PurposeThis study aims to investigate the effects of adding a minimal amount (0.5 Wt.%) of hexagonal boron nitride (hBN) nanoparticles to polylactic acid (PLA) and evaluate how two different dispersion methods, namely, dry mixing and ethanol-assisted physical blending, influence the mechanical, thermal, morphological and tribological properties of the resulting nanocomposites.Design/methodology/approachPLA/hBN nanocomposites were prepared via two physical mixing routes, extruded into filaments and three-dimensional printed using fused deposition modeling. Mechanical properties were assessed through tensile, Charpy impact and hardness tests. Tribological performance was evaluated via pin-on-disk friction tests. Thermal stability and chemical interactions were analyzed using thermogravimetric analysis, differential thermal analysis and Fourier-transform infrared spectroscopy (FTIR). Morphology and dimensional accuracy were examined using scanning electron microscopy and precision dimensional measurements.FindingsThe incorporation of only 0.5 Wt.% hBN significantly improved key properties of PLA. Tensile strength increased by up to 19.2% with dry mixing and 9.3% with ethanol-assisted mixing. Impact resistance showed remarkable enhancement, rising approximately fourfold for dry-mixed and 4.5-fold for ethanol-mixed composites. The coefficient of friction decreased by 33.8% and 35.3% for dry- and ethanol-mixed specimens, respectively. Thermal stability was maintained, and FTIR confirmed successful hBN integration with indications of interfacial interactions. Ethanol-assisted mixing promoted more homogeneous nanoparticle dispersion, leading to superior impact performance and more stable frictional behavior.Practical implicationsThis work demonstrates that ultralow loadings of hBN can meaningfully enhance PLA's performance, offering a viable and sustainable route to produce high-performance, biodegradable composites suitable for demanding applications in sectors such as aerospace, automotive and precision engineering, where a balance of strength, toughness and tribological performance is required.Originality/valueWhile hBN reinforcement of polymers has been studied, research on ultralow filler concentrations (=0.5 Wt.%) and the direct comparison of simple, scalable dry- versus solvent-assisted physical mixing methods for PLA/hBN composites has been limited. This study provides new insights into how minimal filler content and dispersion methodology critically affect the multifunctional properties of biodegradable nanocomposites, presenting a practical framework for developing high-performance sustainable materials with minimal environmental and processing burden.

Selective laser melted (SLM) Ti-6Al-4V components are widely used in aerospace, biomedical and defense applications, but their as-built parts inherently exhibit poor surface quality, high residual stresses and a heterogeneous, martensitic alpha '-dominated microstructure that complicates secondary machining. The present study investigates a hybrid eco-friendly cooling/lubrication strategy in which hexagonal boron nitride (hBN) and zinc oxide (ZnO) nanofluids prepared at 0.6 vol% in a biodegradable vegetable-based synthetic oil are coupled with Ranque-Hilsch vortex-tube (VT) cooling during the milling of SLM Ti-6Al-4V. Eight machining environments were compared: dry, MQL, VT, MQL + VT, hBN-MQL, ZnO-MQL, hBN-MQL + VT and ZnO-MQL + VT, at constant cutting parameters (vc = 90 m/min, f = 0.1 mm/rev, ap = 0.8 mm, ae = 12 mm). The nanofluids were characterized in terms of pH, dynamic viscosity and thermal conductivity, and machining performance was assessed through cutting temperature (Tc), average surface roughness (Ra), flank wear progression (VB), power consumption (P), coefficient of friction (CoF) and specific wear rate. Tool wear mechanisms were further elucidated through SEM imaging and EDX point analysis. Compared with the dry baseline (Tc ti 474 degrees C, Ra ti0.326 mu m, VB ti 542 mu m, P ti 490 W, CoF ti 0.539), the ZnO-MQL + VT hybrid produced the largest improvements: Tc, Ra, VB, P and CoF were reduced by 24.7%, 44.5%, 53.1%, 39.4% and 52.3%, respectively, while the specific wear rate decreased by 31.0%. SEM/EDX analysis confirmed that adhesion, diffusion and built-up edge (BUE)/built-up layer (BUL) formation, accompanied by coating delamination, were the dominant wear modes in dry and partially cooled conditions, whereas these mechanisms were strongly suppressed under hybrid nanofluid + VT environments. The findings provide a coherent thermo-tribological framework for designing sustainable hybrid cooling/lubrication strategies tailored to the specific challenges of additively manufactured titanium alloys.

