scholarly journals An investigation of cutting parameters effect on sound level, surface roughness, and power consumption during machining of hardened AISI 4140

2020 ◽  
Vol 21 (5) ◽  
pp. 523
Author(s):  
Abidin Şahinoğlu ◽  
Efehan Ulas
Keyword(s):  
Surface Roughness ◽  
Energy Consumption ◽  
Power Consumption ◽  
Feed Rate ◽  
Cutting Speed ◽  
Total Power ◽  
Depth Of Cut ◽  
Machining Time ◽  
Total Power Consumption ◽  
Aisi 4140

In recent years, the necessity for energy in the manufacturing industry has become an important problem because fossil fuel reserves are decreasing in order to produce energy. Therefore, the efficient use of energy has become an important research topic. In this study, energy efficiency is investigated in detail for sustainable life and manufacturing. AISI 4140 material with high hardness of 50 HRC hardness has been applied cryogenic process to improve mechanical and machinability properties. In this experiment study, the effects of feed rate (0.04, 0.08, 0.12 mm/rev), cutting speed (140, 160, 180 m/min), depth of cut (0.05, 0.10, 0.15 mm) and tool radius (0.4, 0.8) on energy consumption, surface roughness and sound intensity were investigated. Then, a new mathematical model with high accuracy was developed. Total power consumption was calculated by considering the instantaneous current value and machining time. As a result, it is found that good surface quality obtained when the feed rate is low, and the tool radius is high and the machining time is shortened, the energy consumption is reduced due to the increase in cutting speed, depth of cut and feed rate. Also, it is found that the tool radius has a limited effect on energy consumption, but low feed value increases energy consumption.

scholarly journals Green machining for the dry milling process of stainless steel 304

2019 ◽  
Vol 234 (5) ◽  
pp. 881-899 ◽  
Author(s):  
Trung-Thanh Nguyen ◽  
Mozammel Mia ◽  
Xuan-Phuong Dang ◽  
Chi-Hieu Le ◽  
Michael S Packianather
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Energy Consumption ◽  
Power Factor ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Dry Machining ◽  
Dry Milling ◽  
Stainless Steel 304

Dry machining represents an eco-friendly method that reduces the environmental impacts, saves energy costs, and protects operator health. This article presents a multi-response optimization which aims to enhance the power factor and decrease the energy consumption as well as the surface roughness for the dry machining of a stainless steel 304. The cutting speed ( V), depth of cut ( a), feed rate ( f), and nose radius ( r) were the processing conditions. The outputs of the optimization are the power factor, energy consumption, and surface roughness. The relationships between inputs and outputs were established using the radial basis function models. The experimental data were normalized, with the use of the Grey relational analysis. The principal component analysis is applied to calculate the weight values of technical responses. The desirability approach is used to observe the optimal values. The results showed that the technical outputs are primarily influenced by the feed rate and cutting speed. The reductions of energy consumption and surface roughness are approximately 34.85% and 57.65%, respectively, and the power factor improves around 28.83%, compared to the initial process parameter settings. The outcomes and findings of the investigated work can be used for further research in sustainable design and manufacturing as well as directly used in the knowledge-based and expert systems for dry milling applications in industrial practices.

Machining Apprenticeship Based on Experimental Training Practice

2011 ◽  
Vol 692 ◽  
pp. 83-92
Author(s):  
Pedro Jose Arrazola ◽  
A. Villar ◽  
R. Fernández ◽  
J. Aperribay
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Feed Rate ◽  
Cutting Forces ◽  
Theoretical Calculations ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Practical Training ◽  
Input Parameters

This article describes a practical machining training aiming that the students acquire the theoretical-practical knowledge of chip formation process. The training takes place after theoretical lessons of machining processes. Thus, this practice allows strengthening the knowledge gained during the lessons. The practical training lasts for five hours, and the student assisted by the teacher analyses the influence of some machining entry parameters (cutting speed, feed rate...) on exit parameters like: (I) cutting forces and power consumption, (II) surface roughness, and (III) chip typology. The practical session is carried out on an experimental set-up (Lathe CNC Danobar 65) equipped with sensors and devices to measure forces (sensor Kistler 9121) and power consumption. In addition, a portable rugosimeter (Hommelwerke) is employed to perform surface roughness measurements. No especial devices are needed for the chip typology analysis. In the case of cutting forces and power consumption, the following input parameters influences are analysed: feed rate, depth of cut and cutting speed. In the case of surface roughness analysis, the following input parameters influences are analysed: feed rate and nose radius of the cutting insert. Finally, regarding chip typology feed rate and depth of cut are examined. The experimental results are compared with model predictions (theoretical calculations) for the three issues studied. The students have to compare both results: theoretical an empirical and they need to explain the reasons when discrepancies appear. Results obtained during the last years demonstrate the student acquires better knowledge of the machining process, and at the same time realises of the process complexity.

