scholarly journals Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6106
Author(s):  
Waleed Ahmed ◽  
Hussien Hegab ◽  
Atef Mohany ◽  
Hossam Kishawy
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Inclination Angle ◽  
Feed Rate ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Hardened Steel ◽  
Machining Process ◽  
Aisi 4140 ◽  
Steel Aisi

It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle were the selected design variables, while the tool wear, surface roughness, and material removal rate (MRR) were the studied outputs. The optimal surface roughness was obtained at a cutting speed of 240 m/min, an inclination angle of 20°, and a feed rate of 0.1 mm/rev. In addition, the minimum flank tool wear was observed at a cutting speed of 70 m/min, an inclination angle of 10°, and a feed rate of 0.15 mm/rev. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer’s interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140 within the selected ranges.

scholarly journals Towards Analysis and Optimization during Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

2021 ◽  
Author(s):  
Waleed Ahmed ◽  
Hussien Hegab ◽  
Atef Mohany ◽  
Hossam Kishawy
Keyword(s):  
Tool Wear ◽  
Inclination Angle ◽  
Removal Rate ◽  
Weight Ratio ◽  
High Strength ◽  
Hardened Steel ◽  
Machining Process ◽  
Nsga Ii ◽  
Aisi 4140 ◽  
Steel Aisi

Abstract It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered as one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance, and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle are selected to be the design variables, while the tool wear, surface roughness, and material removal rate (MRR) are the studied outputs. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140.

Characterisation, Performance and Optimisation of Nanocellulose Metalworking Fluid (MWF) for Green Machining Process

2021 ◽  
Vol 18 (4) ◽  
pp. 9188-9207
Author(s):  
Mahendran Samykano ◽  
J. Kananathan ◽  
K. Kadirgama ◽  
A. K. Amirruddin ◽  
D. Ramasamy ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Alumina Nanoparticles ◽  
Working Fluid ◽  
Depth Of Cut ◽  
Nanoparticle Concentration

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour.

Influence of the cutting condition on the wear and the surface roughness in the steel AISI 4140 with mixed ceramic and diamond tool

2018 ◽  
Vol 16 (6) ◽  
pp. 828-836
Author(s):  
Razika Aouad ◽  
Idriss Amara
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Tool Wear ◽  
Tool Life ◽  
Cutting Speed ◽  
Cutting Condition ◽  
Content Type ◽  
Aisi 4140 ◽  
Steel Aisi ◽  
Mixed Ceramic

PurposeThe purpose of this paper is to study the influence of the cutting conditions (cutting speed, feed rate and cutting depth) on the roughness (Ra) and on the flank wear (Vb) of the steel AISI 4140.Design/methodology/approachMixed ceramic (CC650) and polycrystalline cubic boron nitride (PCBN) have been used to carry out straight turning tests under dry conditions.FindingsThe results indicate that PCBN is more efficient than mixed ceramic (Al2O3+TiC) used in terms of wear resistance regardless of the aggressiveness of the AISI 4140 at 50 hardness rockwell (HRC). Consequently, it is the most powerful. Surface quality attained with PCBN tool considerably compares with that of grinding. Even when the tool wear VB reached 0.3 mm, the majority of the recorded Ra values did not exceed 1 m at the various speeds tested. The correlation of tool wear Vb and surface roughness Ra established allows obtaining experimental empirical data on the cutting tool wear from measured surface roughness for practical use in industry. The values of constants and the coefficient of determinationR2of this mathematical model will be calculated. Mathematical models expressing the relation between the elements of the cutting regime and technological parameters (tool life and roughness) are proposed.Originality/valueMany works have been already made in the similar manner, but this study of CC650 and PCBN wear is the first. Through this study, we propose a mathematical model expressing the relation between the elements of the cutting regime, tool life and roughness.