This study elucidates the tribological interactions and wear mechanisms at the tool-chip interface during the milling of Powder Bed Fusion (PBF) additively manufactured (AMed) Ti6Al4V alloy. The synergistic effects of hybrid cooling-lubrication strategy combining COQ cryogenic cooling with AlQO3-based nanofluid minimum quantity lubrication (nanoMQL) were investigated under dry, mono-cryogenic, and mono-nanoMQL environments. Milling experiments were conducted at two cutting speeds (100 and 150 m/min) to assess the influence of thermal and mechanical loads on tool degradation. Tool wear was evaluated through quantitative measurements and characterized via scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) to reveal dominant wear modes. Results show that the hybrid nanoMQL + COQ strategy provided the most effective wear suppression, reducing flank wear by up to 38.97% compared to cryogenic cooling and 26.5% compared to dry machining at 100 m/min. While nanoMQL alone also demonstrated considerable improvements in tool life by enhancing both cooling and lubrication, COQ only cooling, despite its thermal control capabilities, induced brittle wear mechanisms due to the suppression of thermal softening. Increasing the cutting speed amplified tool wear across all conditions, with dry machining at 150 m/min exhibiting the highest wear rate due to intensified thermal and mechanical stresses. SEM and EDX analyses revealed built-up edge (BUE) and built-up layer (BUL) formation, notching, chipping, and fracture as the primary wear mechanisms, which varied significantly with cooling-lubrication strategy. The hybrid environment minimized adhesive layer formation and suppressed thermally activated diffusion, thereby preserving cutting edge integrity. These findings underscore the potential of hybrid cooling-lubrication techniques in enhancing machining performance of AMed Titanium alloys and contribute to the development of more sustainable and efficient manufacturing strategies.

The cobalt-based Haynes 25 superalloy is a key material in sectors such as aerospace, medical, and energy, known for its outstanding high-temperature strength, wear and corrosion resistance. However, its low thermal conductivity and rapid work hardening rate make it inherently difficult to machine, highlighting the need for new cooling and lubrication methods. This work investigates the machinability of Haynes 25 under various sustainable cooling and lubrication techniques, including dry conditions, minimum quantity lubrication (MQL), nanofluids, and cryogenic COQ. Additionally, hybrid systems combining cryogenic COQ with nanofluids are also being investigated. The effectiveness of these approaches was ascertained by thorough investigations of surface roughness, cutting temperature, tool wear, and its mechanisms, and power consumption. Experimental results show that hybrid cooling systems especially those including nanofluids and cryogenic COQ significantly improve machining performance. Compared to dry machining, these methods minimized tool wear by 38 % and achieved up to a 44 % reduction in cutting temperature and a 32 % reduction in power usage. These results were a result of the enhanced thermal and tribological characteristics of nanofluids along with COQ's fast cooling capacity. This work provides a route toward sustainable and high-performance manufacture of challenging-to-machine materials by highlighting the possibilities of hybrid cooling strategies to maximize machining efficiency, extend tool life, and lower environmental impact.