The Effect of Vortex Tube Air Cooling on Surface Roughness and Power Consumption in Dry Turning

2013 ◽  
Vol 310 ◽  
pp. 348-351 ◽  
Author(s):  
Hadi Abdul Salaam ◽  
Phoon Sin Ye ◽  
Zahari Taha ◽  
Tuan Muhammad Yusoff Shah Tuan Ya
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Feed Rate ◽  
Vortex Tube ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Air Cooling ◽  
Coated Carbide

This paper presents a study of the effect of Ranque-Hilsch vortex tube air cooling on surface roughness quality and power consumption when turning mild steel material with coated carbide cutting tool. The cutting parameters involved in this study were cutting speed, feed rate and depth of cut. The cutting speed and feed rate were fixed at 160 m/min and 0.28 mm/rev, while the depth of cut was varied from 1.0 to 4.0 mm. During the turning process, the cutting temperatures were measured using an infrared thermometer and the power consumption was measured using a power and harmonics analyzer. The machined parts surface roughnesses were measured using a surface roughness tester. The results show that cooling using the Ranque-Hilsch vortex tube air cooling reduces the cutting temperature and the power consumption, but the surface roughness results is better when cooling with environment air.

scholarly journals Investigation of tool wear, surface roughness, sound intensity, and power consumption during hard turning of AISI 4140 steel using multilayer-coated carbide inserts

2021 ◽  
Vol 9 (4B) ◽  
Author(s):  
Abidin Şahinoğlu ◽  
◽  
Mohammad Rafighi ◽  
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Cutting Speed ◽  
Sound Intensity ◽  
Depth Of Cut ◽  
Crater Wear ◽  
Aisi 4140 Steel ◽  
Aisi 4140 ◽  
Coated Carbide ◽  
Carbide Inserts

The present study investigated the machinability aspects, namely, surface roughness, sound intensity, power consumption, and crater wear, during dry turning of hardened AISI 4140 steel (63 HRC) employing (TiCN/Al2O3/TiN) multilayer-coated carbide inserts under dry cutting condition. The relationship between machining parameters and output parameters was determined using the Taguchi design. The analysis of variance was employed to evaluate the contributions of input parameters on output parameters. The main effect plots illustrated the impacts of cutting speed, feed, and depth of cut on response variables. Results show that the feed was the most dominant factor that affects surface roughness. Increasing the feed value increases the surface roughness, power consumption, and sound intensity. In the other part of this study, the constant values for feed (0.3 mm/rev), depth of cut (0.7 mm), and cutting speed (150 m/min) have been selected to evaluate a tool life that has 0.3 mm crater wear criteria. The results indicated that multilayer-coated carbide inserts presented very good tool life and reached 0.3 mm in 90 min. The experimental study results showed that chipping and abrasion were found to be the significant wear mechanism during hard turning of AISI 4140 steel. The cutting speed was the most significant parameter on the tool wear, although high cutting speed results the good surface finish but adversely increases the tool crater wear.

scholarly journals Modeling and optimization of face milling process parameters for AISI 4140 steel

2018 ◽  
Vol 12 (1) ◽  
pp. 5-10 ◽  
Author(s):  
Gokhan Basar ◽  
Funda Kahraman
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Aisi 4140 Steel ◽  
Control Factors ◽  
Aisi 4140

In this study, the effect of cutting parameters such as the depth of cut, feed rate, cutting speed and the number of inserts on surface roughness were investigated in the milling of the AISI 4140 steel. The optimal control factors for surface quality were detected by using the Taguchi technique. Experimental trials were designed according to the Taguchi L18 (21x33) orthogonal array. The statistical effects of control factors on surface roughness have been established by using the analysis of variance (ANOVA). Optimal cutting parameters were obtained by using the S/N ratio values. The ANOVA results showed that the effective factors were the number of inserts and the feed rate on surface roughness. However, the depth of cut and the cutting speed showed an insignificant effect. Additionally, the First-order and Second-order regression analysis were conducted to estimate the performance characteristics of the experiment. The acquired regression equation results matched with the surface roughness measurement results. The optimal performance characteristics were obtained as a 0.5 mm depth of cut, 0.08 mm/rev feed rate, 325 m/min cutting speed and 1 number of inserts by using the Taguchi method. Additionally, the confirmation test results indicated that the Taguchi method was very prosperous in the optimization of the machining parameters to obtain the minimum surface roughness in the milling of the AISI 4140 steel.

