement of LN 2 as mono-jet and dual-jets. This study has three parts: evaluation of the role of factors on the output parameters, optimization of parameters, and lastly the life cycle assessment (LCA) of cryogenic LN 2 assisted machining. Owing to irreconcilable nature of single-objective optimization, multi-response optimization was conducted using Grey-Taguchi integrated approach. It was found that LN 2 dual-jets were most effective in reducing the specific energy consumption and temperature, and improving surface quality. This can be attributed to the faster and effective heat removal by LN 2 from the critical interfaces. Other optimum parameters were cutting speed of 140 m/min and feed rate of 0.16 mm/rev. It was found that LCA showed that there is a clear relation between cooling strategy and environmental aspects such as resources, energy, human health, and biodiversity, etc. that directly affects the machining performance of Ti-6Al-4V alloy. Graphical abstract Image Research-Highlights • Turning of hardened Ti-6Al-4V using dry, mono-jet and dual-jets of cryogenic conditions. • Study of cutting force, specific energy, temperature, surface quality and material removal rate. • Evaluation of the role of factors on the output parameters. • Optimization of parameters using Grey Relational Analysis (GRA). • Life Cycle Assessment (LCA) of cryogenic LN 2 assisted machining. [ABSTRACT FROM AUTHOR]

The Inconel 718 alloy, a difficult-to-cut superalloy with an extensive demand on aircraft and nuclear industries, being a low thermally conductive material exhibits a poor machinability. Consequently, the cutting tool is severely affected, and the tool cost is increased. In this context, an intelligent solution is presented in this paper—investigation of minimum quantity lubrication (MQL) and the selection of best machining conditions using evolutionary optimization techniques. A series of milling experiments on Inconel 718 alloy was conducted under dry, conventional flood, and MQL cooling modes. Afterward, the particle swarm optimization (PSO) and bacteria foraging optimization (BFO) were employed to optimize the cutting speed, feed rate, and depth-of-cut to minimize the flank wear (VBmax) parameter of a cutting tool. Though both the PSO and BFO models performed well, the validated results showed the superiority of PSO. Furthermore, it was found that the MQL performed better than the dry and flood cooling condition with respect to the reduction of the tool flank wear. [ABSTRACT FROM AUTHOR]

To address the negative consequences of conventional mineral-based cutting fluids, manufacturing industries strive to utilize less harmful and environmentally friendly cutting fluids. The non-toxicity and biodegradability of vegetable oils present them as a suitable replacement for cutting fluids based on mineral oil. However, vegetable oil possesses inferior oxidation and thermal stability at elevated temperatures due to which nanoparticles are blended with vegetable oil to improve the lubrication and cooling characteristics. In this perspective, the influence of nano-suspended coconut oil (CO) has been investigated during the turning of AISI-1040 steel. The various wt% concentrations of nano-Al2O3 ranging from 0.25 to 1.50% were added in CO to prepare the nanofluid. Then, the machining operation was performed under dry cutting, flood cooling with conventional mineral-based oil, minimum quantity lubrication with pure coconut oil (CO-MQL), and MQL with nanofluids (NF-MQL). The performance was evaluated through tool wear, cutting temperature, surface integrity, cutting tool vibration, and microhardness. The findings revealed that NF-MQL significantly reduces tool wear in comparison with other selected cutting environments. The 53%, 38%, and 25% reduction in flank wear and 37%, 31%, and 17% reduction in crater wear depth in correlation with dry cutting, flood cooling, and CO-MQL demonstrate the superiority of NF-MQL in increasing the tool life. NF-MQL also results in superior surface finish quality with an improvement of 54%, 32%, and 28%, reduction in cutting temperature by 55%, 38%, and 20%, minimizing the tool vibration by 68%, 45%, and 24% in comparison with dry cutting, flood cooling, and CO-MQL cutting environments. [ABSTRACT FROM AUTHOR]

