Machining Of Steel Research Articles

A new intelligent approach of surface roughness measurement in sustainable machining of AM-316L stainless steel with deep learning models

Due to the manufacturing sector's digitalization and ability to combine quality measurement and production data, machine learning and deep learning for quality assurance hold enormous potential. In this situation, industries may process data to inform data-driven estimates of product quality, thanks to predictive excellence. This research investigates the machinability of Laser Powder Bed Fusion (LPBF) − 316L stainless steel specimens, focusing on the impact of cutting parameters and cooling conditions (Dry, MQL, CO2 and CO2 + MQL) on surface roughness. The research employs advanced data augmentation techniques, incorporating TransGAN and multi-head attention (MHA) based Alexnet model for surface imperfection classification. The results highlight the effectiveness of the proposed methodology in accurately classifying surface conditions and underscore the superior performance of the MHA-Alexnet algorithm compared to alternative models (Alexnet and AE-Alexnet). Overall, the study contributes valuable insights into optimizing machining parameters and cooling strategies for enhanced surface finish in additively manufactured alloys.

Influence of different wet-blasting pressure on the surface integrity and tool cutting performance of hybrid CVD-TiN/TiCN/α-Al2O3/TiN coated tools

This paper investigates the effect of wet-blasting pressure on the surface integrity and tool cutting performance of hybrid CVD-TiN/TiCN/α-Al2O3/TiN coated tools. The hybrid TiN/MT-TiCN/α-Al2O3/TiN multilayer coating was deposited on the surface of the cemented carbide inserts by chemical vapor deposition (CVD) technique. Then the coated inserts were subjected to wet-blasting by aluminum oxide with varying pressure. The coatings were characterized by scanning electron microscopy, white light surface profiler, and X-ray residual stress diffractometer. The results indicate that the average residual tensile stress of the α-Al2O3 layer on the rake face of CVD-coated inserts gradually decreased with the increase of wet-blasting pressure. When the wet-blasting pressure reached 0.24 MPa, the residual tensile stress was transformed into compressive stress. It was accompanied by increased cutting edge roughness and cutting edge radius, reduced cutting edge coating thickness, and a change in rake face surface roughness. To understand the effect of the surface integrity change on the cutting performance of CVD-coated inserts, a case study designed for AISI 4340 steel machining under continuous and intermittent cutting conditions is performed. When the Al2O3 layer on the cutting edge is not peeled off by wet-blasting, the change of residual stress from tensile to compressive in the rake face of CVD-coated inserts can effectively improve the fracture failure resistance of inserts in continuous and intermittent cutting processes. When the Al2O3 layer on the cutting edge is peeled off by wet-blasting, the fracture failure resistance during intermittent cutting will be significantly reduced.

Characterization and machinability of a high-silicon cast steel with ceramic and carbide tools

Characterization and machinability of a high-silicon cast steel with ceramic and carbide tools

Investigation on the optimal ultra-precision machining of nitriding mold steel by in-situ laser assisted diamond cutting

S136 (STAVAX ESR) mold steel is an advanced material for the optical mold industry. The precisely machined surface quality is essential for guaranteeing the excellent performance of molds. Diamond cutting is a high-efficiency machining technique in optical mold manufacturing. However, the chemical wear of diamond tool is a huge challenge in precisely machining steel mold due to the reaction between atoms C and Fe. In this study, the hybrid machining technique which combined the in-situ laser assisted diamond cutting (LADC) and plasma nitriding was used to machine S136 mold steel. Furthermore, the impact of the various machining conditions on the machined workpiece surface roughness Sa was comprehensively investigated by the Taguchi method (TM) and Response surface methodology (RSM). The experimental results of material characterization indicated that a 90 μm nitride layer was generated on the workpiece surface by plasma nitriding. Analysis of variance (ANOVA) results demonstrated that the feed rate and laser power had an important impact on the machined surface roughness Sa. According to the RSM, a precise mathematical model was developed which is explored by experimental investigations. The results showed that the optimal machining parameter combination by RSM generated the better surface quality of 6.393 nm in in-situ LADC of nitriding steel. This study provides a reference for mold steel ultra-precision machining technique and parameter optimization method for surface integrity.