One of the significant challenges the manufacturing industry faces is creating sustainable machining processes that strike a balance between economic productivity and energy consumption. To address this challenge, this work is focused on a comprehensive life cycle assessment (LCA) analysis and machinability analysis during the milling of wrought and wire arc additively manufactured (WAAMed) Inconel 925 (IN925). In addition, the work offers an in-depth description of the steps essential to conduct LCA. Four conditions are used for machining experiments: dry, flood cooling, minimum quantity lubrication (MQL), and hybrid nanofluid MQL (HNMQL). LCA is performed for 18 environmental impact categories using the ReCiPe 2016 Midpoint (H) impact assessment method. The comparison study demonstrated the potential benefits of additive manufacturing, especially in terms of lower material waste and energy efficiency. Using HNMQL reduced surface roughness by approximately 19-46

In this study, the effect of sustainable cooling and lubrication strategies such as MQL, LN2, LN2+MQL, LN2+hBN/GA, LN2+GNP/GA, LN2+hBN-GNP/GA on drilling nickel-based Hastelloy X alloy was examined. The environmental impacts and health risks of traditional petroleum-based cutting fluids used in drilling operations have led researchers to look for ecological alternatives. In this context, combinations of nanofluids enriched with minimum quantity lubrication (MQL), liquid nitrogen (LN2), and nanosized hBN and GNP particles have been tested. The experiments were carried out at cutting speeds of 20 and 30m/min and feed rates of 0.04 and 0.06mm/rev. Nanofluids characteristics i.e., viscosity, Ph, thermal conductivity and wettability, and drilling performance were evaluated with criteria such as cutting force, surface roughness, hole quality and tool wear. The results obtained showed that the hybrid methods combining LN2 and nanofluid-based MQL provided superior performance in terms of both cooling and lubrication, and the condition directly positively affected the processing outputs. This study contributes to the literature by revealing the potential of ecological cooling/lubrication methods in the sustainable production of difficult-to-machine materials such as Hastelloy X.

Despite being expensive and difficult to process, the Ti6Al4V alloy is a vital component for crucial industries. To improve its machinability and accomplish sustainable production, environmentally friendly cooling and lubricating agencies are used. Studies on the machinability of the alloy are still necessary because of its unique features and significance in vital industries like aerospace, defense, and medicine. Therefore, this investigation focuses on tool wear, temperature, and surface integrity for sustainable milling Ti6Al4V under various machining environments, i.e., dry, pure-MQL, LN2, 2 , hBN, CuO-doped nanofluids, and hybrid methods. The produced nanofluids' thermophysical and rheological characteristics were examined in the study's initial phase. Because of the results from the first stage, machining performance indicators were assessed in the subsequent milling experiments. As a result, CuO-doped nanofluids gave improved results in terms of viscosity and pH. The best results obtained in the LN2 2 + CuO hybrid cooling lubrication environment in important machinability outcomes such as tool wear and surface integrity were attributed to the rheological properties of CuO-doped nanofluid and its harmonious cooperation with LN2-cryogenic 2-cryogenic cooling.

Three-dimension (3D) printing technology, also known as additive manufacturing, is a manufacturing technology that creates three-dimensional objects by depositing material layer by layer, as opposed to subtractive manufacturing methods. However, the newness of the technology brings with it many unknowns. In particular, the raw materials used are constantly increasing. For this reason, testing each raw material used in many aspects and to determine the optimum production conditions is important for the wide use of 3D printing technology. These optimal conditions may be the parameters used to produce a material, and sometimes they can appear as a new material. In addition, the production of new materials with varying production parameters is fundamental research topic that requires comprehensive study. For all these purposes, in this study, a new material type known as Lubri PLA (LPLA) was selected and produced in different filling types and subjected to a series of friction and wear tests. Thus, it is aimed to determine the tribological properties of the material. Additionally, samples were produced in ten different infill types (grid, lines, triangels, hexagon, cubic, octal, zigzag, diagonal, diagonal 3D and gyroid) to show the effect of filler type on friction and wear behavior. These filler types were used for both PLA and Lubri PLA materials and a total of twenty samples were produced. Thereby, it is aimed to conduct a comprehensive study showing the effect of both material difference and filling type on friction-wear behavior. Diameter deviations, hardness deviations, friction coefficient, temperature, specific wear rates (SWr), and vibration were selected as output parameters. According to the analysis of the test results, the best result in terms of material structure was given by Lubri PLA, while the best result in terms of filling type was obtained with Diagonal 3D filling type. In addition, the lowest vibration level was obtained in the LP-Diagonal 3D sample with 0.041 mm/s2, while the highest vibration level was obtained in the P-Grid sample with 1.756 mm/s2.Highlights LPLA closed to nominal value in diameter and hardness deviations Addition of graphite nanoparticle increased the dimensional accuracy Diagonal 3D infill type Lubri PLA composites showed the superior performance Graphite modified Lubri PLA composites demonstrated superior performance The Graphical Abstract is proper for publication. image