Extreme thermal conditions in machining of hardened steel impair the overall performance especially the tool life and surface quality. Although, the cutting fluids are known for improving the tool life and surface quality, yet they have adverse effects on the human health as well as environment because of the presence of potentially harmful chemical ingredients. Hence, in view of the above problems associated with the cutting fluids, the implementation of sustainable methods is advantageous which further reduces the use of cutting fluids i.e. dry, minimum quantity lubrication (MQL) spray system and solid lubricant with compressed air cooling system. In this paper, the effect of three sustainable techniques, along with the traditional flood cooling system, on prominent machining indices such as cutting temperature, surface roughness, chip characteristics and tool wear in plain turning of hardened AISI 1060 steel has been investigated. In the end, the Pugh matrix environmental approach has been used to establish the sustainability assessment model (in terms of environmental effect, operator health, coolant cost, recycling cost and disposal, part cleaning and selected machining responses) among the used cooling/lubrication conditions. The research findings show that use of MQL system can ameliorate the heat transfer problem, and divulge quite promising results. Therefore, it is suggested that MQL system, provides environment friendliness, cleaner production and helps to improve the desirable machinability characteristics. [ABSTRACT FROM AUTHOR]

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editors. Following receipt of whistle-blower complaints, an investigation of this and related papers was conducted. The Editor-in-Chief no longer has confidence in the scientific integrity of this paper as similar images have been used in various articles in multiple journals claiming varying conditions, which violates our publishing policies. Table 6, Table 7, and Figure 9 in this article were reported differently in other articles (e.g., The International Journal of Advanced Manufacturing Technology, 2019, 102, pp. 3995–4009, https://doi.org/10.1007/s00170-019-03453-3). These results have been carefully checked and reviewed by a duly constituted expert committee, and are concluded to be unreliable findings. Communication with the corresponding author raised further concerns with the integrity of this work and proposed revisions deepened, rather than clarified, the uncertainty as to what materials/parameters were used in this study. One of the conditions of submission of a paper for publication is that authors of reports of original research should present an accurate account of the work performed as well as an objective discussion of its significance. Underlying data should be represented accurately in the paper. A paper should contain sufficient detail and references to permit others to replicate the work. As such this article represents a misuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process. [ABSTRACT FROM AUTHOR]

The application of sustainable techniques in the machining of aerospace materials is quite prominent for attaining viability with respect to economic and environmental aspects. The recently embraced method in the context of sustainable machining includes the application of MQL (Minimum Quantity Lubrication) technique. This article presents an experimental investigation, comparison of empirical and experimental results, complemented with a desirability optimization technique, for study the impact on cutting forces, surface roughness, tool wear, surface topography, micro-hardness and surface chemical composition in the turning of the aerospace material – titanium (grade-2) alloy considering MQL conditions. In order to achieve this aim, firstly, the turning experiments were performed under varying conditions of process parameters such as cutting speed, feed rate and approach angle by using response surface methodology (RSM). Then, the analysis of variance and regression analysis were considered to analyze the effect of machining parameters on selected responses. Further, the comparison of empirical and experimental results for cutting force components has been made by using Kienzle approach. In the end, the model validation is performed by comparing the analytical predicted results of cutting forces with experimental and desirability approach that are in good agreement. The investigations showed that turning at low cutting speeds (200 m/min), low feed rates (0.10 mm/rev) and high side cutting edge angle (90°) ensures the high quality of surface roughness, lower cutting forces, tool wear and micro-hardness. [ABSTRACT FROM AUTHOR]

In metal cutting operations, the proper selection of machining parameters and cutting fluids affects the cutting mechanism, which is associated to the cutting forces, tool wear, cutting temperature and surface finish of the machined part. For this purpose, the effect of cutting fluid types is investigated as a function of three machining parameters (cutting speed, feed rate and approach angle) on responses (cutting force, cutting temperature, tool wear and surface roughness) while turning titanium alloy under Nano-Fluid based Minimum Quantity Lubrication (NFMQL) environment. The experiments are conducted based on response surface methodology and a combined objective function using the output parameters was generated. Further, the parametric optimization was performed through two evolutionary techniques, i.e., Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO). The results are analyzed and also compared with the traditional desirability function approach technique. [ABSTRACT FROM AUTHOR]

