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There is a need to replace non-sustainable conventional coolant (emulsion) with eco benign high-performance cutting fluids such as biodegradable nanofluids that exhibit sufficient lubrication and cooling properties. Also, the sustainability performance of titanium-based alloys can be improved with the geometric alteration on the tool rake zone and by the proper cooling-lubrication mechanism. In the present study, the holistic sustainability of external turning of titanium (Ti–6Al–4V) alloy under two different cutting environments (Al–GnP nanoparticle–based minimum quantity lubrication (MQL) with textured carbide tools and conventional emulsion) is investigated. Novel empirical models for cycle time, machining power, embodied and electrical energy consumption carbon emission, and production cost were developed. For both environments, machining experiments were performed until the cutting tool reaches its life. All sustainable indicators were measured and compared with the conventional process. Results showed that textured carbide cutting tools in the presence of Al–GnP nanoparticle–based MQL-assisted machining (hybrid process) are sustainable environmentally and economically. At the very-high (130 m/min) cutting speed, the sustainable hybrid machining process consumed 1.50% less specific cumulative energy (S_CEC), emitted 5.96% less specific CO2, and incurred 4.33% less specific production cost (S_PC) compared with flood-assisted machining. Finally, it is concluded that the presence of hybrid Al–GnP nanofluids in line texture has the potential to act as lubricant/coolant in turning processes.

To achieve an excellent workpiece surface quality and longer tool life in the machining of hardened steel is an excessive challenge. Recently, conventional emulsion cooling assisted machining processes are being used to address this problem. However, such traditional processes have adverse effects on the environment as well as on the machine shop worker’s health. Hence, in this study, the effects of emulsion cooling and sustainable Cryo-LN2 cooling approach on sustainable metrics, such as surface roughness, energy consumption, tool life, and production cost in the external turning of AISI-52100 have been investigated and compared. The comparative results showed that the Cryo-LN2 technique outperformed emulsion cooling for all measured indices. The Cryo-LN2 assisted turning process not only improved surface quality but also consumed 18% less energy consumption and produced 70.9% low-priced products at aggressive cutting parameters as compared to the emulsion. The findings of the current study encourage metal processing industries to use such type of sustainable techniques at a machine shop. This study is based on the “ Think Green, Plan Green and Execute Green” strategy.

Sustainable grinding is one of the development directions of modern processing. When profile grinding titanium alloys, since the grinding burn-out is easy to happen, a large amount of cooling fluid is commonly used for cooling the grinding zone. However, the cooling fluid is harmful to human health and is neither economical nor efficient. Given that, a method of dry profile-grinding Ti–6Al–4V alloy to achieve environmentally-friendly machining was proposed in this article. An axial rotating heat-pipe profile grinding wheel (HPGW) was designed and manufactured, not only to eliminate the harmful cooling fluid; but also to augment heat transfer in the grinding zone and control the grinding temperatures. By developing this HPGW, a sustainable grinding process will be achieved with less resource utilization, less environmental and health issues, less energy consumption, and carbon emission. The design methods of HPGW were put forward through comprehensive consideration of the sonic limit, heat transfer and structural strength requirements. Then, the design was checked by FEM simulation. Moreover, experiments were conducted to investigate the influences of the filling ratio, rotational speed, and material removal rate on the heat transport performance of HPGW. The Ti–6Al–4V alloy profile structure was successfully dry ground by this HPGW. Results reveal that the temperature of the ground surface was controlled below 80 °C and temperature difference on the profile surface was within 10 °C. The novel HPGW with desirable heat transfer performance can be applied in the metal processing industries, and it is a promising candidate for sustainable grinding of titanium alloys.

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.

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.

Sustainable manufacturing philosophy strives for energy-efficient, high quality, and productivity as critical characteristics of a milling process. Hence, an attempt was made to limit the energy consumption, and tool wear in the face milling of hard-to-cut titanium alloy without compromising product quality and productivity. For that, a strong influence of hybrid alumina and multiwalled carbon nanotube (Al2O3-MWCNT) nanoadditive-based minimum quantity lubrication (MQL) was investigated on key machining characteristics. The simultaneous influence of control factors on machining characteristics was evaluated through mathematical modeling and the most straightforward multi-objective optimization. Based on the multi-objective decision approach, the energy consumption of Ec = 829.78 W, surface roughness Ra = 0.549 μm, and material removal rate MRR = 303.9 mm3/min were attained at cutting speed N = 3800 rpm, feed f = 0.012 mm/tooth, depth of cut ap = 0.40 mm, and width of cut ae = 3.6 mm respectively. Despite the trade-off among energy consumption, surface roughness, and material removal rate, the desirability function tried to strike a balanced operating level to achieve less energy consumption, better surface quality, and higher materials removal rate. Additionally, tool wear, chip analysis, and surface topography as key characteristics of the milling process were considered to analyze the wear behavior, chip sliding, and machined surface characteristics under hybrid nanoadditive-based MQL machining. The novelty of this experimental work lies in considering important milling characteristics of hard-to-cut Ti–6Al–4V alloy under hybrid nanofluid-assisted MQL machining. Regarding sustainable green cutting technology, clean cutting of titanium alloy was implemented by nanoadditive-assisted MQL technique.