Vacuum-oxygen-low recycling process of aluminium composites manufactured from steel machining chips

Vacuum-oxygen-low recycling process of aluminium composites manufactured from steel machining chips

Fuzzy logic-based prediction data for the CNC lathe

The research aims to predict the parameters between the cutting speed range correlated to the depth of cut for the CNC lathe.The model predicts the cutting speed parameters carried out based on the data range between the depth of the cut and the cutting speed. That information has been derived from the machine tool handbook and expert engineer recommendations. The fuzzy logic-based methods were used to predict cutting speed parameters for three different materials: aluminium, machine steel, and stainless steel. The data range in each material was used to condition the membership function.The result shows that the prediction cutting speed parameters are related to the range of the depth of the cut between 0.15 and 0.4 mm. It is observed that if the depth of the cut is very high, the cutting speed is lower. The information obtained is slightly different from the machine tool handbook. It can be used with the feed rate parameters to perform the machining process of the CNC lathes in the smart factory.Further research should focus on predicting surface roughness and tool wear in the turning.The cutting speed selection has a significant impact on manufacturing. It affects production time, tool wear, cost, etc. Generally, the parameter has been derived from machining handbooks or machine tools textbooks, and some data is vague because it has only maximum and minimum. The data between ranges is unclear for operation. Executing production planning for new engineers was hard, which can affect manufacturing systems. Therefore, proper and precise cutting parameters are required.General machine tool manuals often provide vague information on recommended parameters and only show the maximum and minimum values. In past research, it has only a determined parameters range for the experiment. The data between ranges is unclear for operation. In this research, the parameter prediction was performed between the cutting speed range related to the cutting depth, which is for use in the CNC lathe process.

Experimental investigation on the surface quality of WEDM machined 20MnCr5 steel for gear application

This experimental study investigates the Wire-cut Electrical Discharge Machining (WEDM) of 20MnCr5 steel, a low alloy steel grade material which is intended for the production of gears, shafts and other parts which need high surface hardness and wear resistance. WEDM is a crucial manufacturing process for producing gears, shafts, spindles, and various mechanical components. The investigation focuses on three key performance parameters: profile error, material removal rate (MRR), and surface roughness (SR), employing five WEDM parameters—wire feed (Wf), wire tension (Wt), servo voltage (SV), discharge arc-off time (Toff), and arc-on time (Ton) - by employing the Taguchi L27 orthogonal array. The study reveals that, in comparison to arc-on time and servo voltage, wire feed rate and tension have a lesser impact. Higher arc-on time and servo voltage result in increased profile error, while reduced wire tension values elevate surface roughness. Recast layer formation has been explored under different WEDM input parameters, revealing its dependence on arc-on time, voltage, wire tension, and feed rate. Higher voltage leads to uneven surfaces with larger globules and deep craters, contributing to a thicker recast layer at higher arc-on time and servo voltage.

Tool wear analysis in AISI 52100 steel machining with sustainable approach

ABSTRACT Manufacturing industries work towards the development of low toxic, eco-friendly, and sustainable alternatives to save the ecosystem from the harmful effects of traditional cutting fluids used for machining from long decades. The utilization of solid lubricants in machining is an advance alternative aimed at regulating the temperature in the machining zone without causing environmental pollution. The present study illustrates the machining performance of AISI 52100 steel employing solid lubricant-assisted machining (SLAM). The study evaluates the machining performance of SLAM with respect to cutting forces, vibration acceleration, tool wear, chip morphology, and surface roughness against dry machining (DM). The experimental findings indicate that utilizing SLAM leads to a notable decrease in cutting forces, ranging between 45% to 60%, a reduction in vibration acceleration by 14% to 29%, a decrease in tool wear by 11% to 17%, and a substantial improvement in surface finish ranging from 47% to 66% compared to DM.

Machinability of steels used for drinking water installation fittings

Machinability of steels used for drinking water installation fittings

Enhanced steel machining performance using texture-controlled CVD alpha-alumina coatings: Fundamental degradation mechanisms

