Influence of heat treatment on the machinability and corrosion behavior of AZ91 Mg alloy

In the present study,AZ91 Mg alloy was heat treated at 410℃ for 6,12 and 24 h to investigate the influence of heat treatment on machinability and corrosion behavior.The effect of soaking time on the amount and distribution of Mg 17 Al 12(β-phase)was analyzed under the optical microscope.Microhardness measurements demonstrated the increased hardness with increased heat treatment soaking time,which can be attributed to the solid solution strengthening.The influence of super saturatedα-grains on reducing the cutting force(F z)with respect to increased cutting speed was observed as prominent.The corrosion behavior of the heat treated specimens was studied by conducting electrochemical tests.Surprisingly,corrosion rate of heat treated samples was observed as increased compared with the base material.From the results,it is evident that the machinability of AZ91 Mg alloy can be improved by producing super saturatedα-grains through heat treatment but at the cost of losing corrosion resistance.

Effect of inoculating addition on machinability of gray cast iron

Gray cast irons were inoculated with FeSi75＋RE and FeSi75＋Sr inoculants. The changes of apex angle of the drills before and after being used were used to evaluate machinability of gray cast irons. Effect of FeSi75＋RE and FeSi75＋Sr inoculants on mechanical properties, machinability and sensibility of gray cast iron used in cylinder block were investigated. Experimental results showed that gray cast iron treated with 60%FeSi75＋40% RE inoculants exhibited tensile strength consistently at about 295 MPa along with good hardness and improved metallurgical quality. While gray cast iron inoculated with 20%FeSi75＋80% Sr inoculants exhibited the best machinability, the lowest cross-section sensibility and the least microhardness difference. The tool flank wear of the drill increased correspondingly with the increase of the microhardness difference of the matrix, indicating the great effect of homogeneity of the matrix on the machinability of gray cast iron.

Precipitation and control of BN inclusions in 42CrMo steel and their efect on machinability

The precipitation and control of boron nitrogen （BN） inclusions in 42CrMo steel were investigated and their effect on machinability was analyzed. First, the precipitation regularity of BN in 42CrMo steel was studied by theoretical calculation. Then, the machinability of the steel was investigated through contrast cutting experiments, and the composition and cooling rate of the steel were controlled to analyze the variation laws of the size, distribution, and area ratio of BN inclusions. Finally, the results were combined with the machinability of the steel to analyze the relationship among them. It is found that the machinability of the steel is mainly influenced by the diameter and quantity of BN inclusions. Fine and dispersedly distributed BN inclusions are more beneficial for the improvement in machinability of 42CrMo steel than coarse and sparse BN inclusions.

Experiment on Machinability of Ti2AlNb Intermetallic Alloy

Ti2AlNb intermetallic alloy is a newly developed high-temperature resistant structural material due to its excellent material and mechanical properties,which also make it to be one of the most difficult-to-cut materials.In order to study the machinability of Ti2AlNb alloy,a series of turning experiments of Ti2AlNb alloy with varying cutting speed and feed rate using coated carbide tools are carried out.The results associated with cutting forces,cutting temperature and tool wear are presented and discussed.Moreover,the cutting performance of Ti2AlNb alloy is evaluated in comparison with that of most commonly used Ti6Al4 Vand Inconel 718 alloys in terms of the cutting forces and cutting temperature.The comparison results show that there is a correlation between the machinability and the mechanical properties of work material properties.Additionally,considering material removal rate and tool life,the optimized machining parameters for cutting Ti2AlNb alloys using coated carbide tools are recommended.

