Steel EN Research Articles

Effect of the Heat-Treatment Process on the Mechanical and Microstructure Properties of EN8 Steel

EN-9 is one of the steel grades, and it is widely used in power plants, automobiles, and the aerospace sector. The availability and ductility of EN9 steel have been limited. Heat-treatment procedures are used to increase the hardness, wear resistance, and percentage of elongation. The main intention of this study is to discover the effect of heat treatment on EN8 steel. In this work, the various kinds of heat-treatment methods like annealing, normalizing, hardening, and tempering were carried out on EN-8 steel. Mechanical properties like hardness, tensile strength, and percentage of elongation are evaluated. The microstructure is examined and compared, before and after the heat treatment process. Hardening and tempering results indicated that EN8 steel has better hardness, yield strength, ultimate tensile strength and elongation when compared to EN9 steel.

Fatigue crack behaviour of composite- and mono-coated marine structural components

ABSTRACT In this study, experimental and numerical studies of fatigue crack growth (FCG) mechanisms in coated and uncoated structural components of EN8 steel (EN8) and aluminium alloy 6063 (AA6063) samples were compared. Electroplating (EP) (of nickel (Ni) and chromium (Cr)) and physical vapour deposition technique (PVD) (of aluminium nitride (Al-N) and nanocrystalline layers of titanium aluminium nitride (Ti-Al-N)) methods were used for mono and composite metallic coatings of EN8 and AA6063. The present study focuses on the implications of the coating-substrate interface during FCG initiation and propagation by considering the loading-bearing ability of the coating. Fatigue cracking mechanism depends on coating fracture toughness (FT) at the interface of mono-composite coating and its thickness. In comparison, composite-coated PVD samples proved better than mono-coated electroplated samples due to the delayed plastic deformation process on the surface of the substrate sample.

Effect of Temperature and Sliding Velocity on the Dry Sliding Wear Mechanisms of Boron Modified Ti-6Al-4V Alloys

The dry sliding wear behavior of as-cast pristine and boron-modified Ti-6Al-4V (Ti64) alloys (having 0.3 and 0.55 wt% B) is investigated using pin-on-disc experiments with the pin being Ti64 alloy and the EN31 steel disc. Experiments are performed at sliding speeds (s) of 1, 2, and 4 m/s and temperatures 300 and 573 K. A mixed response in wear behavior is observed. At the lowest sliding speed, all three alloys (except 0.55B alloy at 300 K) exhibit similar wear rates, with abrasive wear being the dominant wear mechanism. At 2 m/s, temperature and s increase, and adhesive wear takes over along with delamination wear. Here, the 0.55B sample shows the highest wear rate due to the debonding of more TiB particles, which increases three body abrasion wear. With further increase in s to 4 m/s, delamination and oxidation wear are observed for all the samples. XRD evaluation shows traces of TiO2 and Fe2O3, which imply the formation of MML in samples tested at s = 4 m/s, which is also validated through subsurface microstructure analysis. It is found that MML having more TiB particles has more stability, because of which 0.3B samples show higher wear rate.

A Supervised Machine Learning Model for Tool Condition Monitoring in Smart Manufacturing

In the current industry 4.0 scenario, good quality cutting tools result in a good surface finish, minimum vibrations, low power consumption, and reduction of machining time. Monitoring tool wear plays a crucial role in manufacturing quality components. In addition to tool monitoring, wear prediction assists the manufacturing systems in making tool-changing decisions. This paper introduces an industrial use case supervised machine learning model to predict the turning tool wear. Cutting forces, the surface roughness of a specimen, and flank wear of tool insert are measured for corresponding spindle speed, feed rate, and depth of cut. Those turning test datasets are applied in machine learning for tool wear predictions. The test was conducted using SNMG TiN Coated Silicon Carbide tool insert in turning of EN8 steel specimen. The dataset of cutting forces, surface finish, and flank wear is extracted from 200 turning tests with varied spindle speed, feed rate, and depth of cut. Random forest regression, Support vector regression, K Nearest Neighbour regression machine learning algorithms are used to predict the tool wear. R squared, the technique shows the random forest machine learning model predicts the tool wear of 91.82% of accuracy validated with the experimental trials. The experimental results exhibit flank wear is mainly influenced by the feed rate followed by the spindle speed and depth of cut. The reduction of flank wear with a lower feed rate can be achieved with a good surface finish of the workpiece. The proposed model may be helpful in tool wear prediction and making tool-changing decisions, which leads to achieving good quality machined components. Moreover, the machine learning model is adaptable for industry 4.0 and cloud environments for intelligent manufacturing systems.