Experimental Investigation of Effects of Feed Rate and Cutting Speed on Surface Roughness and Cutting Tool Wear in Drilling of AISI 4140 Steel Workpieces Hardened up to 30 HRC using Solid Carbide Drills

2020 ◽  
Author(s):  
Ömer ŞAHİN ◽  
Erdinç KALUÇ
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cooling Water ◽  
Measurement Instrument ◽  
Cutting Tool Wear ◽  
Aisi 4140 ◽  
Solid Carbide

Abstract In this study, effects of feed rate and cutting speed on surface roughness and cutting tool wear were investigated in drilling of AISI 4140 tempered steel workpieces with internally cooled, Ø14 mm diameter solid carbide drills on a CNC lathe. Although there are various literature on this subject, since there is no information on the experimental parameters that the study has been done, the contribution and originality of the study to the literature is to be qualitative.The experimental study was conducted using cooling water and with cutting speeds of 50, 60, 70, and 80 m/min and feed rate parameters of 0.10, 0.15, 0.20, and 0.25 mm/rev. At the end of the experiment, wear of the used drills was monitored with a material microscope and wear values were determined. Surface roughness of the holes was measured with Mitutoyo branded surface roughness measurement instrument. The longest drill life was obtained at 50 m/min cutting speed and 0.10 mm/rev feed rate. Surface roughness of the samples with drilled holes was measured, and these values were found to vary in the range of 0.270–2.480 µm. At 0.10 mm/rev feed rate and 50 m/min cutting speed, the lowest cutting tool wear was measured as 1222393.74 µm2, while the highest wear was measured as 4532811.14 µm2. For the best surface quality and lowest cutting tool wear, 50 m/min cutting speed and 0.10 mm/rev feed rate were determined to be the optimum parameters.

scholarly journals An experimental study on the effect of tool geometry on tool wear and surface roughness in hard turning

2020 ◽  
Vol 12 (9) ◽  
pp. 168781402095988
Author(s):  
Pham Minh Duc ◽  
Le Hieu Giang ◽  
Mai Duc Dai ◽  
Do Tien Sy
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Inclination Angle ◽  
Hard Turning ◽  
Rake Angle ◽  
Machining Process ◽  
Tool Geometry ◽  
Standard Tool ◽  
Inclination Angles ◽  
Mixed Ceramic

The main purpose of this study is to investigate the influence of tool geometry (cutting edge angle, rake angle, and inclination angle) and to optimize tool wear and surface roughness in hard turning of AISI 1055 (52HRC) hardened steel by using TiN coated mixed ceramic inserts. The results show that the inclination angle is the major factor affecting the tool wear and the surface roughness in hard turning. With the increase in negative rake and inclination angles, the tool wear decreases, and the surface roughness increases. However, the surface roughness will decrease when the inclination angle increases to overpass a certain limit. This is a new and significant point in the research of the hard turning process. From this result, the large negative inclination angle (λ = −10°) should be applied to reduce the surface roughness and the tool wear simultaneously. With the optimal cutting tool angles in the research, the hard machining process is improved remarkably with decreases of surface roughness and tool wear 8.3% and 41.3%, respectively in comparison with the standard tool angles. And the proposed tool-post design approach brings an effective method to change the tool insert angles using standard tool-holders to improve hard or other difficult-to-cut materials turning quality.

scholarly journals Experimental Investigation on Surface Roughness and Tool Wear in Dry Machining of TiC Reinforced Aluminium LM6 Composite

2013 ◽  
Vol 773-774 ◽  
pp. 339-347 ◽  
Author(s):  
Muhammad Yusuf ◽  
M.K.A. Ariffin ◽  
N. Ismail ◽  
S. Sulaiman
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Carbide Tool ◽  
Dry Machining ◽  
Workpiece Surface ◽  
High Cutting Speed

With increasing quantities of applications of Metal Matrix Composites (MMCs), the machinablity of these materials has become important for investigation. This paper presents an investigation of surface roughness and tool wear in dry machining of aluminium LM6-TiC composite using uncoated carbide tool. The experiments carried out consisted of different cutting models based on combination of cutting speed, feed rate and depth of cut as the parameters of cutting process. The cutting models designed based on the Design of Experiment Response Surface Methodology. The objective of this research is finding the optimum cutting parameters based on workpiece surface roughness and cutting tool wear. The results indicated that the optimum workpiece surface roughness was found at high cutting speed of 250 m min-1 with various feed rate within range of 0.05 to 0.2 mm rev-1, and depth of cut within range of 0.5 to 1.5 mm. Turning operation at high cutting speed of 250 m min-1 produced faster tool wear as compared to low cutting speed of 175 m min-1 and 100 m min-1. The wear minimum (VB = 42 μm ) was found at cutting speed of 100 m min-1, feet rate of 0.2 mm rev-1, and depth of cut of 1.0 mm until the length of cut reached 4050 mm. Based on the results of the workpiece surface roughness and the tool flank wear, recommended that turning of LM6 aluminium with 2 wt % TiC composite using uncoated carbide tool should be carried out at cutting speed higher than 175 m min-1 but at feed rate of less than 0.05 mm rev-1 and depth of cut less than 1.0 mm.