Poor surface quality and rapid tool wear are the main problems in micro-cutting of Inconel 718. In this study, a novel hybrid machining method named laser-induced oxidation assisted micro-milling is proposed to solve the aforementioned problems. A loose oxide layer and a relatively flat sublayer are formed on the material after laser irradiation. Under optimized laser parameters with a scanning speed of 1 mm/s and an average laser power of 4.5 W, the thicknesses of the oxide layer and the sublayer are 24 and 18 μm, respectively. The influence of cutting parameters on milling force, surface roughness, surface quality, and top burr size is studied in detail. Cutting force and thrust force in the proposed hybrid machining process are lower than those in the conventional micro-milling. Results show that for the investigated range of parameters, the optimal feed per tooth and depth of cut in the hybrid process are 3 μm/z and 3 μm, respectively. When using the optimal parameters, the surface roughness of the machined slot bottom is 108.5 nm. The top burr size on the up-milling side and the down-milling side is 26.8 and 36.2 μm, respectively. In addition, the tool wear mechanism is coating delamination in hybrid process, whereas chipping, coating delamination, tool nose breakage, and adhesion are the main tool wear mechanism in the conventional micro-milling. For the same amount of material removal, the proposed hybrid process can decrease the tool wear and enhance the service life of the micro-end mill as compared to conventional micro-milling.

Machining-induced residual stress plays a significant role in the corrosion resistance and fatigue life of the manufacturing end product. In the current study, milling experiments were performed to investigate the influence of pre-stress on the surface residual stresses. For this purpose, finite element (FE) simulations of the orthogonal cutting based on arbitrary Lagrangian-Eulerian approach were performed. To validate the simulation results, a device was designed to stretch the workpiece with pre-stresses before the machining process. The residual stresses obtained under different pre-stresses were measured based on the varied bending deflection of the workpiece after each material layer removal. As a result, the general variation trend of residual stress profiles that obtained under different pre-stresses was found well consistent with the finite element simulation results, indicating that the proposed residual stress measuring principle is reliable. Furthermore, the pre-stress loaded on the Ti6Al4V part can significantly affect the distribution of machining-induced residual stresses, implying that surface residual stresses can be adjusted by employing appropriate values of pre-stresses during the machining process.

The surface modification is a pivotal step in the field of the biomedical implant in order to improve its biomedical characteristics. A number of methods can be adopted to improve surface characteristics like coating, evaporation, sputtering, and ion implantation. The surface of any material can also be improved by machining. In the present work, an electric discharge drilling (EDD) was used for the development of quality holes on any conductive material regardless of its hardness. In the present research, commercially pure titanium (CPTi) was drilled for the development of microhole using the EDD. The effect of microholes on the apatite formation and weight gain was determined. The apatite formation was measured in the presence of simulated body fluid (SBF) after 7, 14, and 21 days of immersion. The temperature and pH during the apatite formation were 37 °C and 7.4, respectively. It was found that after the development of microholes, the quantity of apatite formation increases. On the contrary side on the normal CPTi material (without drilling), an insignificant apatite formation was observed. However, after drilling, the elements of calcium and phosphate were observed ever after 4 days of immersion in SBF. The surface area of the apatite formation increases by 24% after the development of microholes. Scanning electron microscopy (SEM) revealed the microstructure of the drilled surface before and after the immersion of CPTi in SBF. In addition, it was observed that with the increase in the number of holes and immersion period, the apatite formation increases.

Recently, hybrid lubricooling is considered as the emerging sustainable cooling technique and is in a rudimentary stage. The application of hybrid CryoMQL (Cryogenic+MQL) method is getting repute in the industrial sectors due to its benefits, such as less resource consumption and improved productivity. In the past, machining efficiency in term of the trade-off of productivity and energy efficiency has not been explored in-depth for hybrid Lubricooling assisted sustainable machining process. Therefore, in this study, turning experiments were performed to analyze the productivity and machining efficiency in sustainable machining of Ti-6Al-4V alloy. All experiments were performed in different cooling techniques, and comparative results were obtained. Cutting time was fixed for each environment during a particular set of experiments and cutting speed was kept relatively higher in hybrid CryoMQL (HCM) method. Results showed that the HCM method performed best as compared to dry and MQL method. Longer tool life, higher productivity, lower energy consumption can be obtained using the proposed method. The study preaches “Think Green, Plan Green, and Go Green” and the proposed technology can be implemented in the metal processing industry to get high productivity and save cost.

During the machining of α+β intermetallic stable titanium alloy, their poor thermal conductivity and resistance at elevated temperature accumulates most of the shearing and friction heat. The resulting heat damage the cutting tool, causes in high power consumption, shorter tool life and poor surface quality. Therefore, it is important to choose a latest cooling technique with excellent capacity to remove heat, chips and frictional effects from the cutting zone. Therefore, Carbon dioxide snow (CO2-snow) and hybrid copper oxide (CuO)-multi-walled carbon nanotubes (MWCNTs) nanofluids based minimum quantity lubrication (MQL) are compared to achieve clean cooling/lubrication technique to machine biomedical/aerospace material Ti-6Al-4V. Taguchi L9 orthogonal array was applied to design the experiments. Critical machining parameters are cutting speed (m/min), feed (mm/rev), and cooling mode. The output responses are surface quality Ra (μm), cutting power Pc (W), cutting temperature T (oC), and tool life TL (min) were evaluated under CO2-snow and MQL-hybrid nanofluids. Findings have revealed less surface roughness and longer tool life under hybrid nanofluids. While CO2-snow has justified less temperature and power consumption at high cutting conditions.