Study of Tribological Properties of EN8 Steel against Inconel X-750 Alloy under Dry and Lubricated Conditions

Study of Tribological Properties of EN8 Steel against Inconel X-750 Alloy under Dry and Lubricated Conditions

Wear and Microstructural Characteristics of Colmonoy-4 and Stellite-6 Additive Layer Deposits on En19 Steel by Laser Cladding

Wear and Microstructural Characteristics of Colmonoy-4 and Stellite-6 Additive Layer Deposits on En19 Steel by Laser Cladding

Experimental and Analytical Investigation into Cutting Forces during Turning of EN-31 Steel in Different Machining Conditions

Metal cutting is the way of processing the workpiece with tool having sharp cutting edges of different materials generating chips of different shapes and sizes. In present era of industry 4.0, metal machining should not be unrated during processing of hard grades metals and superalloys where large amount of cutting forces are generated. Also, the measurement of cutting forces provides the basic of economical machining and hence accurate evaluation in experimental and analytical manner has great importance. The traditional models of metal cutting have disagreement with experimental results due to missing of important mechanics terms. With the development of digital technology, the errors in calculation of cutting force have also been shortened due to consideration of terms absent in conventional models. In present investigation, the cutting forces have been evaluated experimentally using dynamometer and analytically with Astakhov’s methodology during turning of EN-31 steel. The results revealed that 12.9% observations have deviation more than 20%, whereas 16.67 % has zero deviation. Further, the feed rate has more influence on cutting forces as compared to speed and nose radius. In addition, the minimum quantity lubrication (MQL) of vegetable oil has lowered the cutting forces appreciably compared to dry machining.

Experimental investigation of machining of EN31 Steel in abrasive mixed rotary EDM with graphite and copper electrode

Experimental investigation of machining of EN31 Steel in abrasive mixed rotary EDM with graphite and copper electrode

Near dry turning of EN8 and EN31 steel: multi-objective optimization using grey relational analysis

Steel is the most commonly employed material in various engineering applications, and their successful machining demands finding the optimized set of machining parameters along with appropriate cooling strategies. Moreover, the significance of process parameter optimization is progressively perceived in the wake of expensive CNC machine adaptation on the shop floor for machining. Further, a competent cooling strategy is essential with a minimal amount of coolant to obtain the best quality products. In the present work, the optimization of process parameters for Near Dry Turning (NDT) of two steel grades, EN8 and EN31, was done. NDT utilizes a minimal coolant with a major amount of compressed air. For competent cooling, Al2O3 nanofluid as coolant was used with compressed air. Speed, feed, and depth of cut were taken as the machining parameters for the turning process. Two response variables, the surface roughness of machined specimen and cutting zone temperature, were considered for the analysis. Three levels of each turning parameter were chosen, and the Taguchi L9 orthogonal array was adopted for the experimentation. The optimized turning parameter was found through the Grey Relational Analysis (GRA). Further, the applicability of compressed air was also presented to achieve sustainable and green machining to eliminate the negative impact on environmental footprints. For this purpose, results at the obtained optimized set of parameters were compared with plain base fluid and compressed dry air as coolants. The reduction in surface roughness of ∼12.3% and ∼14.6% for EN8 and EN31 steel were observed using nanofluid in near dry turning. Similarly, the reduction in cutting zone temperature was ∼7% in both cases. These results show the significance of process parameter optimization and the applicability of nanofluid in near dry turning of steels.

