D2 Steel Research Articles

Friction Stir Welding of Dissimilar Materials with Reinforcement of Copper Particulates

In this study, the controlled input parameters namely welding speed and spindle speed were optimized by Taguchi method for reinforcement of copper particulates in aluminium alloy (AA6061-AA6063-T6). High carbon and high chromium steel i.e. tool steel D2 type material is used as a friction stir welding tool. Subsequently, the effects of the process parameters were investigated. The signal-to-noise ratios and analysis of variance were applied for statistical analysis. The outcome shows welding speed is the significant parameter than spindle speed. Under the optimum process parameters, 1400 rpm with 16 mm/min were shown best values such as 61.60 MPa for ultimate tensile strength and 91 hardness values. It means moderate spindle speed and lower welding speed develop higher heat. Subsequently, it is also shown that the feasibility of signal-to-noise ratio is responsible to improve welding quality after reinforcement.

An investigation on machinability of AISI D2 steel during hard milling with multi-resolution analysis of vibration

Vibration is a major concern in hard milling process as it adversely affects productivity, surface finish, tool wear, energy consumption, etc. The aim of this paper is to investigate the effects of cutting parameters on acceleration of vibration, acoustic pressure, surface finish, and tool flank wear in face milling of AISI D2 steel. Each cutting parameter was varied in four levels while keeping the maximum value of the other two parameters as constant. Wavelet transform was used to decompose the signals of vibration. Acceleration of vibration has been found to rise with increasing cutting speed in the range of 100 to 180 m min−1. In general, acoustic pressure was found to increase with increasing depth of cut and cutting speed. The results showed that increasing cutting speed leads to reduction in surface roughness while feed rate and cutting depth have opposite effects. It was revealed that while flank wear increases with increasing depth of cut and feed rate, it reduces when cutting speed is raised in the range of 100 to 180 m min−1.

Minimizing Tool Wear, Cutting Temperature and Surface Roughness in the Intermittent Turning of AISI D3 Steel Using the DF and GRA Method

Intermittent turning (IT) is characterized by a different context than continuous turning (CT). The cutting tool is shocked each time it goes off-load and engages a new surface. This interruption causes severe cutting conditions, which fatally affect the performance parameters. The purpose of this study is to assess the effects of four cutting factors, tool nose radius (r), cutting speed (Vc), feed rate (f), and depth of cut (ap), on the following output performance parameters: surface roughness (Ra), cutting temperature (T°), and cutting tool wear (VB) during turning (IT) AISI D3 cold work tool steel. A triple CVD (AI2O3/TiC/TiCN)-coated carbide cutting tool was used. A Taguchi L9 (3^4) experimental design was adopted for carrying out the experiments in intermittent turning. To improve the performance parameters based on three (3) highly particular scenarios that fulfill industrial criteria, the desirability function (DF) and the grey relational analysis method (GRA) were used. Finally, the optimization findings of the two strategies were compared in order to evaluate the performance of each method.

Einfluss fertigungsbedingter Effekte auf das tribologische Verhalten im ADAM-Verfahren gedruckter Bauteile

Additive manufacturing processes have become increasingly important in recent years. However, the use of additive manufactured components in tribological applications – especially for metallic components – has still been little investigated. This work analyzes the extent to which components printed with the Atomic Diffusion Additive Manufacturing (ADAM) process are suitable for use in tribomechanical systems. The focus is on the tribological behavior of the tool steel D2 against 100Cr6 counterparts under lubrication with deep drawing oil, taking direction-dependent manufacturing effects into account. The first tribological investigations with the ADAM process show great optimization potential for possible applications in the field of forming technology. The surface treatment of the samples has proven to be mandatory in the investigations.