In bone fixation, frictional heat effect in orthopedic surgery has a potentially hazardous for soft tissues. Saline water irrigation has frequently been practiced preventing the thermal damage and limiting the applied cutting forces in high-speed orthopedic drilling. The application of excessive cutting fluids limits the heat and applied forces; however, it isn’t an environmentally friendly solution. In this work, a novel micro-irrigation system was developed to provide a mixture of air and saline water, having a small quantity of cooling spray (SQCS) at higher pressure into the cutting zone. This SQCS limits the frictional heat and providing lubrication and near to dry clean operative zone through a superior cooling effect compared to conventional irrigation. The carbide drills were used to make a hole in the fresh calf tibia bone. In addition, response surface methodology (RSM) was used to design the experiments. The regression models were developed between the input design parameters and performance measures to explore the relation under proposed micro-irrigation and facilitate the multi-objective optimization. Besides, cost analysis for the process has been performed. Thus, this work offers an integrated analysis to purely study and understand the bone drilling process under employing micro-cooling spray.

Distribution of temperature during the welding process is essential for predicting and realizing some important welding features such as microstructure of the welds, heat-affected zone (HAZ), residual stresses, and their effects. In this paper, a numerical model was developed using COMSOL Multiphysics of dissimilar laser welding (butt joint) of AISI 316L and Ti6Al4V thin sheet of 2.5 mm thickness. A continuous mode (CW) fiber laser heat source of 300 W laser power was used for the present study. A time-dependent prediction of temperature distributions was attempted. The heat source was assumed as a Hermit–Gaussian analytical function with a moving velocity of 120 mm/min. Both convective and radiant heat loss and phase change of the materials were considered for the analysis. In addition, variation of temperature-dependent material properties was also considered. The maximum and minimum temperature for the two materials at different times and the temperature in the different penetration depths were also predicted. It was found that the average temperature that can be achieved in the bottom-most surface near the weld line was more than 2400 K, which justifies the penetration. Averages of maximum temperatures on the weld line at different times at the laser spot irradiation were identified near 3000 K.The temperature fluctuation near the weld line was minimal and decreased more in the traverse direction. Scanning with a displaced laser relative to the interface toward the Ti6Al4V side reduces the maximum temperature at the interface and the HAZ of the 316L side. All of these predictions agree well with the experimental results reported in current literature studies.

Titanium, a difficult-to-cut material, consumes higher time and cost in removing material by machining to produce parts. Machining of Ti alloys has got serious attention owing to its reacti...

The cutting fluid is significant in any metal cutting operation, for cooling the cutting tool and the surface of the workpiece, by lubricating the tool-workpiece interface and removing chips from the cutting zone. Recently, many researchers have been focusing on minimum quantity lubrication (MQL) among the numerous methods existing on the application of the coolant as it reduces the usage of coolant by spurting a mixture of compressed air and cutting fluid in an improved way instead of flood cooling. The MQL method has been demonstrated to be appropriate as it fulfills the necessities of ‘green’ machining. In the current study, firstly, various lubrication methods were introduced which are used in machining processes, and then, basic machining processes used in manufacturing industries such as grinding, milling, turning, and drilling have been discussed. The comprehensive review of various nanofluids (NFs) used as lubricants by different researchers for machining process is presented. Furthermore, some cases of utilizing NFs in machining operations have been reported briefly in a table. Based on the studies, it can be concluded that utilizing NFs as coolant and lubricant lead to lower tool temperature, tool wear, higher surface quality, and less environmental dangers. However, the high cost of nanoparticles, need for devices, clustering, and sediment are still challenges for the NF applications in metalworking operations. At last, the article identifies the opportunities for using NFs as lubricants in the future. It should be stated that this work offers a clear guideline for utilizing MQL and MQL-nanofluid approaches in machining processes. This guideline shows the physical, tribological, and heat transfer mechanisms associated with employing such cooling/lubrication approaches and their effects on different machining quality characteristics such as tool wear, surface integrity, and cutting forces.

In this present research, a cryogenic machining system with adjustable jet temperature (− 196~20 °C) has been developed, and then a series of cutting experiments have been conducted to investigate the surface integrity of 35CrMnSiA high-strength steel under dry machining and cryogenic machining. The influences of cutting speed, jet temperature, and cooling condition on cutting force, surface roughness, microhardness, microstructure, and residual stress have been investigated. Experimental results are evaluated by means of a surface roughness tester, digital microhardness tester, digital microscope, and X-ray diffractometer. The experimental results reveal that the jet temperature, cooling condition, and cutting speed have a remarkable influence on the cutting force and surface integrity of 35CrMnSiA high-strength steel. At the same cutting speed, a reduction in jet temperature results in an increase in cutting force and decrease in microhardness. The lower jet temperature, the smaller the surface roughness. Compared with dry machining, the tensile residual stress can be effectively reduced under the condition of cryogenic machining. At the same jet temperature, as the cutting speed increases, the cutting force increases firstly and then decreases. In contrast, the surface roughness decreases firstly and then increases. With the increase of cutting speed, under the same cooling condition, the microhardness and residual stress shows a decreasing and increasing trend, respectively. This research contributes to providing a guide to optimize the machining process and improve machined surface integrity.