In machining processes, there are contradictions between high efficiency and environmentally-friendly machining. This indicated that there is a major potential for sustainable machining to both increase efficiency and protect ecological balance. For this, the employment of effective methods has become imperative to reduce resource use. In this way, the use of analysis and optimization tools to select the tool material, cutting parameters, cooling/lubrication conditions, etc., will be a benefit for minimizing waste without sacrificing efficiency. In the literature, researchers have used various methods to reveal the requirements of sustainability. However, reaching the concept of sustainable machining by using one more than technique confuses the readers. Therefore, it was deemed necessary to present and discuss the current methods, models and analyzes in a comprehensive review paper. In this context, this paper reviewed the previously published works, especially focusing on sustainability and energy consumption modeling methods in machining operations. At the end of the study, it was seen that LCA provides a systematic and quantitative view of the system and thus can act as a decision support tool. Moreover, it can give an idea to the manufacturers about the improvement of the process and the areas of innovation. However, the method has several disadvantages such as relatively expensive and specific software, obtaining inventory data, impractical to use, time-consuming and requires large amounts of data. Various mathematical models and algorithms have been developed to deal with the complex situations and offer a more practical use compared to LCA. However, it is difficult to state that clear results have been achieved thanks to these models. It was seen that in complex machining processes, only approximate results can be found with models, which leads to questioning the reliability of the models. [ABSTRACT FROM AUTHOR]

Hybrid lubri-cooling is a latest technology that provides synergistic cooling and lubrication effect in the machining area especially in the cutting of titanium and its alloys. In this current study, cryogenic-LN 2 , minimum quantity lubrication (MQL), and hybrid cryogenic LN 2 -MQL are applied and compared against dry medium in perspective of in-depth analysis of tool flank wear, EDS mapping, and intensity of tool wear. Experimental results showed that in comparison with dry, hybrid LN 2 -MQL substantially reduced the tool flank and rake wear followed by LN 2 , MQL, and dry conditions, respectively. Additionally, the SEM and EDS analysis depicted relatively less severe wear and chemical elements adhesion on the tool's main cutting edge, while turning titanium alloy under a hybrid LN 2 -MQL lubri-cooling environment. In addition, the dry condition has maximum value of tool wear progressions i.e., 1.04 mm and hybrid LN 2 -MQL have 0.06 mm while machining titanium alloys. When tool wear is evaluated from a tribological point of view, the reduction in flank wear value compared to dry machining is 89.4 %, 92.3 % and 94.2 % owing to MQL, LN 2 , MQL and hybrid LN 2 -MQL cutting strategies. In terms of crater wear, the improvement was 87.7 %, 90.4 % and 90.8 % thanks to MQL, LN 2 , MQL and hybrid LN 2 -MQL. [ABSTRACT FROM AUTHOR]

The titanium carbide is considered as a hard to cut material and it is very helpful in critical applications especially in guide roller applications. This study investigated the machining based tribological characteristics of TiC rollers during hard turning under sustainable cooling/lubrication conditions. Surface quality, power consumption, tool wear, microstructural changes, microhardness after machining, and SEM-EDX analysis were evaluated under dry, minimum quantity lubrication (MQL), cryogenic and hybrid cryo+MQL environments. Although the surface quality did not meet the expectations in dry cutting, MQL improved slightly than cryo methods. However, the best surface quality, the smallest tool wear and power consumption was obtained in the hybrid cryo+MQL lubrication/cooling method. [ABSTRACT FROM AUTHOR]

The degree of surface separation is generally used to determine the lubrication regimes. The smooth functioning of components are possible by providing the lubrication at intermediate zone, which reduces the wear and prevents severe stresses or bearing arrests. This work is also focus on lubrication regime phenomena and its influence on tribological characteristics of additively manufactured 316 steel under novel lubrication environment. The tribology tests were performed on ball-on flat machine under dry, minimum quantity lubrication (MQL), cryogenic and hybrid cryo+MQL conditions. The 100Cr6 ball has been used against additively manufactured 316 steel and the theoretical exploration of lubrication regimes has been discussed along with other tribological characteristics such as wear rate, surface roughness and coefficient of friction etc. The outcome demonstrated that the hybrid cryo+MQL is helpful in providing the good lubrication film and consequently improves the tribological properties. [ABSTRACT FROM AUTHOR]