Parametric optimization and wear analysis of AISI D2 steel components

AISI D2 steel is widely used for forming die or cold stamping, chipper knives, shear blade, trimming cutter threading dies, punches and stamping tools etc. Hence, the current investigation aim is to determine the effects of sliding parameters on the wear performance of AISI D2 steel. The experiments were conducted on AISI D2 steel pin and disk of mild steel using the pin-on-disk apparatus. After that, relationships for forecasting weight loss of pins due to rubbing action have been developed using the design of experiment (DOE), which is based on response surface methodology (RSM) and has three independent parameters (slide duration, normal load, and sliding speed). ANOVA was used to perform the model adequacy tests, and the results of various parameters were computed and displayed in 3D surface graphs and contour plots. To reduce the weight loss, numerical optimization has been done while keeping all of the input parameters within range (wear volume). The manufacturing sector that uses AISI D2 steel for deforming dies would benefit from the study's findings.

Effect of Al content on the low-stress abrasive wear behaviour of Fe-18Mn-xAl-0.7C alloys

The low-stress ASTM-G65 abrasive wear behaviour was studied in a system of high manganese steels Fe-18Mn-xAl-0.7C with aluminium contents of 0%, 3%, 6% and 9.5% by weight and the results were compared with those of AISI D2 and AISI 9260 steels. By a completely randomized design (CRD), it was determined that the highest wear resistance corresponds to AISI D2 steel, followed by Fe18Mn0Al, Fe18Mn3Al, Fe18Mn9Al, Fe18Mn6Al and AISI 9260 steel. Using micro hardness tests, surface analysis and staking fault energy calculations it was possible to establish a relationship between wear resistance and the strain hardening mechanisms such as transformation induced plasticity (TRIP), twinning induced plasticity (TWIP) and microband induced plasticity (MBIP) for the Fe-Mn-Al-C steels under study.

Influence of nano-minimum quantity lubrication with MoS2 and CuO nanoparticles on cutting forces and surface roughness during grinding of AISI D2 steel

Environmental side effects of machining lubricants are the main reasons for the progressive development of utilizing the minimum quantity lubrication (MQL) method instead of conventional methods. Owing to the high specific energy of cutting and generation of more heat in grinding, the MQL technique has a lower efficiency than conventional methods. However, by adding nanoparticles to the base oil, the lubrication efficiency in grinding can be enhanced. In this research, grinding of cold work tool steel AISI D2 was studied using a MQL technique by adding MoS2 and CuO nanoparticles to two types of vegetable-based oils: colza and soybean with different concentration percentages, and their effects were examined on the cutting forces (normal and tangential forces) and surface roughness. The results indicated that the values of normal force and tangential forces diminished by 19 and 35 % when using CuO nano powder in soybean base oil with a concentration of 4 % and MoS2 nano powder in soybean base oil with a concentration of 2 %, respectively. Furthermore, when using CuO nano powder in colza base oil and with a concentration of 2 %, the surface roughness had a significant reduction of 77 % in comparison with pure oil as a grinding fluid.

Effect of Pre-treatment and Duration of Pulse Plasma Nitriding on Duplex Plasma Treatment by Physical Vapor Deposition of TiN on AISI D2 Steel

Effect of Pre-treatment and Duration of Pulse Plasma Nitriding on Duplex Plasma Treatment by Physical Vapor Deposition of TiN on AISI D2 Steel

Experimental investigation of the low-temperature oil-on-water cooling and lubrication in turning the hardened AISI D2 steel

