scholarly journals On the Assessment of Surface Quality and Productivity Aspects in Precision Hard Turning of AISI 4340 Steel Alloy: Relative Performance of Wiper vs. Conventional Inserts

Materials ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2036 ◽  
Author(s):  
Adel T. Abbas ◽  
Magdy M. El Rayes ◽  
Monis Luqman ◽  
Noha Naeim ◽  
Hussien Hegab ◽  
...  
Keyword(s):  
Surface Quality ◽  
Feed Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Steel Alloy ◽  
Aisi 4340 Steel ◽  
Aisi 4340

This article reports an experimental assessment of surface quality generated in the precision turning of AISI 4340 steel alloy using conventional round and wiper nose inserts for different cutting conditions. A three-factor (each at 4 levels) full factorial design of experiment was followed for feed rate, cutting speed, and depth of cut, with resulting machined surface quality characterized by resulting average roughness (Ra). The results show that, for the provided range of cutting conditions, lower surface roughness values were obtained using wiper inserts compared with conventional inserts, indicating a superior performance. When including the type of insert as a qualitative factor, ANOVA revealed that the type of insert was most important in determining surface roughness and material removal rate, with feed rate as the second most significant, followed by the interaction of feed rate and type of insert. It was found that using wiper inserts allowed simultaneous increases in feed rate, cutting speed, and depth of cut, while providing better surface quality of lower Ra, compared to the global minimum value that could be achieved using the conventional insert. These findings show that wiper inserts produce better surface quality and a material removal rate up to ten times higher than that obtained with conventional inserts. This clearly indicates the tremendous advantages of high surface quality and productivity that wiper inserts can offer when compared with the conventional round nose type in precision hard turning of AISI 4340 alloy steel.

Modeling and optimization for surface roughness and tool flank wear in hard turning of AISI 4340 steel (35 HRC) using TiSiN-TiAlN nanolaminate coated insert

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Kaladhar
Keyword(s):  
Feed Rate ◽  
Hard Turning ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Content Type ◽  
Aisi 4340 Steel ◽  
4340 Steel ◽  
Optimal Set ◽  
Aisi 4340

PurposeThe present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.Design/methodology/approachIn this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.FindingsOptimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.Originality/valueThis work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.

scholarly journals Optimization of Dimensional Tolerances and Material Removal Rate in the Orthogonal Turning of AISI 4340 Steel

2021 ◽  
Author(s):  
Chathakudath Sukumaran Sumesh ◽  
Dawood Sheriff Akbar ◽  
Hari Shankar Purandharadass ◽  
Raghunandan J. Chandrasekaran
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 4340 Steel ◽  
4340 Steel ◽  
Aisi 4340

Turning is one of the most used metal removal operations in the industry. It can remove material faster, giving reasonably good surface quality apart from geometrical requirements. Conformity of geometry is one of the most significant requirements of turned components to perform their intended functions. Apart from dimensional requirements, the important geometrical necessities are Circularity, Straightness, Cylindricity, Perpendicularity, etc. Since they have a direct influence on the functioning of the components, the effect of the cutting parameters on them has greater significance. In this paper experiments are carried out to examine the effect of turning parameters such as cutting speed, feed rate, and depth of cut on responses like; straightness, roundness, surface roughness, and material removal rate during turning of AISI 4340 steel. Analysis of Variance (ANOVA) is performed and the influence of parameters on each response is studied. The optimal values of parameters obtained from the study are further confirmed by conducting experiments.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

Performance Analysis of Trihexyltetradecylphosphonium Chloride Ionic Fluid under MQL Condition in Hard turning

2020 ◽  
Vol 17 (1) ◽  
pp. 7629-7647
Author(s):  
A. Pandey ◽  
R. Kumar ◽  
A. K. Sahoo ◽  
A. Paul ◽  
A. Panda
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Coconut Oil ◽  
Chip Morphology ◽  
Weight Fraction ◽  
Cutting Fluid ◽  
Depth Of Cut