Purpose Sustainable machining is a global consensus and the necessity to cope up the serious environmental threats. Minimum quantity lubrication (MQL) and nanofluids-based MQL(NFMQL) are state-of-the-art sustainable lubrication modes. The purpose of this study is to investigate the effect of process parameters, such as feed rate, depth of cut and cutting fluid flow rate, on temperature and surface roughness of the manufactured pieces during face milling of the AISI D2 steel. Design/methodology/approach A statistical technique called response surface methodology with Box–Behnken Design was used to design experimental runs, and empirical modeling was presented. Analysis of variance was carried out to evaluate the model’s accuracy and the validation of the applied technique. Findings A comprehensive analysis revealed the superiority of implementing NFMQL in comparison to MQL within the levels of process parameters. The comparison has shown a significant reduction of temperature under NFMQL at the tool-workpiece interface from 16.2 to 34.5 per cent and surface roughness from 11.3 to 12 per cent. Practical implications This research is useful for practitioners to predict the responses in workshop and select appropriate cutting parameters. Moreover, this research will be helpful to reduce the resource which will ultimately save energy consumption and cost. Originality/value To cope with the industrial challenges and tribological issues associated with the milling of AISI D2 steel, experiments were conducted in a distinct machining mode with innovative cooling/lubrication. Until now, few studies have addressed the key lubrication effects of Al2O3-based nanofluid on the machinability of D2 steel under NFMQL lubrication condition.

Owing to superior physio-chemical characteristics, titanium alloys are widely adopted in numerous fields such as medical, aerospace, and military applications. However, titanium alloys have poor machinability due to its low thermal conductivity which results in high temperature during machining. Numerous lubrication and cooling techniques have already been employed to reduce the harmful environmental footprints and temperature elevation and to improve the machining of titanium alloys. In this current work, an attempt has been made to evaluate the effectiveness of two cooling and lubrication techniques namely cryogenic cooling and hybrid nanoadditive–based minimum quantity lubrication (MQL). The key objective of this experimental research is to compare the influence of cryogenic CO2 and hybrid nanofluid–based MQL techniques for turning Ti–6Al–4V. The used hybrid nanofluid is alumina (Al2O3) with multi-walled carbon nanotubes (MWCNTs) dispersed in vegetable oil. Taguchi-based L9 orthogonal-array was used for the design of the experiment. The design variables were cutting speed, feed rate, and cooling technique. Results showed that the hybrid nanoadditives reduced the average surface roughness by 8.72%, cutting force by 11.8%, and increased the tool life by 23% in comparison with the cryogenic cooling. Nevertheless, the cryogenic technique showed a reduction of 11.2% in cutting temperature compared to the MQL-hybrid nanofluids at low and high levels of cutting speed and feed rate. In this regard, a milestone has been achieved by implementing two different sustainable cooling/lubrication techniques.

Air-leakage detection is among the most important processes at the assembly stage of unclosed components, especially for large aircraft. A series of air-leakage detecting methods are generally applied during the final assembly, nevertheless, many of them are less effective to detect the leakage at the assembly stage. The present study aims to discuss the principles of ultrasonic generation in negative pressure conditions to detect the air-leakage. An ultrasonic-based detection method is proposed and designed to detect the air-leakage of unclosed components for aircraft. A relationship between the acoustic power, sound pressure, and the leak aperture detection distance was identified and discussed. A leakage rate model related to leakage rate, leak aperture, and system pressure was implemented and confirmed through experiments. Findings have indicated that the air-leakage can be detected effectively within a detection distance of 0.8 m and a leak aperture greater or equal to 0.4 mm with this method. Besides, the leak location, leak aperture, and leakage rate was acquired in an accurate and fast way. It is an effective method of detecting the air-leakage of unclosed components at the aircraft assembly stage reducing the testing time, energy consumption, and cost for the air-leakage detection in the final assembly stage of large aircraft.

Design and manufacturing are the key steps in the sustainable manufacturing of any product to be produced. Within the perspective of injection molds production, increased competitiveness and repeated changes in the design require a complete optimized manufacturing process. Local and minor improvements in the milling process do not generally lead to an optimized manufacturing process. The goal of the new geometry and parametric analysis of the mould is to reduce the quality issues in mild steel grade 60. In this explicit research, the surface roughness (smoothness) of indigenously produced injection moulds in the local market in Pakistan is investigated. The CNC milling machine (five-axis) is used for the manufacturing of an injection mould, and the Taguchi method of the design of the experiment is applied for parameters optimization. Hence, the overall process is assisted in balancing the milling machine parameters to trim down the surface roughness issue in mild steel moulds and increase their sustainability. The spindle speed (rpm), the depth of cut (mm), and the feed rate (mm/rev) are considered as input variables for process optimization, and the experiments are performed on mild steel grade 60. It is deduced that the combination of a spindle speed of 800 rpm, feed rate of 10 mm/rev and depth of cut of 0.5 mm is the best case in case of minimum surface roughness, which leads to sustainable products. It is also deduced from ANOVA, that the spindle speed is a factor that affects the surface roughness of mild steel products, while the feed rate turns out to be insignificant.