In this study, during the turning process of Ti6Al4V alloy, which is difficult to machine, nanofluid, whose base fluid is vegetable oil (sunflower oil), was applied to the cutting zone with the minimum quantity lubrication (MQL) technique. Nanofluids were prepared by adding hexagonal boron nitride (hBN) nanoparticles (65-75 nm) with different concentration ratios (0.5 and 1%) and surfactant (Sodium dodecyl sulfate, SDS) into vegetable oil. Thermal conductivity coefficients and dynamic viscosities of the prepared nanofluids and pure sunflower oil were measured at four different temperatures. Additionally, the stability of the prepared nanofluids was observed for 15 months. In turning experiments, four different cutting speeds (50, 75, 100 and 125 m/min), four different feed rates (0.05, 0.10, 0.15 and 0.20 mm/rev) and four different cooling conditions (dry, PureMQL, 0.5% NanoMQL and 1% NanoMQL) were used. The effect of the change in these parameters on surface roughness (Ra), temperature in the cutting zone (T) and flank wear on the tools (Vb) was investigated experimentally and analytically. As a result of the research, the experimental results were evaluated using variance analysis, signal/noise (S/N) analysis and artificial neural networks (ANN) methods. As a result of the measurements and observations, it was determined that the nanofluid with 0.5% concentration had the best stability. In the main experiments, the MQL condition using this nanofluid (0.5% NanoMQL) exhibited the best machining performance. In the wear experiments, the lowest tool wear was detected under the 1% NanoMQL condition. According to the ANOVA and S/N analysis results showed that Ra was most affected by the feed rate (95%), T was most affected by the cooling condition (70%), and Vb was most affected by the cutting speed (45%). The prediction performances of ANN and Taguchi approaches were examined and the prediction success of these approaches was more than 98.5% and 80.8%, respectively. Especially for Vb values that have very close data, more accurate predictions were made with the ANN approach compared to Taguchi.

One of the main goals in sustainability is to reduce the environmental effects of boundary and mixed lubrication on rubbing surfaces. Petroleum-based fluids are at the center of environmental concerns and have attracted the attention of researchers in recent years. Vegetable-based oils are a good alternative to petroleum-based oils, and their tribological performance is a matter of curiosity. For the last 10 years, nanoparticle additives have been used to increase the tribological effect of plant-based oils. Green tribology is an integrated concept that includes the terms nanotribology and biotribology. In this study, nanofluid was prepared by adding SiO2 and TiO2 nanoparticles into the vegetable-based oil to examine green tribology performance. Friction/wear tests were applied to AISI 329 stainless steel material with a ball-on-disc tester. In the green tribology performance evaluation, pH, thermal conductivity, surface roughness, topography, microhardness deviations, coefficient of friction (CoF), track width, SEM analysis, and power consumption results were taken into consideration. As a result of the tests, the SiO2 nanofluid condition provided a reduction of 40.76