It is critical in today's modern manufacturing era to have a machining system that is both environmentally and economically beneficial. It is therefore necessary in many ways to illustrate a relationship between technological, economic and sustainability measures in the machining of Inconel 718. In present investigation, the experimental studies are incorporated by the use of the dry and MQL (minimum quantity lubrication) environments, as well as cryogenic-LN 2 and cryogenic-CO 2 environments. In terms of technological, sustainability, and economic metrics, the results show that cryogenic-LN 2 performed better, followed by cryogenic-CO 2 , MQL, and dry conditions. As turning Inconel 718, LN 2 assisted machining reduce total machining costs and energy usage considerably when compared to dry, MQL, cryogenic-CO 2 environments. In addition, the LN 2 cooling environment has been shown to significantly reduce machining outputs such as cutting force, tool wear, and surface roughness. LN 2 conditions was found to be most promising as it has decreased the cutting force by 32.1%, tool flank wear by 33.33% and total energy consumption by 18% compared to dry machining conditions. It's worth noting that modern lubri-cooling technologies help the aerospace sector be more sustainable by decreasing resource consumption, enhancing environmental advantages, and improving machining features. [ABSTRACT FROM AUTHOR]

• FEM simulation of cutting forces and cutting temperature were performed. • Advantedge software was used for FEM simulation. • Experiments were performed to validate the results. Aluminium alloys are widely used in modern engineering applications such as automobile, aerospace etc because of its characteristics. The machining of aluminium alloys are also considered as difficult because of its sticky and soft nature, low thermal conductivity, strain hardening effect etc. The cooling conditions employed at cutting zone improved the machining performance but the resources, material consumption, skilled labor etc. are also required for performing the machining experiments. Therefore, the simulation of process parameters with the help of Finite Element Modelling (FEM) during machining is highly researched topic these days. In this work, a new practice from measurement science i.e., FEM simulation was performed with AdvantEdge software and the prediction models were developed for evaluating the cutting forces and cutting temperature while machining AA2024-T351 alloy under dry, liquid nitrogen (LN 2) and carbon dioxide (CO 2) conditions. Initially, the 3D turning model was developed and the results were compared with experimental findings. The results obtained from simulation model are very close with experimental results with minimum standard value of 0.67 (5.7%) for cutting forces and 4.58 (6.16%) for cutting temperature. Thus, it is worthy to mention that the 3D FE model is efficient and effective to predict and measurement results with minimum error. [ABSTRACT FROM AUTHOR]

The poor thermal conductivity of Inconel 718 leads to higher cutting temperatures and, as a consequence, rapid tool degradation is a common phenomenon. As a result, a hybrid lubri-cooling environment for turning Inconel 718 alloys is proposed, incorporating the theory of cryogenic cooling and minimum quantity lubrication (Cryo-MQL). For improved lubri-cooling effect, Cryo-MQL integrates the application of a minimum quantity of vegetable oil and liquid nitrogen from two distinct nozzles in the cutting zone. Surface roughness, cutting temperature, tool wear, chip morphology, and micro-structure of the machined surface were evaluated for different lubri-cooling mediums: dry, MQL, Cryogenic, and Cryo-MQL. In comparison to a dry medium, the Cryo-MQL environment decreases surface roughness, cutting temperature, and tool wear by 60.6%, 37%, and 19.5%, respectively. Adhesion and abrasion were patented to be common tool wear types, as per SEM micro-graphs. Eventually, in the Cryo-MQL environment, a spike in micro-hardness value has been reported. However, during processing with Cryo-MQL, the grain structure of the working material is found to be smaller as compared to other mediums. • Turning of the aerospace alloy under sustainable lubri-cooling mediums were performed. • Wear tribology of the cutting inserts was investigated using FESEM and EDX. • Microstructure and micro-hardness of the machined surfaces were also examined. • Hybrid cryo-MQL provides significant results. [ABSTRACT FROM AUTHOR]

The reduction of weight elements is considered as a major objective of several manufacturing companies. This objective will help in growing application sections of the used fiber composites for important structural elements. Modern fiber metal laminate (FML) having lightweight properties is established to be used instead of other substances in different applications including those related to the aerospace industrial sector. Fiber metal laminate is being deemed as an alternative significant substance that is being extensively explored due to its operation, unlike other current materials. There are different profitable FML such as GLARE (glass-reinforced aluminum laminate), established on elevated intensity ARALL glass fibers (aramid-reinforced aluminum laminate), built on fibers of aramid, in addition to CARALL (carbon-reinforced aluminum laminate), centered on fibers of carbon. This paper analyzes important information that contributes to the mechanical characteristics of FMLs under tensile, flexure, impact, etc. conditions. [ABSTRACT FROM AUTHOR]