The current research presents an overall performance-based analysis of Trihexyltetradecylphosphonium Chloride [[CH3(CH2)5]P(Cl)(CH2)13CH3] ionic fluid mixed with organic coconut oil (OCO) during turning of hardened D2 steel. The application of cutting fluid on the cutting interface was performed through Minimum Quantity Lubrication (MQL) approach keeping an eye on the detrimental consequences of conventional flood cooling. PVD coated (TiN/TiCN/TiN) cermet tool was employed in the current experimental work. Taguchi’s L9 orthogonal array and TOPSIS are executed to analysis the influences, significance and optimum parameter settings for predefined process parameters. The prime objective of the current work is to analyze the influence of OCO based Trihexyltetradecylphosphonium Chloride ionic fluid on flank wear, surface roughness, material removal rate, and chip morphology. Better quality of finish (Ra = 0.2 to 1.82 µm) was found with 1% weight fraction but it is not sufficient to control the wear growth. Abrasion, chipping, groove wear, and catastrophic tool tip breakage are recognized as foremost tool failure mechanisms. The significance of responses have been studied with the help of probability plots, main effect plots, contour plots, and surface plots and the correlation between the input and output parameters have been analyzed using regression model. Feed rate and depth of cut are equally influenced (48.98%) the surface finish while cutting speed attributed the strongest influence (90.1%). The material removal rate is strongly prejudiced by cutting speed (69.39 %) followed by feed rate (28.94%) whereas chip reduction coefficient is strongly influenced through the depth of cut (63.4%) succeeded by feed (28.8%). TOPSIS significantly optimized the responses with 67.1 % gain in closeness coefficient.

Development of Tooling Cost Model for High Speed Hard Turning

2011 ◽  
Vol 418-420 ◽  
pp. 1482-1485 ◽  
Author(s):  
Erry Yulian Triblas Adesta ◽  
Muataz Al Hazza ◽  
Delvis Agusman ◽  
Agus Geter Edy Sutjipto
Keyword(s):  
Feed Rate ◽  
High Speed ◽  
Hard Turning ◽  
Cost Model ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Rake Angle ◽  
Depth Of Cut ◽  
Predictive Regression ◽  
Aisi 4340

The current work presents the development of cost model for tooling during high speed hard turning of AISI 4340 hardened steel using regression analysis. A set of experimental data using ceramic cutting tools, composed approximately of Al2O3 (70%) and TiC (30%) on AISI 4340 heat treated to a hardness of 60 HRC was obtained in the following design boundary: cutting speeds (175-325 m/min), feed rate (0.075-0.125 m/rev), negative rake angle (0 to -12) and depth of cut of (0.1-0.15) mm. The output data is used to develop a new model in predicting the tooling cost using in terms of cutting speed, feed rate, depth of cut and rake angle. Box Behnken Design was used in developing the model. Predictive regression model was found to be capable of good predictions the tooling cost within the boundary design.

scholarly journals Analysis and Optimization of Ceramic Cutting Tool In Hard Turning of EN-31 Using Factorial Design

2012 ◽  
pp. 53-58
Author(s):  
Chetan Darshan ◽  
Lakhvir Singh ◽  
APS Sethi
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Analysis Of Variance ◽  
Feed Rate ◽  
Hard Turning ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Good Surface ◽  
En 31

Manufacturers around the globe persistently looking for the cheapest and quality manufactured machined components to compete in the market. Good surface quality is desired for the proper functioning of the produced parts. The surface quality is influenced by cutting speed, feed rate and depth of cut and many other parameters. In the present study attempt has been made to evaluate the performance of ceramic inserts during hard turning of EN-31 steel. The analysis of variance is applied to study the effect of cutting speed, feed rate and depth of cut on Flank wear and surface roughness. Model is found to be statically significant using regression model, while feed and depth of cut are the factor affecting Flank wear and feed is dominating factors for surface roughness. The analysis of variance was used to analyze the input parameters and there interactions during machining. The developed model predicted response factor at 95% confidence level.

scholarly journals Optimal Seeking Surface Roughness and Material Removal Rate Responses of Hardened AISI 4340 High Strength Low AlloySteel in Dry Sustainable Environment

2021 ◽  
Vol 40 (1) ◽  
pp. 116-129
Author(s):  
Amar ul Hassan Khawaja ◽  
Mirza Jahanzaib ◽  
Shahzad Zaka
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
High Strength ◽  
Depth Of Cut ◽  
Sustainable Environment ◽  
Coated Carbide ◽  
Aisi 4340