Experimental Study of Machinability in Millgrinding of SiCp/Al Composites

An attempt was made to investigate the machinability of Si Cp/Al composites based on the experimental study using mill-grinding processing method. The experiments were carried out on a high-speed CNC machining center using integrated abrasive cutting tool. The effects of combined machining parameters, e g, cutting speed（vs）, feed rate（vf）, and depth of cut（ap）, with the same change of material removal rate（MRR） on the mill-grinding force and surface roughness（Ra） were investigated. The formation mechanism of typical machined surface defects was analyzed by SEM. The experimental results reveal that with the same change of material removal rate, lower mill-grinding force values can be gained by increasing depth of cut and feed rate simultaneously at higher cutting speed. With the same change of MRR value, lower surface roughness values can be gained by increasing the feed rate at higher cutting speed, rather than just increasing the depth of cut, or increasing the feed rate and depth of cut simultaneously. The machined surface of Si Cp/Al composites reveals typical defects which can influence surface integrity.

Machinability of Hastelloy C-276 Using Hot-pressed Sintered Ti(C_7N_3)-based Cermet Cutting Tools

C-276 nickel-based alloy is a difficult-to-cut material. In high-speed machining of Hastelloy C-276, notching is a prominent failure mode due to high mechanical properties of work piece, which results in the short tool life and low productivity. In this paper, a newly developed Ti（C7N3）-based cermet insert manufactured by a hot-pressing method is used to machine the C-276 nickel-based alloy, and its cutting performances are studied. Based on orthogonal experiment method, the influence of cutting parameters on tool life, material removal rates and surface roughness are investigated. Experimental research results indicate that the optimal cutting condition is a cutting speed of 50 m/min, depth of cut of 0.4 mm and feed rate of 0.15 mm/r if the tool life and material removal rates are considered comprehensively. In this case, the tool life is 32 min and material removal rates are 3000 mm^3/min, which is appropriate to the rough machining. If the tool life and surface roughness are considered, the better cutting condition is a cutting speed of 75 m/min, depth of cut of 0.6 mm and feed rate of 0.1 mm/r. In this case, the surface roughness is 0.59μm. Notch wear, flank wear, chipping at the tool nose, built-up edge（BUE） and micro-cracks are found when Ti（C7N3）-based cermet insert turned Hastelloy C-276. Oxidation, adhesive, abrasive and diffusion are the wear mechanisms, which can be investigated by the observations of scanning electron microscope and energy-dispersive spectroscopy. This research will help to guide studies on the evaluation of machining parameters to further advance the productivity of nickel based alloy Hastelloy C-276 machining.

Sintering and Machinability of Monazite-Type CePO_4 Ceramics

The sintering and machinability of monazite-type CePO_4 ceramics were investigated. Relative density ≥98% and apparent porosity <2% were achieved when the monazite-type CePO_4 were sintered at 1500 ℃/1 h in air,and the maximal bending strength value (184 MPa) was achieved at this temperature. CePO_4 ceramics has a multilayer structure and an exciting 'ductility',so it can be drilled and cut with WC cutter with a small machining damage.

Superior machinability of steel enhanced with BN and MnS particles

The strategy that replacing part of MnS with BN was proposed in order to decrease the sulfur content in sulfur based free-cutting steel. The effects of BN and MnS inclusions on the microstructure and machinability of the steel were systematically investigated. The results show that most of the BN and MnS inclusions exist individually in the steel and only a small amount of them are in a composite state form- ing either isolated particles or clusters of particles. In the case of multi-phased steel, the theoretical calculation predicts that the volume of large BN particles should be 0.7 times of the volume of large MnS particles. The machinability of this type of BN and MnS alloy steel over a wide range of cutting speeds ranging from a low speed appropriate for drilling to a high speed appropriate for turning is confirmed as being equal to or superior to that of an MnS reference steel, even though the sulfur content in the composite steel is only half that of the MnS steel. The aptitude for cutting effect of 240 ppm nitrogen and 115 ppm boron in the composite steel is demonstrated to be equivalent or even better than 1000 ppm sulfur in MnS free-cutting steel.