Role of Friction Time on the Joint Characteristics of Continuous Drive Friction-Welded Inconel 718 and EN24 Steel

Role of Friction Time on the Joint Characteristics of Continuous Drive Friction-Welded Inconel 718 and EN24 Steel

High Speed Grinding of EN31 Steel with Alumina Nanofluid Coolant

Grinding is a choice for obtaining high surface quality and closer dimensional tolerance. For meeting this objective economically, the material removal rate (MRR) must be sacrificed to certain extent. The MRR could be increased by either increase in wheel speed, depth of cut, and feed rate. An increase in MRR increases the surface temperature leading to thermal defects on surfaces. Improving the MRR without compromising the surface quality is a challenging objective. Many investigations are progressing for machining various materials under different cooling environments to meet such challenges. This experimental novel aim is to investigate the performance of Al2O3 nanofluid in high-speed grinding of EN31 steel under flood cooling method for reduction of surface roughness and cutting zone temperature. Taguchi’s full factorial design was employed for experimental investigation. The factors such as feed, depth of cut and cutting fluid environment were considered for analysing the responses of cutting zone temperature and surface roughness. The thermal analysis on the work piece was carried out with experimental values by the finite element analysis method. The nanofluids outperform in terms of reduction of surface roughness and downsizing cutting zone temperature. The proposed nanofluid-based grinding significantly reduced the surface roughness and cutting zone temperature.

Prediction of surface roughness in turning using vibration features selected by largest Lyapunov exponent based ICEEMDAN decomposition

The prediction of surface roughness during turning using indirect methods helps improve the quality of production. This study proposes an intelligent surface roughness prediction scheme during turning of forged EN8 steel using ELM. The training and testing datasets are developed using Taguchi L25 and L8 orthogonal arrays respectively. The vibration signal acquired from machining is decomposed into modes using ICEEMDAN, followed by selection of the sensitive mode using LLE. Cutting parameters have been combined with features of the sensitive mode to form the feature matrix. Z-score normalization is used to normalize the matrix which is fed to ELM for surface roughness prediction. The SMA is used to optimize the kernel parameters of the ELM. The results obtained using arbitrary kernel parmeters have been compared with the optimized model. The mean absolute percentage error obtained using the proposed model is 4.957% representing better accuracy than the unoptimized results.

Comparative study on machining performance of TiAlSiN, AlTiN/TiAlSiN-coated cutting tools

ABSTRACT The present study investigates the microstructure of monolayer TiAlSiN and bilayer AlTiN/TiAlSiN coatings deposited on WC-Co inserts through magnetron sputtering. Further, a comparative study on the tool life and wear characteristics of uncoated, monolayer and bilayer coated inserts was performed through dry turning of tempered EN-8 steel under extreme cutting conditions. The TiAlSiN coating showed a dense fine morphology whereas the AlTiN/TiAlSiN coating showed a mixed morphology with a columnar structure for the intermediate layer of AlTiN followed by a dense nanocrystalline structure for the top layer of TiAlSiN. The dry turning experiments show that the major form of wear mechanism observed during machining was crater wear. Both monolayer and bilayer coated inserts showed promising cutting performance and the bilayer coated inserts showed better tool life than the monolayer coated inserts under most of the cutting conditions.

Influence of Different Heat Treatment Temperatures on the Microstructure and Corrosion Behaviour of Dual-Phase EN8 Steel in 0.5 M Sulphuric Acid Solution