Cemented carbide inserts coated with CVD α-alumina, particularly those exhibiting a (0001) texture, have proven highly effective in steel turning. Despite the established superior performance of (0001) textured alumina coatings, the underlying reasons remain unclear. This study explores the influence of the crystallographic texture of alumina on wear mechanisms in various chip-tool contact zones on the insert rake face. The objective is to establish a fundamental understanding of the active degradation mechanisms and machining performance by relating coating texture to the orientation and deformation of individual Al2O3 grains. Two multilayered coatings, Al2O3 on Ti(C,N), featuring (0001)- and (112‾0)-textured CVD α-alumina, were assessed in dry turning of a bearing steel. The wear rate of the (112‾0) coating was double that of the (0001) coating. Worn coatings exhibit nano-terrace formation at the insert edge, likely due to chemical etching. In the sticking zone, plastic deformation leads to larger facets for grains oriented with the chip flow direction, while rounded surfaces result if this condition is not met. In the transition zone, both (0001) and (112‾0) textured coatings undergo increased plastic deformation accompanied by sub-surface dislocations. (0001) texture deforms more by basal slip creating a wavy coating pattern with steps present at larger misalignments of the lattice planes in neighboring grains while (112‾0) texture deforms by several slip systems creating elongated ridges and ruptured-like areas resulting in rougher surface. This difference in surface morphology is then inherited by the abrasion of submicron coating fragments embedded in the chip (more in (112‾0) texture) in the sliding zone resulting in an even rougher surface. Chemical reaction with the hot chip may also contribute to wear acting as an additional mechanism. This fundamental understanding contributes to the potential enhancement of steel machining using texture-controlled CVD alumina coatings, ultimately improving coated cutting tool performance.

Implementation of Grey Wolf, Multi-Verse and Ant Lion Metaheuristic Algorithms for Optimizing Machinability of Dry CNC Turning of Annealed and Hardened UNIMAX® Tool Steel

Advances in machining technology and materials science impose the identification of optimal settings for process-related parameters to maintain high quality and process efficiency. Given the available resources, manufacturers should determine an advantageous process parameter range for their settings. In this work, the machinability of a special tool steel (UNIMAX® by Uddeholm, Sweden) under dry CNC turning is investigated. The working material is examined under two states; annealed and hardened. As major machinability indicators, main cutting force Fz (N) and mean surface roughness Ra (μm) were selected and studied under different values for the cutting conditions of cutting speed, feed rate, and depth of cut. A systematic experimental design was established as per the response surface methodology (RSM). The experimental design involved twenty base runs with eight cube points, four center points in the cube, six axial points, and two center points in the axial direction. Corresponding statistical analysis was based on analysis of variance and normal probability plots for residuals. Two regression models referring to main cutting force and surface roughness for both the annealed and hardened states of the material were developed and used as objective functions for subsequent evaluations by three modern meta-heuristics under the goal of machinability optimization, namely multi-objective grey wolf algorithm, multi-objective multi-verse algorithm and multi-objective ant lion algorithm. All algorithms were found capable of providing beneficial Pareto-optimal solutions for both main cutting force and surface roughness simultaneously whilst regression models achieved high correlation among input variables and optimization responses.

Experimental and statistical investigation of electro-erosion machining performance of cryogenic treated hardened AISI H13 hot work tool steel

This study investigated the machinability of AISI H13 hot work tool steel with a hardness of 54 HRC, which has been deep cryogenically treated using the electro-erosion machining technique, one of the unconventional manufacturing methods. The machinability parameters used in the study were determined as current (4, 8 and 12 A), pulse time (200, 300 and 400 µs) and three different electrodes (Copper, Graphite and Tuncop). The experimental design was designed according to the Taguchi L27 model, and machinability tests were carried out to examine the results obtained from the experimental study both experimentally and statistically. When the literature was examined, it was seen that cryogenic treatment was generally applied to electrode materials, and only surface roughness and material wear amounts were examined as output parameters. The original value of the study is the interpretation of the results by applying cryogenic treatment to the test material and exploring the surface roughness and material wear amount, as well as the hole diameters and criterion diameters formed on the treated surfaces after the EDM process. As a result of the study, it was observed that the surface roughness value, the hole diameter, the amount of material wear, and the crater diameter increased with the increase in ampere and impact time. The lowest surface roughness value was 2.266 µm in the graphite electrode material at 4 amps and 200 µs impact time and the highest wear amount was realized as 0.555 g in the copper electrode material 12 amps and 400 µs impact time. The smallest hole diameter was 12.254 mm with a tuncop electrode with a pulse duration of 4 amps and 200 µs, and the lowest crater diameter was 127.301 µm with a graphite electrode at a current of 4 amps and a pulse duration of 200 µs. When the signal-to-noise ratios were examined, the optimum machining parameters for surface roughness, hole diameter, material wear amount, and crater diameter were determined as A2B1C1, A1B3C3, A3B1C1, and A3B1C1, respectively. When the ANOVA results are examined, it is determined that the most effective parameter for the surface roughness is of the current value with 86.54%, the most effective parameter for the hole diameter is the electrode material with 85.20%, the most effective parameter for material wear amount is the electrode material with 45.67% and the most effective parameter for the crater diameter is current value with 75.35%.