Influence of inoculation on cast iron machinability:Case studies

Machinability can sometimes be difficult to predict and be impacted by different characteristics of the castings.Inoculation,a key step in foundry process,is well-known to be a powerful tool to adjust the characteristics of castings in both grey and ductile irons.Some metallurgical cases were investigated to understand different machinability behaviors in correlation to their metallographic characteristics.Thus,two examples taken from grey iron processes are analyzed to illustrate how inoculation is required to adjust characteristics of iron castings,especially the modification of graphite characteristics and the prevention of micro-shrinkage,both parameters are well-known to have an impact on iron machinability.The study also illustrates the importance of the ratio Mn/S to guarantee the presence of manganese sulfides in the matrix,beneficial for iron machinability.

Comparative Assessment on Machinability of Nano-Structured Bainitic Steel and Titanium64

Titanium64 has characteristics well sought after for applications in demanding environments. In general, due to titanium64’s high performance, it is a material which requires careful and well considered machining approaches in order to optimize the process. Nano-structured bainitic steel whilst having different application bases does none the less have similar machining and machinability short comes as that of titanium64. These similar characteristics have been compared and contrasted in this research study using parameters including cutting force, surface texture and metallography. The results tend to indicate that titanium64 has a poorer machinability characteristics compared to nano-structured bainitic steel. However, in terms of achieving greater surface texture characteristics, the nano-structured bainitic steel exhibited an enhanced capacity.

Machinability of Polymeric Composites and Future Reinforcements—A Review

This paper reviews the machinability and mechanical properties of natural fiber-reinforced composites. Coupling agents, operating parameters, as well as chemical treatment effects on natural fiber-reinforced composites’ machinability are also reviewed. Moreover, the impacts of fibers’ physical properties on the machinability of the composite are mentioned. Fiber volume fraction (Vf), fiber orientation as well as chemical treatment effects on mechanical properties are also defined. Conclusively, the effect of fibers’ physical properties as well as mechanical properties is described. It was discovered that chemical treatment of natural fibers improved their compatibility with the matrix by removing their surface tissues, increasing the roughness average (Ra), and reducing moisture absorption. Also, the Orientation of the fiber plays an important role in controlling the mechanical properties of the composite. Moreover, some physical properties of the fibers, including quality of fiber distributed in the matrix;fiber size, length, and diameter;moisture absorption;porosity and the way fibers break during compounding with the matrix, were found to affect the mechanical properties of the composites formed.

Comprehensive Study on Machinability of Titanium Composite

Metal framework composites have higher mechanical properties in examination to metals over an extensive variety of working conditions. This makes them an alluring alternative in swapping metals for different building applications. The present review is a study on the influence of composite titanium on the cutting parameters, mechanical behavior, reinforcements, structure and nanostructure. This review will provide an understanding into selecting the optimum machining parameters for machining titanium composites. It’s also an attempt to give brief explanation by suitably machining the titanium composite which can be made reasonable.

A review on machinability of carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP)composite materials

Fiber reinforced polymer(FRP) composite materials are heterogeneous and anisotropic materials that do not exhibit plastic deformation. They have been used in a wide range of contemporary applications particularly in space and aviation,automotive,maritime and manufacturing of sports equipment. Carbon fiber reinforced polymer(CFRP) and glass fiber reinforced polymer(GFRP) composite materials,among other fiber reinforced materials,have been increasingly replacing conventional materials with their excellent strength and low specific weight properties. Their manufacturability in varying combinations with customized strength properties,also their high fatigue,toughness and high temperature wear and oxidation resistance capabilities render these materials an excellent choice in engineering applications.In the present review study,a literature survey was conducted on the machinability properties and related approaches for CFRP and GFRP composite materials. As in the machining of all anisotropic and heterogeneous materials,failure mechanisms were also reported in the machining of CFRP and GFRP materials with both conventional and modern manufacturing methods and the results of these studies were obtained by use of variance analysis(ANOVA),artificial neural networks(ANN) model,fuzzy inference system(FIS),harmony search(HS) algorithm,genetic algorithm(GA),Taguchi's optimization technique,multi-criteria optimization,analytical modeling,stress analysis,finite elements method(FEM),data analysis,and linear regression technique. Failure mechanisms and surface quality is discussed with the help of optical and scanning electron microscopy,and profilometry. ANOVA,GA,FEM,etc. are used to analyze and generate predictive models.