Machining of titanium is considered as a challenging process due to its ability to interact with various tool materials when critical cutting temperature is exceeded, resulting in excessive tool wear and poor surface finish, etc. To exhibit an efficient machining process, this research study has experimentally investigated the key quality indicators of machinability, namely surface roughness, cutting temperature, tool wear, in-depth analysis of worn tool and cutting force in the machining process of α-β titanium alloy, which used in critical applications, under three sustainable cooling environments i.e., dry, liquid nitrogen (LN 2) and carbon dioxide (CO 2). The effect of cutting speed and feed rate on such performance measures were examined under a function of cooling strategy as the best substitute in machining. As a result, the feasibility of LN 2 cooling has been confirmed to be more significant for the machining of α-β titanium alloy when compared to dry and CO 2 machining strategies. To sum up, cryogenic cooling (LN 2 cooling) assisted machining of α-β titanium has acquiesced as a sustainable strategy in the context of environmental consciousness. • Turning of Ti6Al4V alloy under various sustainable conditions was investigated. • Tool wear, surface roughness, cutting force and temperature was evaluated. • Worn tools were analyzed in depth with SEM and EDS tools. • LN 2 and CO 2 cooling contributed significantly to improving machining performance. [ABSTRACT FROM AUTHOR]

The present research focuses on comprehensively evaluating energy consumption and other vital machining characteristics during the turning process, aiming to optimize efficiency while minimizing environmental impact. The experimental data is collected through a series of machining tests on EA1N railway axle steel under dry, minimum quantity lubrication (MQL), and cryogenic cooling conditions. Under these cutting conditions, the machinability criteria (energy consumption, tool wear, surface quality, chip morphology) of train wheel axle steel were tried to be improved. As a result, cryogenic cooling at constant cutting speed gave 40% and 53% better results in terms of energy consumption than MQL and dry environment, respectively. When the same situation was examined in terms of tool wear and surface quality, 10–18% and 8–14% gave better results, respectively. In other words, it is worthy to mention that the research findings not only benefit the manufacturing industry by optimizing resource utilization but also align with global efforts to promote environmentally conscious practices in the engineering and transportation sectors. [ABSTRACT FROM AUTHOR]

Due to extensive distribution and huge demand of energy efficient processes, the energy-saving of machining processes draws more and more attention, and a significant variety of methods have evolved to prognosis or optimise the energy consumption in machining operations. Similarly, the estimation of power consumption-cutting conditions relationships is of great importance for optimizing processing costs and for cleaner machining. Compared to traditional methods, machine learning (ML) approach is one of the effective analysis options to model machinability indicators such as cutting force, tool wear, power consumption and surface quality. In this study, PH13-8Mo stainless steel was machined with coated carbide inserts using primarily Dry, MQL, nano-Graphene + MQL, nano-hBN + MQL, Cryo, Cryo + MQL cutting environments. Power consumption and its signals during milling were measured and different machine learning models were applied to estimate the Pc. To develop the Pc model based on the ML algorithm, 70% of the power consumption data is reserved for training and 30% for testing. In all cutting environments, power consumption increased by an average of 3.14% as feed speed increased. The reduction in Pc compared to the dry cutting was calculated as an average of 2.2%, 3.17%, 2.57%, 4.88% and 5.45% for MQL, nano-Graphen + MQL, nano-hBN + MQL, Cryo, Cryo + MQL, respectively. It is seen that the developed prediction model can reflect the power consumption-parameter relationships at high accuracy. [ABSTRACT FROM AUTHOR]

Mineral oil–based lubricants play an important role to serve industrial lubrication and cooling requirements. However, these oils are environmentally unacceptable due to their negative impact on human health and environmental ecology. The current research focuses on generating an eco-friendly oil which has enhanced lubrication properties. In this work, a four-ball tribometer was employed for friction and wear evaluation of a palm oil-commercial grade oil (PO-CGO) blend, which consisted of various weight fractions of functionalized multiwall carbon nanotubes (FMWCNTs) to lubricate steel-steel contacts of ball specimens mounted in tribometer. The specimens were lubricated by using 0.1 wt.% FMWCNT blended PO-CGO oil showed about 38% and 35% reduction in wear scar diameter and wear volume respectively compared to CGO lubricated test samples. Furthermore, roughness values of specimens obtained from atomic focal microscope (AFM) by using 0.1 wt.% nanomaterial blended lubricant showed about 88% lower values than that of CGO lubricated specimens. Raman spectroscopy and SEM/EDS results revealed the details of tribofilm formation and corresponding chemical composition on sliding contact surfaces of ball specimens subjected to PO-CGO and FMWCNT-blended oil lubrication. [ABSTRACT FROM AUTHOR]