Carbon dioxide (CO2) laser cutting finds one of its most relevant applications in the processing of a wide variety of polymeric materials like thermoplastics and thermosetting plastics. Different types of polymeric materials like polypropylene (PP), polymethyl methacrylate (PMMA), low- and high-density polyethylene (LDPE, HDPE), are processed by laser for different household as well as commercial products in the industry. The reason is their easy availability and economical aspect in the market. The problems associated with laser cutting include heat-affected zone (HAZ) generated on the cut surface, kerf width (KW), surface roughness (SR), dross formation, and striations formation. Furthermore, other related problems include taper cutting for deep parts and high-power consumption. The primary purpose of this work is a comprehensive literature review in CO2 laser cutting of polymeric materials. The influence of parametric variation on the cut quality is also explained. Cut quality in terms of KW, SR, HAZ, dross formation, and striations formation is analyzed by optimizing cutting variables like laser power (PL), cutting speed (CS), assist gas pressure (Pg), pulse frequency, nozzle type and its diameter, and stand-off distance (SOD). The effects of the laser cutting on the properties of different thermoplastics/thermosetting materials are also reported. However, this topic requires further studies on exploring the range of polymeric materials, and their optimal parameters selection to improve the cut quality. Therefore, the research gaps and future research directions are also highlighted in the context of CO2 laser cutting for polymeric materials.

Recently, the urgency of improved machining performance and environmental sustainability has forced the manufacturer to seek for alternative cooling and lubricating agent/technique such as nano-fluid (NF)-assisted minimum quantity lubrication (MQL). In this context, the performances of aluminum oxide (Al2O3), molybdenum disulfide (MoS2) and graphite (C) NF-impinged MQL in turning of Ti alloy (grade II) using CBN tool were evaluated regarding the cutting force, cutting temperature and surface roughness. The cutting speed, feed rate, approaching angle and cutting conditions (i.e., NFs) were oriented following the Box–Behnken design-of-experiment. The experimental results showed that the graphite NF, compared to Al2O3 and MoS2, revealed the lowest cutting force, temperature and roughness. Moreover, it is evident from SEM images that graphite NF revealed a smoother machined surface and tool profile. This smooth tool and workpiece surface profile can be accredited to graphite’s role as a nano-lubricant and its breaking ability into smaller NFs under pressure. To make the study complete, the adaptive neuro-fuzzy inference system (ANFIS) was employed to predict, the response surface methodology (RSM) was used to mathematically model, and the composite desirability approach (CDA) was used to optimize the responses. A good agreement between the experimental and modeled observations was found; however, the ANFIS outperformed the RSM. Moreover, the analysis of variance exhibited that the cutting force and temperature were primarily influenced by the cutting speed and the surface roughness was afflicted mostly by the feed.

Bone drilling is a well-known internal fixation procedure to drill a hole, fixing the bone fragments to reduce the susceptibility of permanent paralysis. The success of bone drilling is evaluated based on the extent of osteonecrosis in terms of heat generation, tissue damage, quality of hole, and drilling forces. The appropriate control of cutting conditions, drill geometric parameters, and bone-specific parameters offer bone drilling a viable solution through conventional and non-conventional drilling techniques. The majority of the published research work considers only limited parameters and tries to optimize the drilling parameters and performance measures. However, bone drilling involves numerous conventional and non-conventional drilling parameters and technologies. In order to develop a better understanding of all the studied parameters and performance measures, there is a dire need to develop a framework. The key objective of this review study is to establish a hierarchy of the framework by collecting almost all the parameters studied until now and addressed the relationship between parameters and performance measures to diminish the controversies in the published literature. Therefore, this framework is novel in nature, organizing all the parameters, performance measures, logical comparisons, and limitations of studies. This holistic review can help medical surgeons and design engineers to understand the complicated relationship among parameters and performance measures associated with this state-of-art technologies. Also, modeling, simulations, and optimization techniques are included to explore the application of such techniques in recent advancements in orthopedic drilling.

This paper develops a new technology to improve the anti-friction performance of cutting tools by constructing textured surface with composite lyophilic/lyophobic wettabilities and this method is applied to polycrystalline diamond (PCD) tools. Lyophobic micro/nano structures and lyophilic grooves were successively fabricated on the tool surface by a pulsed fiber laser using different processing parameters. Then the influence of un-textured PCD tools, microgrooved tools and textured tools with lyophilic/lyophobic wettabilities on cutting performance and tool wear were investigated during turning of Ti6Al4V titanium alloy bar under minimum quantity lubrication (MQL) environment. The results indicated that textured PCD tools with lyophilic/lyophobic wettabilities reduced the cutting force, average friction coefficient and cutting tool wear in comparison of un-textured tools and microgrooved tools. Furthermore, the anti-friction mechanism of textured tools with lyophilic/lyophobic wettabilities was discussed from the aspects of drag reduction and the regulation of movement of cutting liquid to the impact tool-chip interface. This new technology provides a new way for textured tools to further enhance cutting performance and mitigate tool wear.