Optimization of Surface Roughness in Turning Operation Using Firefly Algorithm

2015 ◽  
Vol 815 ◽  
pp. 268-272 ◽  
Author(s):  
Nur Farahlina Johari ◽  
Azlan Mohd Zain ◽  
Noorfa Haszlinna Mustaffa ◽  
Amirmudin Udin
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Firefly Algorithm ◽  
Volume Fraction ◽  
Optimization Problems ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Time

Recently, Firefly Algorithm (FA) has become an important technique to solve optimization problems. Various FA variants have been developed to suit various applications. In this paper, FA is used to optimize machining parameters such as % Volume fraction of SiC (V), cutting speed (S), feed rate (F), depth of cut (D) and machining time (T). The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

OPTIMIZATION OF PROCESS PARAMETERS AFFECTING CUTTING FORCE, POWER CONSUMPTION AND SURFACE ROUGHNESS USING TAGUCHI-BASED GRAY RELATIONAL ANALYSIS IN TURNING AISI 1040 STEEL

2021 ◽  
Author(s):  
MAHIR AKGÜN
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Cutting Force ◽  
Cutting Speed ◽  
System Optimization ◽  
Gray Relational Analysis ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Significance Level ◽  
Relational Analysis

This study focuses on optimization of cutting conditions and modeling of cutting force ([Formula: see text]), power consumption ([Formula: see text]), and surface roughness ([Formula: see text]) in machining AISI 1040 steel using cutting tools with 0.4[Formula: see text]mm and 0.8[Formula: see text]mm nose radius. The turning experiments have been performed in CNC turning machining at three different cutting speeds [Formula: see text] (150, 210 and 270[Formula: see text]m/min), three different feed rates [Formula: see text] (0.12 0.18 and 0.24[Formula: see text]mm/rev), and constant depth of cut (1[Formula: see text]mm) according to Taguchi L18 orthogonal array. Kistler 9257A type dynamometer and equipment’s have been used in measuring the main cutting force ([Formula: see text]) in turning experiments. Taguchi-based gray relational analysis (GRA) was also applied to simultaneously optimize the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]). Moreover, analysis of variance (ANOVA) has been performed to determine the effect levels of the turning parameters on [Formula: see text], [Formula: see text] and [Formula: see text]. Then, the mathematical models for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) have been developed using linear and quadratic regression models. The analysis results indicate that the feed rate is the most important factor affecting [Formula: see text] and [Formula: see text], whereas the cutting speed is the most important factor affecting [Formula: see text]. Moreover, the validation tests indicate that the system optimization for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) is successfully completed with the Taguchi method at a significance level of 95%.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

scholarly journals Optimization of Milling Parameters of Unmodified Calotropis Procera Fiber-Reinforced PLA Composite (UCPFRPC)

2021 ◽  
Vol 5 (10) ◽  
pp. 261
Author(s):  
Hassan K. Langat ◽  
Fredrick M. Mwema ◽  
James N. Keraita ◽  
Esther T. Akinlabi ◽  
Job M. Wambua ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Removal Rate ◽  
Infrared Camera ◽  
Calotropis Procera ◽  
Depth Of Cut ◽  
Fiber Reinforced ◽  
Machining Time ◽  
Milling Parameters ◽  
Milling Temperature

This study involves the optimization of the milling parameters of unmodified Calotropis Procera fiber-reinforced PLA composite (UCPFRPC). The material is prepared from the combination of 20% Calotropis-Procera and 80% of PLA by weight. The experiments are designed using the Taguchi methodology, where 16 experiments are obtained using the spindle rotational speed, depth of cut, and feed rate as the parameters. These experiments were conducted while obtaining thermal images using an infrared camera and recording the machining time. The change in mass was then determined and the material removal rate computed. The machined workpieces were then investigated for surface roughness. The study shows that the optimal milling parameters in the machining of UCPFRPC for the lowest surface roughness are 400 rpm, 400 mm/min, and 0.2 mm, for the rotational spindle speed, feed rate, and depth of cut. The parameters were 400 rpm, 100 mm/min, and 1.2 mm for the largest MRR, and 400 rpm, 400 mm/min, and 0.2 mm for the least average milling temperature. In all the responses, the depth of cut is the most significant factor.

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