Aluminum-based metal matrix composites (MMCs) offer a high strength-to-weight ratio with excellent abrasion resistance, finding vast applications in aerospace industries. However, machining these materials is difficult due to the high hardness and wear resistance resulting in a shortened tool life. In this context, Al 7075 hybrid MMC was fabricated with reinforcing elements of TiO2 and Gr (graphite) particles. Furthermore, the machinability of newly fabricated HMMC was investigated under dry, MQL with vegetable oil, cryogenic CO2, and hybrid (MQL + CO2) cutting environments. As per the originality of this work, no studies compared the machinability of Al 7075 HMMC under selected cutting environments. With the reinforcement in Al alloy, the higher cutting forces and deteriorated surface finish were observed with dry milling. The abrasion wear mechanism will dominate under all cutting environments with various feeds and speeds. The combination of MQL + CO2 cutting environments was found to be more effective in terms of cutting forces, with a reduction of 39 to 28% compared to other selected cutting environments. The surface roughness was reduced by 18%, 15%, and 13% with favorable chip generation under MQL + CO2 than that of dry, MQL, and CO2 cooling modes. Additionally, MQL + CO2 showed enhanced tool life with a significant reduction in tool wear. [ABSTRACT FROM AUTHOR]

In today’s rapidly evolving manufacturing industry, researchers and engineers are constantly seeking innovative methods to improve machining processes. One such area of interest is the use of electrical discharge machining (EDM) for difficult-to-machine metals like SS316. This research compares the performance and economic aspects of traditional EDM and powder-mixed EDM when machining SS316 using copper electrode. Graphite powder dispersed in biodegradable palm oil is investigated as a dielectric media with the aim of enhancing EDM performance. According to the findings, the analysis of the cutting performance of different machinability aspects revealed that using graphite powder mixed with palm oil as a dielectric in EDM outperformed conventional EDM relating to material removal, surface finish, surface hardness, electrode wear rate and hole overcut. The flushing condition and unique properties of graphite powder and palm oil, such as cooling, and thermal conductivity, contributed to the improved performance observed in EDM processes. These findings highlight the potential of graphite powder mixed with palm oil as a promising alternative dielectric in EDM, offering enhanced machining capabilities and improved surface quality. The total machining expenditure per part under PMEDM (INR 505.50) is lowered by 9.2% than expenditure under conventional EDM (INR 525). The surface microhardness of the machined component attained using graphite powder-mixed EDM is enhanced in comparison to that achieved using standard EDM due to the creation of a carbon-rich re-solidified layer. [ABSTRACT FROM AUTHOR]

Sustainable manufacturing has become a global and societal goal. Although its execution is much slower, the manufacturing sector is also slowing down the unsustainable practices. One of the difficulties in the implementation of sustainability is to re-engineer its evaluation for specific fields. This study brings sustainable manufacturing underpinned an overall performance index (OPI) by integrating machinability metrics, sustainability metrics, and their comprehensive sustainability evaluation. It involves quantitative and qualitative factors such as the operator's health, shop floor environment, air quality, chip removal, and surface quality of the product in this assessment process. In this attempt, the application of the framework is presented for the assessment of sustainability through a case study with different green and hybrid lubri-cooling technologies in machining processes. These technologies have the potential to contribute to cleaner production by reducing the consumption of cutting fluid, cutting tools, energy, and carbon emissions. Considering these state-of-the-art cooling technologies, this research aims to explore their advantages and promote their application in engineering fields, thereby opening new possibilities for sustainable manufacturing practices. [ABSTRACT FROM AUTHOR]