Investigation of the effects of machining parameters on cutting conditions during orthogonal turning of austenite stainless steel

Abstract The 1.4306 austenite stainless steel has been prominently utilized as a material in the automotive and aerospace industry. Considerable interest has been garnered in the machinability of stainless steel owing to its high strength and poor thermal conductivity. The aim of this study is to ascertain the influential cutting parameters, specifically the cutting speed and feed rate, on cut-ting forces, cutting temperature, and chip evaluation. Thus, austenite stainless steel was subjected to free-cutting using a carbide recessing tool under dry conditions. The principle of measuring cutting temperature, a complex procedure due to varying thermal homogeneity, was elucidated. For the turning experiments in question, the standard Taguchi orthogonal array L9 (32), featuring two factors and three levels, was employed. The experimental results were analyzed using MiniTab 17 software. The findings reveal a substantial effect of feed rate on cutting force, cutting temperature, and chip evaluation. The highest cutting force and cutting temperature were observed at a feed rate of 0.15 mm/rev. Conversely, the cutting force was minimized at a cutting speed of 100 m/min, indicating potential for increasing the cutting speed. The augmentation of feed rate led to chip compression and discoloration, attributed to elevated cutting force and a larger chip cross-section that efficiently dissipates heat from the cutting zone.

Effect of Cutting-Edge Geometry on the Machinability of 316L Austenitic Steel

Effect of Cutting-Edge Geometry on the Machinability of 316L Austenitic Steel

An experimental investigation of F53 super duplex stainless steel using wire cut EDM process

This research focuses on the machinability of F53 super duplex stainless steel using the Wire Electrical Discharge Machining (WEDM) process. F53 Super Duplex Stainless Steel is known for its exceptional corrosion resistance and mechanical properties. It is a popular choice for critical applications in various industries, such as offshore, chemical, and petrochemical. The wire EDM process is chosen for its ability to achieve precise and intricate cuts in hard-to-machine materials like super duplex stainless steel. This study considered important process variables like wire feed rate, servo voltage, pulse-on and pulse-off time, and material removal rate and surface roughness as output responses. Box Behnken method is used to analyse all possible interactions between input and output variables are taken into account, and three different levels of parameter conditions are adopted. It was found that MRR increased by 51.30 % with a gradual increase in pulse on time and applied wire feed and SR decreased by 62.86 % gradually with increasing servo voltage and pulse off time. The optimized values are found to be Ton = 11 µs, WF = 13 m/min, SV = 40 V and Toff = 8 µs. The microhardness study confirms the formation of the melted layer on the machined surface. This research contributes to a deeper understanding of the wire EDM process's applicability to the challenging material properties of F53 super duplex stainless steel, offering insights for the manufacturing and engineering industries aiming to improve the efficiency and precision of machining operations for this advanced material.

Experimental study on electrical discharge machining of porous and pure 316L stainless steel

Porous metal materials are widely used in heat-absorbing, biomedical parts and other fields because of their excellent mechanical properties and biocompatibility. Further applications of porous metal materials are inseparable from secondary precision machining. However, traditional cutting methods tend to compromise the original porosity of the material surface. Electrical discharge machining (EDM) is a type of non-conventional machining method which is more preferable to overcome these defects. In the present study, the main target is to investigate the effect of four input electrical machining parameters (current, frequency, efficiency and gap voltage) on the five output responses (material removal rate (MRR), electrode wear, surface roughness (SR), noise and time consumption value of environmental particulate matter (PM2.5)) when electrical discharge machining porous 316L stainless steel and compared with that of pure 316L stainless steel. The Taguchi method was employed to determine the relationship between electrical discharge machining parameters and output responses. The analysis of variance (ANOVA) was used to evaluate the effect of input parameters on output responses. The effects of electrical machining parameters on above responses were analyzed by main effects, and the order of influence was obtained, respectively. Finally, the surface morphology was observed by scanning electron microscope (SEM), and the effect of electrical machining parameters on the characteristics and formation of machined surface of porous stainless steel was mainly analyzed.