The present work discusses the fabrication of low-cost, reliable and durable flexible electronic circuits from conductive carbon paste on flexible polyethylene terephthalate (PET) substrate using microdispensing direct ink write technique. Printing parameters such as pressure, substrate speed and gap size are optimized through Box–Behnken experimental design technique to achieve the desired quality of prints (patterns). For the nozzle with an inner diameter of 200 µm, the system is able to produce pattern line width ranging from 198 µm to 295 µm, respectively. Based on optimized parameters, circuits such as foil grid and rectangular spiral are printed on a flexible PET substrate. The deposited patterns of circuits are morphologically characterized by optical microscopy and scanning electronic microscopy. Current–Voltage (I–V) characteristic is performed to evaluate the conductive performance of circuits. The sensitivity of circuits to bending is assessed by studying resistance response under fully bend and unbend angle of 90° and 0°. Durability and reliability of circuits are analyzed by subjecting circuits to continuous 500 bend cycles and study its resistance response. The analysis revealed that these direct ink write circuits are reliable, durable and stable in performance and are applicable to the flexible electronic application.

This paper first develops a cryogenic cutting system with adjustable jet temperature (− 196~20 °C), and then carries out a series of dry cutting and cryogenic turning experiments for titanium alloy. Metallographic microscope is used to observe the chip morphology of titanium alloy and the geometric characteristic parameters of the chip are measured using a Digimizer image measurement software. The influence of cutting speed and cooling conditions on the chip morphology, chip height ratio, and serrated pitch has been analyzed. The experimental results reveal that the cutting speed and cooling conditions play significant roles on the chip morphology and serrated characteristics of titanium alloy. During the cryogenic cutting process, with the increase of cutting speed, the chip height ratio and serrated pitch of titanium alloy chip increase. It has been found that under the condition of cryogenic cutting, the lower jet temperature, the more obvious serrated characteristic of titanium alloy chip. It is also found that the fibrous adiabatic shear band exists in the shear zone; the chip height ratio and serrated pitch remarkably increase.

This study aims to investigate the effects of process parameters feed, depth of cut and flow rate, on the temperature during face milling of the D2 tool steel under two different lubricant conditions, Minimum Quantity Lubrication (MQL) and Nanofluid Minimum Quantity Lubrication (NFMQL). Distilled water with the flow rate range 200-400 ml/hr was used in MQL. 2% by weight concentration of Al2O3 nanoparticles with distilled water as the base fluid used as NFMQL with same flow rate. Response surface methodology RSM central composite design CCD was used to design experiment run, modeling, and analysis. ANOVA was used for the adequacy and validation of the system. The comparison shows that NFMQL condition reduced more temperature during machining.

To study the surface residual stresses generated by machining Ti6Al4V alloy, we conducted some finite element simulations of the orthogonal cutting process using different cutting parameters. The simulation was based on the Arbitrary Lagrangian–Eulerian finite element approach. It shows that the tool geometry and the cutting parameters can affect the machining-induced surface residual stresses significantly in orthogonal cutting. To study the influences of the tool corner radius and tool feed per revolution on the surface residual stresses induced by a three-dimensional cutting process (which are always neglected in orthogonal cutting models), a plane strain condition-based indentation model was used to evaluate the corresponding effects. Based on the combination of the orthogonal cutting model and the orthogonal indentation model, the surface residual stresses generated in the three-dimensional cutting process could be modeled with much higher efficiency than with three-dimensional modeling. We conducted some corresponding experiments to validate the predicted results obtained from the model proposed in this paper and found that the results obtained from the two different methods were in satisfactory quantitative agreement.

Integrated vibration in electrical discharge machining (EDM) plays a key role in achieving high efficiency. High levels of variables can be employed in this approach due to integration. However, simultaneous optimization of the EDM parameters to achieve multi-objectives is still very complex and challenging. Studies on integrated vibration are still in a preliminary stage. This report addresses multi-objective optimization in EDM for SKD61 die steel using low-frequency vibration. MOORA (Multi-objective optimization based on ratio analysis) was chosen to resolve this multi-objective optimization problem. The material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) were selected as performance measures in the EDM process. An analytical hierarchical process (AHP) was used to determine the weight value of the quality indicators. The results indicate that low-frequency vibrations significantly improve machining efficiency. When the frequency of the vibrations increased, MRR increased significantly such that MRRMAX = 64.48%. TWR and SR are smaller and their increase are given as TWRMAX = 20.3% and SRMAX = 18.47%. MOORA has been identified as a suitable alternative to multi-objective optimization in an EDM process using low-frequency vibrations for an assigned workpiece. The optimum parameters required to achieve the multi-objective were Ton = 25 μs, I = 8 A, Tof = 5.5 μs and F = 512 Hz, at the resultant quality criteria of MRR = 9.564 mm3/min, TWR = 1.944 mm3/min and SR = 3.24 µm with a maximum error of 8.24%.

Recently, the application of nano-cutting fluids has gained much attention in the machining of nickel-based super alloys due their good lubricating/cooling properties including thermal conductivity, viscosity, and tribological characteristics. In this study, a set of turning experiments on new nickel-based alloy i.e., Inconel-800 alloy, was performed to explore the characteristics of different nano-cutting fluids (aluminum oxide (Al2O3), molybdenum disulfide (MoS2), and graphite) under minimum quantity lubrication (MQL) conditions. The performance of each nano-cutting fluid was deliberated in terms of machining characteristics such as surface roughness, cutting forces, and tool wear. Further, the data generated through experiments were statistically examined through Box Cox transformation, normal probability plots, and analysis of variance (ANOVA) tests. Then, an in-depth analysis of each process parameter was conducted through line plots and the results were compared with the existing literature. In the end, the composite desirability approach (CDA) was successfully implemented to determine the ideal machining parameters under different nano-cutting cooling conditions. The results demonstrate that the MoS2 and graphite-based nanofluids give promising results at high cutting speed values, but the overall performance of graphite-based nanofluids is better in terms of good lubrication and cooling properties. It is worth mentioning that the presence of small quantities of graphite in vegetable oil significantly improves the machining characteristics of Inconel-800 alloy as compared with the two other nanofluids.