scholarly journals Analysis of tool wear and surface roughness in high-speed milling process of aluminum alloy Al6061

2021 ◽  
pp. 71-84
Author(s):  
Nhu-Tung Nguyen ◽  
Dung Hoang Tien ◽  
Nguyen Tien Tung ◽  
Nguyen Duc Luan
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Tool Wear ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Milling Process ◽  
Face Milling ◽  
Depth Of Cut ◽  
High Speed Milling

In this study, the influence of cutting parameters and machining time on the tool wear and surface roughness was investigated in high-speed milling process of Al6061 using face carbide inserts. Taguchi experimental matrix (L9) was chosen to design and conduct the experimental research with three input parameters (feed rate, cutting speed, and axial depth of cut). Tool wear (VB) and surface roughness (Ra) after different machining strokes (after 10, 30, and 50 machining strokes) were selected as the output parameters. In almost cases of high-speed face milling process, the most significant factor that influenced on the tool wear was cutting speed (84.94 % after 10 machining strokes, 52.13 % after 30 machining strokes, and 68.58 % after 50 machining strokes), and the most significant factors that influenced on the surface roughness were depth of cut and feed rate (70.54 % after 10 machining strokes, 43.28 % after 30 machining strokes, and 30.97 % after 50 machining strokes for depth of cut. And 22.01 % after 10 machining strokes, 44.39 % after 30 machining strokes, and 66.58 % after 50 machining strokes for feed rate). Linear regression was the most suitable regression of VB and Ra with the determination coefficients (R2) from 88.00 % to 91.99 % for VB, and from 90.24 % to 96.84 % for Ra. These regression models were successfully verified by comparison between predicted and measured results of VB and Ra. Besides, the relationship of VB, Ra, and different machining strokes was also investigated and evaluated. Tool wear, surface roughness models, and their relationship that were found in this study can be used to improve the surface quality and reduce the tool wear in the high-speed face milling of aluminum alloy Al6061

scholarly journals Sustainability Assessment, Investigations, and Modelling of Slot Milling Characteristics in Eco-Benign Machining of Hardened Steel

Metals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1650
Author(s):  
Angelos P. Markopoulos ◽  
Nikolaos E. Karkalos ◽  
Mozammel Mia ◽  
Danil Yurievich Pimenov ◽  
Munish Kumar Gupta ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Tool Steel ◽  
Sustainability Assessment ◽  
Cutting Speed ◽  
Hardened Steel ◽  
Assessment Model ◽  
Machining Process ◽  
Cutting Power ◽  
Slot Milling

The hardened tool steel AISI O1 has increased strength, hardness, and wear resistance, which affects the complexity of the machining process. AISI O1 has also been classified as difficult to cut material hence optimum cutting parameters are required for the sustainable machining of the alloy. In this work, the effect of feed peer tooth (fz), cutting speed (vc), cutting of depth (ap) on surface roughness (Ra, Rt), cutting force (Fx, Fy), cutting power (Pc), machining cost (Ci), and carbon dioxide (Ene) were investigated during the slot milling process of AISI O1 hardened steel. A regression analysis was carried out on the obtained experimental results and the induction of nonlinear mathematical equations of surface roughness, cutting force, cutting power, and machining cost with a high coefficient of determination (R2 = 90.62–98.74%) were deduced. A sustainability assessment model is obtained for optimal and stable levels of design variables when slot milling AISI O1 tool steel. Stable indicators to ensure personal health and safety of operation, P1 values were set to “1” at a cutting speed of 20 m/min or 43.3 m/min and “2” at a cutting speed of 66.7 m/min or 90 m/min. It is revealed that for eco-benign machining of AISI O1, the optimum parameters of 0.01 mm/tooth, 20 m/min, and 0.1 mm should be adopted for feed rate, cutting speed, and depth of cut respectively.

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