In this paper, the influence of the cutting speed, feed, and the depth of cut on the cutting force, surface roughness, cutting temperature, and tool wear were experimentally investigated under the low-temperature oil-on-water (LTOoW) cooling and lubrication condition in turning the hardened tool steel AISI D2 (60 ± 1HRC) with the PCBN cutting tool. The results showed that the three-component cutting forces are FY > FZ > FX. The influence of the cutting speed on the cutting temperature is slightly more visible compared to the feed and depth of cut. In this experiment, a satisfactory surface roughness value of 0.54 µm can be obtained, gaining the effect of the turning instead of the grinding. The flank wear values of the PCBN tool are 142 µm and 148 µm at the cutting speeds of 55 and 140 m/min, respectively; however, the flank wear abruptly increases to 668 µm at a 495 m/min, which has a very serious impact on the tool life. The abrasive wear is considered to be a predominant wear mechanism on the flank wear of the PCBN tool. The rake face is dominated by crater wear due to the high temperature, high pressure, high stress, and high friction at the chip-tool interface. Compared with dry hard turning (DHT) condition, the lower surface roughness value, lower cutting temperature, and longer tool life can be obtained at LTOoW.

Hard Turning Performance Investigation of AISI D2 Steel under a Dual Nozzle MQL Environment

In recent years, hard turning has emerged as a burgeoning cutting technology for producing high-quality finishing of cylindrical-shaped hardened steel for a variety of industrial applications. Hard turning under dry cutting was not accepted because of the generation of higher cutting temperatures which accelerated tool wear and produced an inferior surface finish. Nowadays, minimum quantity lubrication (MQL) is widely accepted in hard turning to reduce the problems encountered in dry cutting. This research aimed to augment the MQL performance in the hard turning process of AISI D2 steel by applying a novel concept, namely, a dual jet nozzle MQL system that supplies the cutting fluid into the cutting zone from two different directions. The performances of hard turning are discussed using machinability indicator parameters, such as surface roughness, tool wear, cutting temperature, power consumption, noise emission, and chip morphology. The dual nozzle MQL greatly reduced the friction between contact surfaces in the cutting zone and provided improved surface quality (Ra = 0.448 to 1.265 µm). Furthermore, tool flank wear was found to be lower, in the range of 0.041 to 0.112 mm, with abrasion and adhesion being observed to be the main mode of wear mechanisms. The power consumption was greatly influenced by the depth of cut (46.69%), followed by cutting speed (40.76%) and feed (9.70%). The chip shapes were found to be helical, ribbon, and spiral c type, while the colors were a metallic, light blue, deep blue, and light golden.

Environmental sustainability during machining of hardened steel using nanofluid: A case study

The positive effects of nanofluid-assisted minimum quantity lubrication include improved performance during machining and environmental sustainability. In the present study two cutting parameters levels such as feed rate of 0.05 (mm/rev)- depth of cut of 0.1(mm)-cutting speed of 80(m/min) and feed rate of 0.15(mm/rev)-depth of cut of 0.3(mm)-cutting speed of 200(m/min) has been used in the hard turning of D2 steel. It was determined that the 0.3% ZrO2 wt% observed to be improved machinability as compared to dry and Minimum Quantity Lubrication (MQL) environment. Finally, the sustainability assessment through the Pugh Matrix Assessment (PMA) presented the potential of nanofluid-MQL for improvement of machinability of hardened D2 steel for cleaner production.

Optimization of process parameters of EDM used to machine D2-die steel

The present study deals with investigating an optimized set of parameters of electric discharge machining which was used on D-2 die steel. The brass tool was taken in the study. D2 steel is used to make dies and tools as it contains considerable amount of compressive strength and hardness. In this work, current, pulse on time and pulse off time were considered as input parameters. The effects of these input parameters were observed on surface roughness of the workpiece. The experimental layout was formulated by Taguchi method and the effect of input parameters on output characteristic, here Surface Roughness, was analysed by ANOVA technique.