Compared with the roughness, the three-dimensional (3D) topography parameters, surface microstructure geometric characteristics and other information can more fully evaluate the grinding quality of the slider raceway surface. In this paper, based on the 3D topography model of the abrasive particle distribution on the surface of the formed grinding wheel, the material removal mechanism between the abrasive particle and the raceway surface is analyzed. With the undeformed chip thickness distribution model as the intermediate variable, the 3D topography model of the slider raceway surface is established, and the model verification is carried out from the roughness and the geometric characteristics of the surface microstructure, respectively. At the same time, the surface microstructure is extracted from the topography model, and the effects of different grinding process parameters on the geometric characteristics such as the height to width ratio, depth to width ratio and distribution density of groove, convex peak and peak valley structures are studied. Results are shown that AS,TH increase from [0.05 0.6 μm] to [0.25 0.8 μm] and FGH grows from [0.11 1.05 μm] to [0.5 1.61 μm] when the grinding depth rises from 1 μm to 4 μm. AS, TH are firstly decreased from [0.17 0.61 μm] to [0.08 0.52 μm] and then increased to [0.26 0.78 μm], and the FGH declines from [0.34 1.01 μm] to [0.16 0.86 μm] and then increases to [0.51 1.38 μm] with the feeding speed is in [25, 28 m/min]. In addition, in the range of grinding wheel linear velocity [28, 34 m/s], the AS,TH decreases from [0.19 0.81 μm] to [0.1 0.55 μm] and the FGH decreases from [0.55 1.6 μm] to [0.2 1.1 μm]. This can prepare for the subsequent research on the impact of the topography characteristics on the friction coefficient and wear amount of the slider raceway surface. [ABSTRACT FROM AUTHOR]

The present work deals with the machining application of one of the aerospace material i.e., Inconel-800 alloy by considering the social, economic and environmental effects. The turning tests were done under four sustainable machining conditions i.e., dry, vegetable oil with minimum quantity lubrication (MQL) system, graphene nanofluid plus vegetable oil with MQL (NMQL) system and liquid nitrogen (N 2) cooling. Then, the energy consumption, carbon emissions, cost per part, average surface roughness and cutting tool wear have been measured for varied cutting speed and feed rate under selected sustainable environments. The outcomes of this study revealed that the N 2 cooling conditions reduced the total machining cost up to 9.3%, total energy consumption up to11.3%, carbon emissions up to 49.17% and tool wear up to 46.6% as compared to other cooling conditions. Significant improvement in surface roughness and tool wear have also been noticed from the outcomes of N 2 cooling conditions. Hence, it is worthy to mention that these cooling conditions promote sustainability in the aerospace sector by saving resources and extending environmental benefits. Image 1 • Turning of Inconel-800 alloy under dry, MQL, NMQL and liquid N 2 conditions were performed. • Sustainability in terms of machining efficiency, carbon emissions, energy consumption and cost modelling were evaluated. • Overall sustainability aspects were improved with liquid nitrogen cooling. • Machinability indicators such as surface roughness and tool wear were also improved with liquid nitrogen cooling. [ABSTRACT FROM AUTHOR]

In this research study, textured tools were fabricated and used for machining under different cooling conditions. The most important uniqueness of the work lies in the use of textured tools for machining Inconel-718 under dry, Nitrogen cooling and nanofluids (hBN mixed with minimum quantity lubrication) conditions. In the turning experiments, two different level of cutting speed i.e., 75 and 125 m/min and a constant level for feed rate (0.1 mm/rev) and depth of cut (0.5 mm) were considered. The above three conditions were tested and compared with and without the use of textured tools. The tool wear, surface roughness, cutting temperature, micro-hardness of machined samples and chip morphology were investigated under these subjected conditions and at turning parameters. The results demonstrated that the nanofluids with textured tool provide the superior results in comparison with other cooling conditions. These results establish textured tools as a sustainable alternative to the existing cutting tool technology being used in the manufacturing industry. • Textured tools were used to machine the Inconel-718 alloy. • Dry machining, liquid nitrogen cooling and hBN with MQL conditions were used. • Tool wear and its mechanism was investigated. • Surface roughness, micro-hardness, cutting temperature and chips were studied under these cooling conditions. [ABSTRACT FROM AUTHOR]