Achievement of low temperature, thrust force, and clean operating zone under with/without irrigation–assisted drilling is still a challenge in orthopedic surgery owing to substantial bone-tissue damage that extends the healing time. In order to mitigate the above challenges, a new micro-lubrication technique—a low-pressure cold mist impinged on the tool–bone joint interface and penetrating well into the bone surface to improve the cooling/lubrication efficiency—has been proposed in bone drilling. In this study, the aims are to characterize the effect of micro-cooling/lubrication on temperature and thrust force at different levels of cutting speed, feed rate, drill diameter, and coolant flow rate. For that purpose, a fresh calf bone was drilled through commercially available drill tool on three-axis mini-machine. The response surface methodology was applied to get the design of experiments, and the analysis of variance at p-values

Environmental protection is the major concern of any form of manufacturing industry today. As focus has shifted towards sustainable cooling strategies, minimum quantity lubrication (MQL) has proven its usefulness. The current survey intends to make the MQL strategy more effective while improving its performance. A Ranque–Hilsch vortex tube (RHVT) was implemented into the MQL process in order to enhance the performance of the manufacturing process. The RHVT is a device that allows for separating the hot and cold air within the compressed air flows that come tangentially into the vortex chamber through the inlet nozzles. Turning tests with a unique combination of cooling technique were performed on titanium (Grade 2), where the effectiveness of the RHVT was evaluated. The surface quality measurements, forces values, and tool wear were carefully investigated. A combination of analysis of variance (ANOVA) and evolutionary techniques (particle swarm optimization (PSO), bacteria foraging optimization (BFO), and teaching learning-based optimization (TLBO)) was brought into use in order to analyze the influence of the process parameters. In the end, an appropriate correlation between PSO, BFO, and TLBO was investigated. It was shown that RHVT improved the results by nearly 15% for all of the responses, while the TLBO technique was found to be the best optimization technique, with an average time of 1.09 s and a success rate of 90%.

It is hypothesized that the orientation of tool maneuvering in the milling process defines the quality of machining. In that respect, here, the influence of different path strategies of the tool in face milling is investigated, and subsequently, the best strategy is identified following systematic optimization. The surface roughness, material removal rate and cutting time are considered as key responses, whereas the cutting speed, feed rate and depth of cut were considered as inputs (quantitative factors) beside the tool path strategy (qualitative factor) for the material Al 2024 with a torus end mill. The experimental plan, i.e., 27 runs were determined by using the Taguchi design approach. In addition, the analysis of variance is conducted to statistically identify the effects of parameters. The optimal values of process parameters have been evaluated based on Taguchi-grey relational analysis, and the reliability of this analysis has been verified with the confirmation test. It was found that the tool path strategy has a significant influence on the end outcomes of face milling. As such, the surface topography respective to different cutter path strategies and the optimal cutting strategy is discussed in detail.

Modeling and simulation using finite element method (FEM) is a powerful estimation tool and has been greatly helpful to study the metal cutting process, such as investigation of cutting mechanism, optimization of cutting parameters, and design of cutting tools. Thereinto, an effective material model and its parameters are still key problems in the FEM-modeling of metal cutting. In this paper, a 2D FE model for simulating the orthogonal cutting of tungsten carbide WC-17.5Co is developed, in which an inverse identification approach is used to identify the parameters of material model based on orthogonal cutting experiments. The commercially available software DEFORM V11.0 is utilized to develop the FE model, whereas the Johnson–Cook model and Brozzo model are selected as the constitutive model and the fracture model of the work material, respectively. Continuous serrated chip formation is obtained in experiments as well as in FE simulations. The simulated chip morphology, cutting force, and specific cutting force are compared with the experimental results to identify the parameters of the material model. It is found that the chip morphology is more difficult to be used to identify inversely the material model parameters than the cutting force and specific cutting force. The material model parameters are derived, and the verification tests show that there is a close agreement between the simulated and experimental results through comparisons of cutting force and specific cutting force. It indicates that the inversely identified parameters of the Johnson–Cook model and the Brozzo model can be used to describe the mechanical property of tungsten carbide.

In the 40th volume of the Journal of the Brazilian Society of Mechanical Sciences and Engineering, a paper entitled “Investigation of drilling parameters on hybrid polymer composites using grey relational analysis, regression, fuzzy logic, and ANN models” was published. The current study identifies a discrepancy between the grey relational analysis (GRA)’s formula used in that paper. The study identifies the incorrect definition of GRA to be the source of the discrepancy.