Comparison of structural and wear properties of AlSi(N-O) films

The aim of this study was to produce the AlSiN and AlSiO films using sputtering technique and investigate their structural, mechanical and tribological properties comparatively. Coatings were deposited on AISI D2 steel substrates by using 5%, 10% and 15% nitrogen and oxygen gas ratios. The coatings were amorphous when they were first produced, and then heat treatment at 550°C was applied to obtain a crystalline structure. In order to determine the structural, mechanical and tribological properties of the films, XRD, SEM, EDS, knoop microhardness test, 3D profilometer and pin-on-disc wear tests were performed respectively. It has been determined that the gas flow rates had a significant effect on the properties of the AlSiN and AlSiO coatings. It has also been determined that all the coatings had a very dense and columnar structure, and that the thickness values varied according to the nitrogen and oxygen gas flow rates. The hardness values of the oxide films were higher than the nitrogen films. The highest hardness value was 595 HK and the lowest friction coefficient was 0.47. In addition, the lowest wear rate was obtained at 10% nitrogen gas flow ratio. It has been observed that the tribiological properties of the oxide films were very close to nitride films.

Automatic Method for Vickers Hardness Estimation by Image Processing.

Hardness is one of the most important mechanical properties of materials, since it is used to estimate their quality and to determine their suitability for a particular application. One method of determining quality is the Vickers hardness test, in which the resistance to plastic deformation at the surface of the material is measured after applying force with an indenter. The hardness is measured from the sample image, which is a tedious, time-consuming, and prone to human error procedure. Therefore, in this work, a new automatic method based on image processing techniques is proposed, allowing for obtaining results quickly and more accurately even with high irregularities in the indentation mark. For the development and validation of the method, a set of microscopy images of samples indented with applied forces of 5N and 10N on AISI D2 steel with and without quenching, tempering heat treatment and samples coated with titanium niobium nitride (TiNbN) was used. The proposed method was implemented as a plugin of the ImageJ program, allowing for obtaining reproducible Vickers hardness results in an average time of 2.05 seconds with an accuracy of 98.3% and a maximum error of 4.5% with respect to the values obtained manually, used as a golden standard.

Characterizations and Kinetics of Refractory Niobium Carbide Coatings on AISI D3 Steel

Characterizations and Kinetics of Refractory Niobium Carbide Coatings on AISI D3 Steel

Surface Analysis of AISI D2 Steel Treated by Plasma Nitriding and Niobium and Vanadium Nitride Films by Cathodic Cage Plasma Deposition

Surface Analysis of AISI D2 Steel Treated by Plasma Nitriding and Niobium and Vanadium Nitride Films by Cathodic Cage Plasma Deposition

An in-depth analysis of tool wear mechanisms and surface integrity during high-speed hard turning of AISI D2 steel via novel inserts

Over the years, machinists have been exploring the hard part turning of AISI D2 steels. Initially, cylindrical grinding was used for this purpose, but it was later replaced by single-point turning due to its advantages such as high material removal, low cost, and greater flexibility. Conventional inserts are used in single-point turning, but they have been reported to have large radial forces, high notch wear, and poor surface finish. Therefore, multi-radii wiper inserts were designed to overcome these machining issues, but their use was restricted to shallower depths of cut and moderate feed rates because of the thick chips produced by the high entry angle. Prime inserts, on the other hand, were designed with a modest entry angle, making them ideal for evaluating tool wear/life, material removal and surface roughness at greater cutting speeds, depths of cut, and feed rates. It was observed that cutting speed has a significant effect on tool wear/life with a contribution of 55.38% followed by feed rate (13.72%) and depth of cut (11.43%). Cutting speed (84.87%) and feed rate (13.01%) are observed to be the most significant parameters controlling material removed. It was also observed that feed rate has a significant effect on workpiece surface roughness with a contribution of 67.30% followed by depth of cut (20.60%), whereas cutting speed had no significant effect on surface roughness. Moreover, it is found that prime insert outperformed wiper and conventional inserts in terms of tool life/wear and surface roughness.