Integrating fiber reinforcement plastics (FRP) materials into the industry plays a key role especially for pipes. However, due to the production methods of CFRP pipes, surface finishing processes are inevitable at the end of production. Despite the widespread use of CFRP materials, the predominant focus in the literature has been on their mechanical performance. This study aims to contribute to the limited research on the machinability of CFRP materials. In this context, the turning machining process for CFRP pipes was experimentally investigated in the present study. For this purpose, carbon fiber pipes with an inner diameter of 30 mm and an outer diameter of 60 mm were produced and subjected to computer numerical control (CNC) turning. First, a cylindrical aluminum pipe is used as a mold to manufacture CFRP pipes. Unidirectional (UD) carbon fabrics were wrapped on these aluminum molds. Shrink tape was used to enhance the surface smoothness and required pressure to prevent delaminating of the end product during the process. UD carbon fabrics are wrapped on to the mold at the selected angles (0 degrees, 45 degrees, and 90 degrees) and the CFRP pipe specimens were manufactured using epoxy matrix. Pipes were processed on CNC lathe at 120, 160, 200 rev/min speeds and f 0.4 mm/rev feed rate. The surfaces of the machined specimens were measured with a microscope and a surface roughness device. On the other hand, wear on the tools was observed after the process.

Eklemeli imalat, bilgisayar kontrollü üç boyutlu katı model verilerini kullanan modern bir imalat yöntemidir. Eklemeli imalatta amaç; malzemeyi kademeli şekilde üreterek nihai şekline getirmektir. Bu sayede karmaşık geometrilere sahip ürünlerin elde edilmesi diğer klasik yöntemlere göre nispeten daha kolaydır. Özellikle, yüksek ölçüm doğruluğuna, yüksek dayanıma ve düşük ağırlığa sahip parçaların hızlı üretilmesinin gerekli olduğu havacılık-uzay endüstrisi, biyomedikal ve savunma sanayii gibi geniş bir alanda tercih edilmektedir. Eklemeli imalat birçok alt yöntemden oluşmakta ve bu yöntemler malzemenin cinsi, parçanın boyutu, kullanım amacı, çalışma prensibi, malzemelerin hassasiyeti ve özellikleri, üretim sayısı ve hızı gibi birçok kritere bağlıdır. Seçici lazer eritme (SLM) yöntemi, eklemeli imalat yöntemleri arasında genellikle tercih edilmektedir. Ancak, SLM prosesini doğrudan ve dolaylı parametreler olmak üzere birçok faktör etkileyebilmektedir. Bu çalışmanın amacı, farklı üretim parametrelerinin SLM yöntemi kullanılarak üretilen Ti6Al4V alaşım malzemesi üzerinde mekanik özelliklerine etkisini incelemektir. Bu amaç doğrultusunda dört farklı üretim parametresi ve seviyeleri üretim parametresi olarak belirlenmiştir. Değerlendirme kriteri olarak çekme dayanımı, elastisite modülü ve uzama yüzdesi seçilmiştir. Deney tasarımında Taguchi L16 tercih edilmiştir. Deney sonuçları değerlendirilirken S/N analizi kullanılmıştır. Kontrol faktörlerin etki düzeyini belirlemek için varyans analizi (ANOVA) yapılmıştır. Deney sonuçlarından elde edilen verilerle çekme dayanımı için optimum parametreler; 75 μm lazer odak çapı, 230 W lazer gücü, 60 μm tarama mesafesi ve 300 mm/sn hız tarama hızı olarak tespit edilirken, elastisite modülü için 60 μm tarama mesafesi, 450 mm/sn tarama hızı, 80 μm lazer odak çapı ve 250 W lazer gücü ve uzama miktarı için 90 μm lazer odak çapı, 150 μm tarama mesafesi, 450 mm/sn tarama hızı ve 230 W lazer gücü olarak tespit edilmiştir.