The aim of this research is to study the machinability aspects of hardened AISI 4340 High Strength Low Alloy (HSLA) steel (50 ± 2 HRC (Hardness Rockwell C)). The experimental investigation using coated carbide inserts is carried out during the dry hard milling process in a sustainable environment. The input parameters in the study are speed, feed rate and depth of cut and the responses are Average surface Roughness (Ra) and Material Removal Rate (MRR) that are selected through screening. Central Composite Design (CCD) in response surface methodology has been utilized as the experimental design technique with twenty experiments. Analysis of variance has been employed to examine the momentous machining parameters and responses. A mathematical model has been developed to optimize the surface roughness and material removal rate. It has been observed that the most significant factor for Ra is feed rate while for MRR depth of cut is the most significant factor. The results show that the minimum value of Ra ~ 0.098 μm is achieved at speed ~ 1000 RPM, feed rate ~ 300 mm/min and depth of cut ~ 0.2 mm while the maximum value of MRR ~ 6.35 cm3/min is attained at feed rate ~ 500mm/min and depth of cut ~ 0.4 mm regarding less or no effect of speed ~ 500-1000 RPM. The average forecast error for the validation information has been observed to be 3.35%. for Ra and 3.2% for MRR. Further, it is investigated that good surface finish like grinding and dimensional accuracy can be achieved with coated carbide tools.

EXPERIMENTAL ANALYSIS, STATISTICAL MODELING AND OPTIMIZATION OF EFFECTIVE PARAMETERS ON SURFACE QUALITY IN CORTICAL BONE MILLING PROCESS

2020 ◽  
Vol 20 (04) ◽  
pp. 1950078
Author(s):  
MAHDI QASEMI ◽  
M-MORAD SHEIKHI ◽  
MOJTABA ZOLFAGHARI ◽  
VAHID TAHMASBI
Keyword(s):  
Surface Quality ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Milling Process ◽  
Artificial Joint ◽  
Effective Parameters ◽  
Tool Diameter

Knee joint surgery for artificial joint replacement is common in orthopedic surgeries. In this operation, there is a need to prepare the surface of the cortical bone for mounting the artificial joint. Therefore, milling process is frequently performed. Since the surgeon should be careful not to hurt bone tissue and neurons and also minimize waste of blood, the operation should be performed in the shortest possible time. This study, for the first time, focuses on modeling and optimization of effective parameters of bone milling including cutting speed, feed rate and tool diameter on surface roughness and material removal rate using response surface method. Results showed that in order to achieve maximum surface quality, minimum feed rate, maximum tool diameter and down milling procedure should be selected. On the other hand, the maximum material removal rate coincides with maximum feed rate and tool diameter. Therefore, cutting speed of 3000[Formula: see text]rpm, feed rate of 50[Formula: see text]mm/min, tool diameter of 5[Formula: see text]mm and down milling procedure can satisfy both high surface quality and high material removal rate.

scholarly journals Use of Multi-Objective Optimization Technique (Taguchi-GRA Approach) in Dry Hard Turning of Inconel 625

2020 ◽  
Vol 12 (2) ◽  
pp. 133-142
Author(s):  
Chinmaya PADHY ◽  
Pariniti SINGH
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Removal Rate ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Grey Relational

Current developments in manufacturing industries consider developing a suitable optimization technique for achieving improved machining performance. This study investigates the optimum values of machining parameters required namely –cutting speed (v), feed rate (f) and depth-of-cut (d) during dry hard turning of Inconel 625 with the aim of enhancing the productivity by minimizing surface roughness (Ra), cutting force (Fc), whereas maximizing material removal rate(MRR). This kind of multi-response process variable (MRP) problems usually known as multi-objective optimizations (MOOs) are solved with the help of Taguchi- Grey Relational Approach (T-GRA). Thus, here is a study conducted to apply Taguchi and Grey relational analysis to optimize multiple performance characteristics during dry hard turning of Inconel -625. As a result, the attained process variables, viz., cutting speed (60 m/min), feed rate (0.3 mm/rev), depth- of- cut (0.25mm) lead to value of optimum response variables –mean cutting force (340 N), surface roughness (0.998 μm) and material removal rate (0.786 mm3/min). In this setup, PVD coated carbide tool inserts were used for dry hard machining (turning) operation.

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