Dual-phase steels provide an excellent combination of strength and ductility, as well as improved energy absorption and anti-corrosion protection properties. This research aims at evaluating the microstructure and corrosion behaviour of EN8 steel under different heat treatment temperatures in 0.5 M sulphuric acid solution (H2SO4) using the EIS, potentiodynamic polarization, and gravimetric method (weight-loss method). Austenitizing is performed at 973 K, 1023 K, 1063 K, and 1173 K for 2 h followed by quenching in water to form a ferrite–martensite (F–M) dual-phase structure. From the results, it is seen that the corrosion rate increased with different heat treatment conditions depending on the change in the phase when immersed in 0.5 M H2SO4 at the temperature of 303 K, 313 K, 323 K, and 333 K. This work investigates the energy of activation, enthalpy, and entropy of activation. For dual-phase steel containing ferrite and martensite, the corrosion behaviour depends on the amount of martensite and ferrite. As the austenitization temperature increases from 1023 to 1173 K, the amount of martensite increases. This is reflected in the increase of micro galvanic corrosion cells in the region between the ferrite and martensite phases, which acts as active corrosion centres. The normalized specimen showed greater corrosion resistance compared to the water-quenched specimen at 1173 K. This is due to the presence of lower carbon content for normalized dual-phase steel containing ferrite–pearlite phase than the ferrite–martensite phase present in specimen austenitized at 1173 K. Surface characterization and XRD confirmed the corrosion behaviour of the specimens under investigation.

Investigation on mechanical properties of ZTA+ Cr3C2 + Ni reinforced EN31 steel-based composite material: Micromechanical finite-element analysis

The present investigation deals with the development of EN31 steel-based metal matrix composite material under the ultrasonic vibration effect by providing 20 kHz frequency. In the process of the development of composite material, primary and secondary reinforcement has been taken as zirconia toughened alumina (ZTA) and Cr3C2 (chromium (II) carbide), respectively. The Ni has also been taken as dissolving reinforcement material and its weight percentage (wt.%) is kept constant at 2.5%. The variation in ZTA weight percentage was selected between 1.25% and 10%. Furthermore, the weight percentage of Cr3C2 has been kept constant (2.5 wt.%) throughout the development of different composite samples. The microstructural investigation indicated the fair distribution of reinforcement particles up to the 3.75 wt.% of ZTA, developed with the ultrasonic vibration effect. Furthermore, the addition of 2.5 wt.% of nickel in the EN31 steel has improved the wettability of ZTA and Cr3C2 particles. The best values of hardness (254.22 BHN) and tensile strength (892.15 MPa) were achieved with the composition of EN31/3.75 wt.% ZTA/2.5 wt.% Cr3C2/2.5 wt.% Ni composite material sample. Furthermore, the tensile strength and hardness of EN31 steel matrix material were improved by about 45.065% and 100.36% respectively. The addition of ZTA and Cr3C2 decreases the ductility of EN31 steel matrix material. The addition of 2.5wt.% Ni powder with ZTA+ Cr3C2 improved the ductility of EN31 steel. The results revealed that the mechanical properties (tensile strength, hardness, and ductility) of the developed composite material were further improved after performing the heat treatment process. Furthermore, an approach has been made to investigate the micro-mechanical deformation of EN31/3.75 wt.% ZTA/2.5 wt.% Cr3C2 metal matrix composite representative volume element (size: 225 × 225 × 225 nm) with finite-element analysis (FEA). The maximum stress (895.60 MPa) is generated at matrix–particle interfaces, which is the main reason for failure. The percentage difference between FEA and experimental results was less than 10%.

An Experimental Analysis of Grinding Parameters and Conditions on Surface Roughness of Finished Product

Higher grade or smooth surface finish mechanical components and mating parts with close limits and tolerances is one of the most important requirement of modern manufacturing industry. Grinding is the most dominating process among various manufacturing finish processes over final products that require in-depth investigation on how material removal processes influence the surface roughness of the finished products. In this work, an experimental analysis was carried out to evaluate the influence of various machining parameters and conditions on surface roughness of the final substrates. The main objective of this experimental work is to study the comparison of the effects of tools and conditions which are abrasive nature between Mild Steel (MS) and EN24 steel surface by using Depth of Cut (DOC).