Ultrafine WC–Co cemented carbide end mills prepared by spark plasma sintering and wear mechanism in milling of AISI H13

AbstractUltrafine tungsten carbide (WC)–cobalt (Co) and WC–(Ti,W)C–Co end mills were produced via spark plasma sintering. The wear mechanism of these end mills during machining of AISI H13 steel was investigated. WC–Co exhibits good mechanical properties (HV30: 2110 kg/mm2, KIC: 10.4 MPa/m1/2, TRS: 1990 MPa). Although the high hardness of WC–Co makes it show excellent resistance to abrasive wear, it suffers from a significant adhesion problem. As the cutting temperature increases, the oxidation of the WC–Co causes damage to the microstructure of tool materials, which deteriorates the grain boundary strength and promotes adhesive wear. This phenomenon causes large areas of tool materials to chip off and eventually results in cutting‐edge breakage. The high brittleness of (Ti,W)C causes cracks to propagate at low‐stress levels, reducing the mechanical properties of WC–(Ti,W)C–Co (KIC: 8.8 MPa/m1/2, TRS: 1090 MPa). However, (Ti,W)C addition enhances the resistance to oxidation and workpiece adhesion, which reduces the tool material loss caused by adhesive wear. The tool life of WC–(Ti,W)C–Co is three times longer than that of WC–Co in milling of AISI H13 at the same cutting speed. The key to maximizing the mechanical properties of ultrafine cemented carbide tools when machining AISI H13 is the modification of anti‐adhesive wear of surface.

Modeling and optimization of WEDM machining of armour steel using modified crow search algorithm approach

Modeling and optimization of WEDM machining of armour steel using modified crow search algorithm approach

Impact of cryogenic treatment on the performance of coated tungsten carbide inserts during machining of EN24 grade alloy steel

AbstractToday's industries need to be more productive, especially those that shape and machine materials. As a result, engineers and scientists are seeking for cutting tool materials and technologies that have high hot hardness, chemical stability, wear resistance, and toughness while also improving tool life or contact time. Cryogenic treatment of cutting tools has been proven to be a good way for increasing the contact time of any cutting tool material. This study presents the results of turning alloy steel (EN24 grade) using P20 grade carbide inserts under various conditions under continuous machining. Cutting speeds varied from 100 to 500 m/min (in increments of 100 m/min), with feed rates ranging from 0.1 to 0.4 mm/rev in stages of 0.1 mm/rev and a constant radial depth of cut of 1.5 mm were considered under dry machining conditions. Cryogenic treated/coated inserts are better than other inserts in terms of tool life for optimized parameters such as cutting speed 100 m/min, feed rate 0.1 mm/rev, and depth of cut 1.5 mm, according to the study's findings. Under similar conditions of cutting speed, feed rate, and depth of cut, coated/cryotreated inserts had a tool life increase of about 97.5% over uncoated/untreated inserts, a 50.58% increase over uncoated/crytreated inserts, and a 23.89% increase over coated and untreated inserts, respectively.

Effects of Machining Parameters on Total Cutting Force in Hard Turning Process of Hardened 90CrSi Steel Using Carbide Insert with MoS2 Nanofluid MQL

Minimum Quantity Lubrication (MQL) is widely used in machining, especially hard machining. However, this method has many limitations regarding cooling and lubrication capabilities. In recent years, nano-cutting oils have been researched and applied in machining to improve the lubrication and cooling efficiency of the MQL method. In this research, the machinability of 90CrSi steel with carbide inserts using nanofluid with different concentrations (1%, 1.5%, and 3%) of molybdenum disulfide (MoS2) nanoparticles in emulsion oil was evaluated by applying Box-Behnken optimization model. Carbide inserts commonly used to machine the low hardness steel (below 35HRC) have been used to cut hardened steel with high hardness (59-62HRC) by applying the MQL technology with MoS2 nanofluid. A mathematical model was also used to predict the cutting resultant force value in the hard turning process under MQL conditions using MoS2 nanofluid. The obtained results indicate that the total cutting force reached the minimum value (328 N) with the MoS2 nanoparticle concentration of 1.985%, a cutting speed of 80 m/min, and a feed rate of 0.138 mm/rev. In particular, the work has also provided technical guides for different machining conditions.