The necessity to progress towards sustainability has inspired modern researchers to examine the lubrication and cooling effects of vegetable oils on conventional metal cutting operations. Consequently, as an eco-friendly vegetable product, castor oil can be the right choice as Minimum quantity lubrication (MQL) base fluid. Nonetheless, the high viscosity of castor oil limits its flowability and restricts its industrial application. Conversely, palm oil possesses superior lubricity, as well as flowability characteristics. Hence, an attempt has been made to improve the lubrication behavior of castor oil. Here, six castor-palm mixtures (varying from 1:0.5–1:3) were utilized as MQL-fluid, and the values of machining responses viz. average surface roughness, specific cutting energy, and tool wear were evaluated. Furthermore, an integrated Shannon's Entropy-based Technique for order preference by similarity to ideal solution (TOPSIS) framework was employed for selecting the most suitable volume ratio of castor-palm oil mixture. The rank provided by the TOPSIS method confirmed that 1:2 was the best volume ratio for castor-palm oil mixture. Afterward, a comparative analysis demonstrated that the best castor-palm volume fraction resulted in 8.262 and 16.146% lowering of surface roughness, 5.459 and 7.971% decrement of specific cutting energy, 2.445 and 3.155% drop in tool wear compared to that of castor and palm oil medium, respectively. [ABSTRACT FROM AUTHOR]

In this work, sustainable hybrid cryogenic MQL cooling/lubrication techniques viz. Ranque- Hilsch Vortex tube plus MQL (RHVT + MQL), liquid nitrogen plus minimum quantity lubrication (N2+MQL), and liquid nitrogen (N2) are presented for turning Ti–6Al–4V utilizing CVD coated carbide insert. The tool wear, surface roughness, micro-hardness, specific cutting energy, and chip morphology are considered under sustainable cooling conditions and compared with the dry condition. The outcome revealed that the N2+MQL reduced the tons of annual coolant consumption attaining smooth surface quality, minimum built-up-edges of chips, and tool wear. Besides, minimum specific cutting energy and surface hardness achieved under N2+MQL among all cooling conditions. This endeavor is peculiar integrating sustainability and machining perspective under advanced cooling techniques for industrial application of Ti–6Al–4V. Image 1 • Turning of Ti–6Al–4V alloy under hybrid cryo-lubrications were performed. • Tribological aspects in terms of tool wear, surface roughness and micro hardness was evaluated. • Specific cutting energy and chip observations were investigated. • SEM of tools, tool profile and 3D machined surface were analysed. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of this work is to explore the erosion wear characteristics of additively manufactured aluminium alloy. Additive manufacturing (AM), also known as three-dimensional (3D) manufacturing, is the process of manufacturing a part designed in a computer environment using different types of materials such as plastic, ceramic, metal or composite. Similar to other materials, aluminum alloys are also exposed to various wear types during operation. Production efficiency needs to be aware of its reactions to wearing mechanisms. Design/methodology/approach: In this study, quartz sands (SiO2) assisted with oxide ceramics were used in the slurry erosion test setup and its abrasiveness on the AlSi10Mg aluminum alloy material produced by the 3D printer as selective laser melting (SLM) technology was investigated. Quartz was sieved with an average particle size of 302.5 µm, and a slurry environment containing 5, 10 and 15% quartz by weight was prepared. The experiments were carried out at the velocity of 1.88 (250 rpm), 3.76 (500 rpm) and 5.64 m/s (750 rpm) and the impact angles 15, 45 and 75°. Findings: With these experimental studies, it has been determined that the abrasiveness of quartz sand prepared in certain particle sizes is directly related to the particle concentration and particle speed, and that the wear increases with the increase of the concentration and rotational speed. Also, the variation of weight loss and surface roughness of the alloy was investigated after different wear conditions. Surface roughness values at 750 rpm speed, 10% concentration and 75° impingement angle are 0.32 and 0.38 µm for 0 and 90° samples, respectively, with a difference of approximately 18%. Moreover, concerning a sample produced at 0°, the weight loss at 250 rpm at 10% concentration and 45° particle impact angle is 32.8 mg, while the weight loss at 500 rpm 44.4 mg, and weight loss at 750 rpm is 104 mg. Besides, the morphological structures of eroded surfaces were examined using the scanning electron microscope to understand the wear mechanisms. Originality/value: The researchers verified that this specific coating condition increases the slurry wear resistance of the mentioned steel. There are many studies about slurry wear tests; however, there is no study in the literature about the quartz sand (SiO2) assisted slurry-erosive wear of AlSi10Mg alloy produced with AM by using SLM technology. This study is needed to fill this gap in the literature and to examine the erosive wear capability of this current material in different environments. The novelty of the study is the use of SiO2 quartz sands assisted by oxide ceramics in different concentrations for the slurry erosion test setup and the investigations on erosive wear resistance of AlSi10Mg alloy manufactured by AM. [ABSTRACT FROM AUTHOR]