Forgeability and Machinability of Stir Cast Aluminum Alloy Metal Matrix Composites

In the present paper, the aluminum alloy i.e. LM6 based composites reinforced with different weight fraction of SiC particles was produced by stir cast technique and the effect of reinforced ratios on the forgeability and the machinability was examined. The test results show that the increment in weight fraction of reinforcement particles in the matrix metal produced better mechanical property like hardness but the forgeability of the cast MMCs decreases. The forgeability of the as cast MMCs were also varied with the change in thickness of the casting. The results show that the forgeability of cast metal matrix composites at the mid section of the casting is minimum compared to both end section of a three-step casting. The effect of machining parameters, e.g. cutting speed and depth of cut on the surface roughness and cutting forces at constant feed rate was investigated during experimentation. The results show that higher weight percentage of SiCp reinforcement produced a higher surface roughness and needs higher cutting forces during machining operation. It has also observed that the depth of cut and the cutting speed at constant feed rate affected the surface roughness and the cutting forces. This practical research analysis and test results on the forgeability and machinability of Al/SiC-MMC will provide useful guidelines to the present day manufacturing engineers.

Influence of Coolant in Machinability of Titanium Alloy (Ti-6Al-4V)

Application of titanium alloy has increased many fields since the past 50 years. The major drawback encountered during machining was difficult to cut and the formation of BUE (Built up Edge). This paper presents the tool wear study of TTI 15 ceramic insert (80% Aluminum oxide and 20 % Titanium carbide) on machining Ti-6Al-4V at moderate speed with and without the application of water soluble servo cut S coolant. Titanium alloy is highly refractory metal and machining titanium is challenging to the manufacturers. Experiments were carried out on medium duty lathe. Application of coolant tends to reduce toolwear and minimize adhesion of the work material on the cutting tool during machining and also improves the surface finish. Result provides some useful information.

Machinability ofγ-TiAl:A review

Owing to its outstanding mechanical properties,γ-TiAl is desirable materials for crossgeneration aero-engines.Nearly 70 years of exploration have made it into the initial application.However,the intrinsic brittleness ofγ-TiAl is still a critical obstacle to its large-scale applications.In this context,researchers have made many attempts to study the machinability ofγ-TiAl.At present,existing relevant reviews have mostly discussed the processing methods ofγ-TiAl.Hence,there is still a lack of a perspective on material properties to analyze the cutting mechanism.Herein,this paper provides the systematic review of such perspectives.Above all,the developmental process,phase transformation,and microstructural evolution ofγ-TiAl are discussed,as well as its deformation mechanism at quasi-static.These topics can provide a materials science foundation for the machining ofγ-TiAl.And then,the review focuses on the cutting mechanism and surface integrity ofγ-TiAl.Moreover,special attention is paid to the microscope deformation mechanism and surface defects evolution ofγ-TiAl during cutting.Finally,the review indicates that the highperformance machining technology ofγ-TiAl faces challenges and proposes potential future research directions.Solving the difficulties during machiningγ-TiAl aero-engine components will accelerate the development of new aero-engines.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Machine learning applications in stroke medicine:advancements,challenges,and future prospectives