In this study, nanofluids prepared by incorporating silicon dioxide (SiO2) nanoparticles into sunflower oil were used as cutting fluids for turning AISI 304 stainless steel. Dynamic viscosities and thermal conductivities of nanofluids prepared at two different concentrations (1 % and 0.5 % by volume) were measured at four different temperature conditions. The experiments were carried out in two stages: main experiments and additional experiments. In the main experiments, four different cooling conditions (dry, PureMQL, 0.5 % NanoMQL, 1 % NanoMQL), four different cutting speeds (80, 120, 160, 200 m/min), and four different feed rates (0.10; 0.15, 0.20, 0.25 mm/rev) were used. In additional experiments, the effect of 4 different cooling methods on machining performance was investigated by keeping the maximum cutting speed (200 m/min) and feed rate (0.25 mm/rev) constant. In all experiments, workpiece surface roughness (Ra), temperature in the cutting zone (T), and flank wear on cutting tools (Vb) were determined as performance criteria. Also, additional experiments were repeated 45 times, and wear was measured every ten experiments to get a clearer picture of the tool wear process. At the end of the study, it was determined that the most effective parameter on surface roughness was feed rate (76 %), while the temperature in the cutting zone and tool wear were mainly affected by the cooling method (80 % and 50.5 %, respectively). The best machining performance was observed in the 0.5 % nanoMQL method.

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 (LN2) and hybrid (MQL + LN2) 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, LN2, 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.

The potential of VT-20, a titanium (Ti) alloy in the aircraft industry, is increased as it has stronger thermal capabilities than other pseudo-alpha-Ti alloys. However, the alloy's low heat conductivity and chemical reactivity make machining difficult and necessitate efficient cooling/lubrication. Cutting oils based on emulsion have been used to move heat from the cutting region; however, they are not sustainable due to their negative impacts on workers' health and the environment. Therefore, this novel study investigates alternative lubricating approaches, such as drilling VT-20 alloy under dry, MQL, EMQL, and HNPEMQL conditions using SEM and line-scan EDS analysis. An indigenously developed electrostatic minimum quantity lubrication (EMQL) and hybrid nanoparticles (NPs) immersed in EMQL (HNPEMQL) techniques were utilized to improve drilling performance while reducing cutting oil consumption. Hybrid nanofluids for HNPEMQL application were developed using aluminium oxide (Al2O3) and plate-structured graphene nanoparticles using a two-step process. The surface quality of the drilled hole, tool wear, thrust force, power consumption, hole quality indicators, and microhardness are evaluated. The efficacy of HNPEMQL showed improved drilling efficiency compared to dry, MQL, and EMQL machining. HNPEMQL, EMQL, and MQL conditions reduced tool wear by 102 %, 53 %, and 19%, respectively, to dry drilling. The HNPEMQL condition lowered the thrust force by 75.3 %, 28.69 %, and 18.02 %, respectively, compared to the dry, MQL, and EMQL. HNPEMQL demonstrated a 105 %, 41 %, and 22 % reduced variation in circularity values than dry, MQL, and EMQL for the same number of drilled holes. The findings show that HNPEMQL can be considered a promising cooling and lubricating strategy with improved drilling performance and quality.

In present investigation, a number of experiments were done to determine the impact of surfactants on Waspaloy machining characteristics and the friction-wear behavior on the ball-on-disc tester. The experiments were carried out in dry, base fluid (sunflower oil), Cuo, and ZnO nanofluid conditions with/without surfactant. Four distinct surfactants, including Gum Arabic (GA), Sodium Dodecyl Sulfate (SDS), CeTyltrimethylAmmonium Bromide (CTAB), and PolyVinyl Pyrrolidone (PVP), were employed to prepare the nanofluids with surfactant. In addition, viscosity, pH, and thermal conductivity measurements were made to determine the prepared nanofluid's thermo-physical properties. Tool wear and its mechanisms, surface roughness and cutting temperature in machining experiments, coefficient of friction (CoF), microhardness, and wear track width in ball-on-disk tests were choosen as evaluation criterias. From both the machining and ball-on-disk test results, it was determined that the ZnO + PVP nanofluid condition outperformed the other conditions. The ZnO + PVP nanofluid condition provided 53.9 %, 36.52 %, and 44 % improvement in tool wear, surface roughness, and cutting temperature, respectively, compared to the dry cutting condition. Also, considering the results of the ball-on-disk test, it was found that the CoF and width track width values for the ZnO+PVP nanofluid condition were both 76.02 % and 56.11 % lower than the dry condition.