Precipitation of Fine Carbides, Transformation of the Retained Austenite and Corrosion Properties on EN-31 Steel by Cryogenic Treatment Process

Investigate of precipitation carbides transformation of the retained austenite and corrosion properties on EN-31 steel by cryogenic treatment method. In this work to identify the percentage of retained austenite and corrosion rate, was presented on EN 31 bearing steel by which cryogenic treatment process. Further, the hardness values of CHT and DCT were compared by using the microstructure view of the CHT and DCT samples. The optimized cryotreated samples were prepared for metallographic examination as per ASTM E3-01. Then the specimen was subjected to factor level setting like cooling rate, soaking period, soaking temperature and tempering temperature at various conditions. Moreover, the precipitation of fine carbides and the transformation of retained austenite to martensite showed considerable variations in the hardness of the optimized DCT samples compared to the CHT samples. The mean hardness value of this sample is 861HV and 19.20%, 847HV and 17.25%, 838HV and 17.10%, 857HV and 18.40%, 790HV and 13.45% improvement in the hardness compared to CHT.

Grey Relational Analysis and Principal Component Analysis based optimization of process parameters in turning of EN-8 Steel

The present work investigates the optimum machining parameters while turning EN 8 steel by employing hybrid Grey relational analysis (GRA) and principal component analysis (PCA) techniques. Experiments were designed based on the central composite design (CCD) of the Response surface method (RSM). Experiments were conducted by varying machining parameters such as cutting speed, feed, and depth of cut. In this study, the surface roughness and the material removal rate (MRR) are measured during the experimentation. To determine the influence of cutting parameters, an Analysis of variance (ANOVA) was deployed. The optimal turning parameters are found to be speed 1170 rpm, feed 0.225 mm/rev, and depth of cut 1.238 mm. The results revealed that the optimization through hybrid GRA-PCA enhanced the output quality characteristics.

Multi-response optimization in turning of EN-24 steel under MQL

Cutting fluids used in manufacturing industry have environmental and economic drawbacks. In order to reduce the negative effects associated with cutting the fluids, it is now becoming indispensable to move towards more sustainable techniques. In this research work, the turning of EN-24 steel under minimum quantity lubrication (MQL) environment have been done. The study has been completed three phases. The first phase deals with planning of experiments based on Box-Behnken design. The influence of input process parameters i.e., cutting speed, feed rate, depth of cut and MQL flow rate have been investigated on output parameters i.e., surface roughness, tool wear, cutting temperature and cutting force. The desirability approach strategy has been used for multi-response optimizationof input parameters in the second phase.The third step deals with analysis of results using SEM, 3D surface graphs and main effect graphs. The confirmation experiments have been carried out to verify the developed model. Experimental results revealed that, the turning performance under high MQL flow rate has been found to be the most effective parameter on mean surface roughness, cutting temperature, tool wear and cutting force.

Influence of initial quenching on the microstructure and mechanical properties of quenched and partitioned ferritic stainless steels

Modern steel industry has great interest in developing new advanced high-strength steels, especially for the automotive industry. The need for stronger and more ductile sheet steels has led to development of novel heat treatments such as quenching and partitioning. The Q&P heat treatment provides an opportunity of manufacturing strong steels without sacrificing their formability. However, there is limited research conducted on the microstructure evolution of many alloys potential for Q&P such as stainless steels.This study evaluates the selection for the optimal quench interruption temperature during Q&P of ferritic stainless steels. The paper compares different simulation models for optimizing the Q&P-process. Q&P was applied to two AISI 420-type stainless steels EN 1.4021 and EN 1.4034 to assess the simulation results. Microstructure analyses with X-ray diffraction and electron microscopy revealed that simulated values overestimate the retained austenite fractions after Q&P due to formation of Cr-rich carbides. Mechanical tests showed that Q&P is applicable to grade EN 1.4021 stainless steel, whereas EN 1.4034 fractured in a brittle manner under tensile load. Electron microscopy revealed intergranular fracture type and concentration of Cr-rich carbides at parent austenite grain boundaries in EN 1.4034. These results suggest that impurities may expose stainless steels to temper embrittlement during partition.