Stroke is a leading cause of disability and mortality worldwide,necessitating the development of advanced technologies to improve its diagnosis,treatment,and patient outcomes.In recent years,machine learning techniques have emerged as promising tools in stroke medicine,enabling efficient analysis of large-scale datasets and facilitating personalized and precision medicine approaches.This abstract provides a comprehensive overview of machine learning’s applications,challenges,and future directions in stroke medicine.Recently introduced machine learning algorithms have been extensively employed in all the fields of stroke medicine.Machine learning models have demonstrated remarkable accuracy in imaging analysis,diagnosing stroke subtypes,risk stratifications,guiding medical treatment,and predicting patient prognosis.Despite the tremendous potential of machine learning in stroke medicine,several challenges must be addressed.These include the need for standardized and interoperable data collection,robust model validation and generalization,and the ethical considerations surrounding privacy and bias.In addition,integrating machine learning models into clinical workflows and establishing regulatory frameworks are critical for ensuring their widespread adoption and impact in routine stroke care.Machine learning promises to revolutionize stroke medicine by enabling precise diagnosis,tailored treatment selection,and improved prognostication.Continued research and collaboration among clinicians,researchers,and technologists are essential for overcoming challenges and realizing the full potential of machine learning in stroke care,ultimately leading to enhanced patient outcomes and quality of life.This review aims to summarize all the current implications of machine learning in stroke diagnosis,treatment,and prognostic evaluation.At the same time,another purpose of this paper is to explore all the future perspectives these techniques can provide in combating this disabling disease.

Assessment of compressive strength of jet grouting by machine learning

Jet grouting is one of the most popular soil improvement techniques,but its design usually involves great uncertainties that can lead to economic cost overruns in construction projects.The high dispersion in the properties of the improved material leads to designers assuming a conservative,arbitrary and unjustified strength,which is even sometimes subjected to the results of the test fields.The present paper presents an approach for prediction of the uniaxial compressive strength(UCS)of jet grouting columns based on the analysis of several machine learning algorithms on a database of 854 results mainly collected from different research papers.The selected machine learning model(extremely randomized trees)relates the soil type and various parameters of the technique to the value of the compressive strength.Despite the complex mechanism that surrounds the jet grouting process,evidenced by the high dispersion and low correlation of the variables studied,the trained model allows to optimally predict the values of compressive strength with a significant improvement with respect to the existing works.Consequently,this work proposes for the first time a reliable and easily applicable approach for estimation of the compressive strength of jet grouting columns.

Effects of in-situ TiB_(2)particles on machinability and surface integrity in milling of TiB_(2)/2024 and TiB_(2)/7075 Al composites

In-situ ceramics particle reinforced aluminum matrix composites are favored in the aerospace industry due to excellent properties.However,the hard ceramic particles as the reinforcement phase bring challenges to machining.To study the effect of in-situ TiB_(2)particles on machinability and surface integrity of TiB_(2)/2024 composite and TiB_(2)/7075 composite,milling experiments were performed,and compared with conventional 2024 and 7075 aluminum alloys.In-situ TiB_(2)particles clustered at the grain boundaries and dispersed inside the matrix alloy grains hinder the dislocation movement of the matrix alloy.Therefore,the milling force and temperature of the composites are higher than those of the aluminum alloys due to the increase of the strength and the decrease of the plasticity.In the milling of composites,abrasive wear is the main wear form of carbide tools,due to the scratching of hard nano-TiB_(2)particles.The composites containing in-situ TiB_(2)particles have machining defects such as smearing,micro-scratches,micro-pits and tail on the machined surface.However,in-situ TiB_(2)particles impede the plastic deformation of the composites,which greatly reduces cutting edge marks on the machined surface.Therefore,under the same milling parameters,the surface roughness of TiB_(2)/2024 composite and TiB_(2)/7075 composite is much less than that of2024 and 7075 aluminum alloy respectively.Under the milling conditions of this experiment,the machined subsurface has no metamorphic layer,and the microhardness of the machined surface is almost the same as that of the material.Besides,compared with 2024 and 7075 aluminum alloy,machined surfaces of TiB_(2)/2024 composite and TiB_(2)/7075 composite both show tensile residual stress or low magnitude of compressive residual stress.