MACHINE LEARNING-BASED MODELING AND OPTIMIZATION IN HARD TURNING OF AISI D6 STEEL WITH ADVANCED AlTiSiN-COATED CARBIDE INSERTS TO PREDICT SURFACE ROUGHNESS AND OTHER MACHINING CHARACTERISTICS

In recent times, mechanical and production industries are facing increasing challenges related to the shift towards sustainable manufacturing. In this work, the machining was performed in dry cutting condition with the newly developed AlTiSiN-coated carbide inserts coated through scalable pulsed power plasma technique, and a dataset was generated for different machining parameters and output responses. The machining parameters are speed, feed and depth of cut, while the output responses are surface roughness, cutting force, crater wear length, crater wear width and flank wear. Abrasion and adhesion were found to be the two dominant wear mechanisms. With speed, the tool wear was found to increase. Cutting force was found to increase rapidly for higher speed ranges (70, 80 and 90[Formula: see text]m/min). But reduction of cutting force was observed in both low and medium ranges of cutting speed (40, 50, 55 and 60[Formula: see text]m/min). With higher values of feed and depth of cut, higher cutting force was also noticed. With the variation of depth of cut, the machined surface morphology and machined surface roughness were found to deteriorate. With higher feed and depth of cut values, more surface damages were observed compared to low values of feed and depth of cut. Both the feed rate and tool–chip contact length contributed significantly to the formation of crater on the tool rake surface. At high speed, continuous chips were observed. Both chip sliding and sticking were observed on the tool rake face. The data collected from the machining operation was used for the development of machine learning (ML)-based surrogate models to test, evaluate and optimize various input machining parameters. Different ML approaches such as polynomial regression (PR), random forests (RF) regression, gradient boosted (GB) trees and adaptive boosting (AB)-based regression were used to model different output responses in the hard machining of AISI D6 steel. Out of the four ML methodologies, RF and PR performed better in comparison to the other two algorithms in terms of the [Formula: see text] values of predictions. The surrogate models for different output responses were used to prepare a complex objective function for the germinal center algorithm-based optimization of the machining parameters of the hard turning operation.

Fatigue behaviour of laser shock peened AISI D2 tool steel

Laser shock peening (LSP) is an advanced surface enhancement technique capable of imparting beneficial compressive residual stresses, thereby improving metal parts’ fatigue resistance and crack propagation resistance. This study presents the fatigue behaviour of AISI D2 tool steel samples subjected to LSP with a power density of 15 GW/cm2 and a double laser scanning sequence. The effect of LSP on quasi-static tensile properties was also addressed. The fatigue crack propagation was suppressed in LSP-treated samples when tested at ΔK = 10 MPam. The fatigue strength of treated samples was 32.9% higher compared to untreated samples. The LSP-treated samples have shown a larger fatigue fracture surface area than the as-received (AR) sample. In addition, the tendency to form secondary cracks in the fatigue fracture paths decreased due to LSP treatment. LSP treatment can effectively improve the fatigue resistance and crack propagation behaviour of AISI D2 steel. These improvements are due to significant compressive residual stresses in a superficial layer of the material. The present study provides a reference for improving the mechanical properties of AISI D2 steel by laser shock peening.

Hard turning of AISI D2 steel with cubic boron nitride cutting inserts

Industries use heat treated steel for various components due to its strength and other mechanical properties. Usually hardening of machining is carried out by energy and cost intensive grinding process. Recently, hard machining has replaced grinding for certain specific applications. In this study, Cubic boron nitride (CBN) of specification CNMG120408is employed to machine AISI D2 steel of 46 HRC hardness. Nine machining experiments established by L9 orthogonal array were conducted. Surface roughness and cutting force were taken as response variables. From the signal to noise ratio analysis, the optimum combination of cutting process parameters for surface roughness is found out to be 80 m/min (Cutting speed) 0.109 mm/rev (Feed) and 0.1 mm (depth of cut). From Analysis of variance (ANOVA), the share made by every process parameter on the machining performance is found out for this CBN tool-work piece combination. Feed rate has the maximum contribution (56 %) for main cutting force while Cutting speed has the maximum contribution (72 %) for surface roughness. Cutting speed exerts greater influence on surface finish compared to feed rate in hard machining.