The quest for advanced cooling/lubrication approaches for energy-efficient, eco-benign, and cost-effective sustainable machining processes is garnering attention in academia and industry. Electrical and embodied energy consumption plays an important role in reducing CO2 emissions. In the present study, new empirical models are proposed to assess sustainable indicators. The embodied energy, environmental burden, and cost of coolant/lubricant have been added in the proposed models. Initially, optimal levels of minimum quantity lubrication (MQL) oil flow rate, liquid LN2 flow rate, air pressure, and nanoparticle concentration were found. Based on optimal technological parameters, experiments were performed under the same cutting conditions (machining parameters) for MQL and cryogenic LN2-assisted external turning of Ti6-Al-4V titanium alloy. The electric power and energy consumption, production time/cost, and CO2 emissions were assessed for a unit cutting-tool life. Later, specific responses were measured and compared between both cooling and lubrication approaches. Results showed that hybrid Al-GnP nanofluid consumed 80.6% less specific cumulative energy and emitted 88.7% less total CO2 emissions. However, cryogenic LN2 extended tool life by nearly 70% and incurred 4.12% less specific costs with 11.1% better surface quality. In summary, after Energy&ndash, Economy&ndash, Ecology&ndash, Engineering technology (4E)-based analysis, cryogenic LN2 is sustainable economically but not environmentally and there is a need to improve the sustainable production of LN2 at an industrial scale to achieve environmental sustainability. The present study provides useful information to establish clean machining processes.

Sustainability assessments of cooling/lubrication-assisted advanced machining processes has been demanded by environment control agencies because it is an effective management tool for improving process sustainability. To achieve an effective and efficient sustainability evolution of machining processes, there is a need to develop a new method that can incorporate qualitative indicators to create a quantifiable value. In the present research work, a novel quantifiable sustainability value assessment method was proposed to provide performance quantification of the existing sustainability assessment methods. The proposed method consists of three steps: establishing sustainable guidelines and identifying new indicators, data acquisition, and developing an algorithm, which creates the Overall Performance Assessment Indicator (OPAI) from the sustainability assessment method. In the proposed algorithm, initially, both quantitative and qualitative sustainability indicators are normalized. After weight assignment and aggregation, the OPAI is obtained. The developed algorithm was validated from three literature case studies, and optimal cutting parameters were obtained. The present methodology provides effective guidelines for a machinist to enhance process performance and achieve process optimization. The study also offers a relationship between sustainable and machining metrics for the support of industrial sustainability.

Considering the significance of improving the energy efficiency, surface quality and material removal quantity of machining processes, the present study is conducted in the form of an experimental investigation and a multi-objective optimization. The experiments were conducted by face milling AISI 1045 steel on a Computer Numerical Controlled (CNC) milling machine using a carbide cutting tool. The Cu-nano-fluid, dispersed in distilled water, was impinged in small quantity cooling lubrication (SQCL) spray applied to the cutting zone. The data of surface roughness and active cutting energy were measured while the material removal rate was calculated. A multi-objective optimization was performed by the integration of the Taguchi method, Grey Relational Analysis (GRA), and the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The optimum results calculated were a cutting speed of 1200 rev/min, a feed rate of 320 mm/min, a depth of cut of 0.5 mm, and a width of cut of 15 mm. It was also endowed with a 20.7% reduction in energy consumption. Furthermore, the use of SQCL promoted sustainable manufacturing. The novelty of the work is in reducing energy consumption under nano fluid assisted machining while paying adequate attention to material removal quantity and the product’s surface quality.

The emerging grave consequences of conventional coolants on health, ecology and product quality, have pushed the scientific research to explore eco-friendly lubrication technique. Electrostatic minimum quantity lubrication (EMQL) has been underscored as a burgeoning technology to cut-down bete noire impacts in machining. This research confers the adoption of a negatively charged cold mist of air-castor oil employed in turning of aluminium-6061T6 material by varying the cutting conditions, as per experimental designed through response surface methodology (RSM). For comprehensive sagacity, a range of cutting speed, feed, depth of cut and EMQL-flow rate were considered. Material removal rate, tool life, surface roughness and power consumption of machine tool were adopted as performance measures. To satisfy multi-criterion simultaneously, RSM-based grey relational analysis (GRA) was employed for multi-objective optimisation. Highest proportion of grey relational grade (GRG) as a single desideratum response function, provided a trade-off between performance measures with 15.56% improvement in GRG.

In the present study, the machinability indices of surface grinding of AISI D2 steel under dry, flood cooling, and minimum quantity lubrication (MQL) conditions are compared. The comparison was confined within three responses, namely, the surface quality, surface temperature, and normal force. For deeper insight, the surface topography of MQL-assisted ground surface was analyzed too. Furthermore, the statistical analysis of variance (ANOVA) was employed to extract the major influencing factors on the above-mentioned responses. Apart from this, the multi-objective optimization by Grey–Taguchi method was performed to suggest the best parameter settings for system-wide optimal performance. The central composite experimental design plan was adopted to orient the inputs wherein the inclusion of MQL flow rate as an input adds addition novelty to this study. The mathematical models were formulated using Response Surface Methodology (RSM). It was found that the developed models are statistically significant, with optimum conditions of depth of cut of 15 µm, table speed of 3 m/min, cutting speed 25 m/min, and MQL flow rate 250 mL/h. It was also found that MQL outperformed the dry as well as wet condition in surface grinding due to its effective penetration ability and improved heat dissipation property.