In recent years, developments in the defense, aerospace, and medical industries have significantly increased the expectations regarding material performances. In particular, the demand for materials that can withstand very high and/or very low temperatures and harsh mechanical/chemical conditions has increased. The superior qualities of superalloys can adequately meet this demand. However, the difficulties encountered in the machining of these alloys cause some burdens both ecologically and economically due to the use of cutting fluid. Therefore, the use of cost-friendly and sustainable cutting fluids in the production industry has a vital role, both in terms of machining performance and the environment. From this perspective, this paper focuses on the effects of various cutting environments, i.e., Dry, MQL, LN2, N-2, CO2, Vortex, LN2 + MQL, N-2 + MQL, CO2 + MQL, and Vortex +MQL on the machining performance of Ni-based C4 alloy. Additionally, it was aimed to reveal the effect of cooling/lubrication methods on sustainability by performing a sustainability analysis. Firstly, surface roughness, power consumption, tool wear and mechanisms, and cutting temperature were considered as performance characteristics. When examined in terms of machinability, Vortex + MQL gave the best result in terms of surface roughness and power consumption, while LN2 gave the best result in terms of cutting temperature. Then, a comprehensive sustainability analysis was carried out. As a result, the CESMO follows the order of Dry > MQL > LN2 > LN(2 +)MQL > CO2 > CO2 + MQL > N-2 > N-2 + MQL > Vortex > Vortex + MQL. While employing Vortex + MQL cutting condition, the CESMO decreased by about 11.37% as compared to Dry cutting condition. While using a combination of different sustainable lubrications or coolants, the overall carbon emissions decreased in the range of about 15-25% approximately as compared to the employment of the individual cutting conditions (i.e., coolant/lubricants).

One of the essential elements of automated and intelligent machining processes is accurately predicting tool life. It also helps in achieving the goal of producing quality products with reduced production costs. This work proposes a computer vision-based tool wear monitoring and tool life prediction system using machine learning methods. Gradient-boosted trees and support vector machine (SVM) techniques are used to predict tool life. The experimental investigation on the CNC machine is conducted to study the applicability of the proposed tool wear monitoring system. Experiments are performed using workpiece material made of alloy steel and PVD-coated cutting inserts, and flank wear is monitored. An imaging system consisting of an industrial camera, lens, and LED ring light is mounted on the machine to capture tool wear zone images. Images are then processed by algorithms developed in MATLAB ® . Boosted tree methods and the SVM methodology have 96% and 97% prediction accuracy, respectively. Validation tests are carried out to determine the accuracy of proposed models. It is observed that the prediction accuracy of boosted three and SVM is good, with a maximum error of 5.89% and 7.56%, respectively. The outcome of the study established that the developed system can monitor the tool wear with good accuracy and can be adopted in industries to optimize the utilization of tool inserts.

Purpose The purpose of this study is the investigation of the friction performance of 3D-printed polylactic acid (PLA) at different infill densities. Design/methodology/approach PLA samples were printed with fused filament fabrication (FFF). Friction performance test of PLA samples were performed under 18 N load at 20 min, 40 min and 60 min using a pin-on-disc tester. Diameter deviation, hardness of 3D-printed PLA, weight variation, coefficient of friction, temperature and wear images were chosen as performance criteria. Findings The hardness values of the samples with 30%, 50% and 70% infill density were determined as 93.9, 99.93 and 102.67 Shore D, respectively. The friction of coefficient values obtained in these samples at 20 min, 40 min and 60 min were measured as 0.5737, 0.4454 and 0.3824, respectively. The least deformation occurred in the sample with 50% occupancy rate and during the test period of 20 min. Practical implications The aim of this study was to determine the best friction performance of 3D-printed biodegradable and biocompatible PLA with different infill densities. Originality/value In the literature, several studies can be found on the mechanical characteristics of 3D-printed parts produced with PLA. However, investigations on the wear characterisation of these parts are very limited. In this regard, the friction coefficient results obtained from different infill density of 3D-printed PLA used in this study will significantly contribute to the literature.