scholarly journals Effect of Cutting Speed, Feed-rate and Depth of Cut on the Surface Roughness Level of ST-37 Steel in Shaping Proces

Teknomekanik ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 1-6
Author(s):  
Krisko Govinda ◽  
Abd Aziz
Keyword(s):  
Surface Roughness ◽  
Data Analysis ◽  
Feed Rate ◽  
Steel Surface ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
High Data ◽  
Scrap Process ◽  
Effect Of Feeding

Abstract The application in the industrial world, the use of scrap machines by operators pay little attention to the surface roughness of objects produced. The roughness that occurs is influenced by machining parameters such as cutting speed, feed motion, and cutting thickness. The purpose of this study was to determine the effect of cutting speed, feed motion and cutting thickness on the level of roughness of ST 37 steel surface in the scrap process. This type of research is an experimental method that determines the level of steel surface roughness from variations in cutting speed, feed motion, and cutting thickness to ST 37 steel surface roughness. The material used is 70 mm long, 25 mm wide, and 25 mm high. Data processing results from the level of roughness testing using the SPSS version 16.0 application. The results of data analysis showed (1) the significant effect of cutting speed on the level of surface roughness of 5.5%. (2) the significant effect of feeding on the level of surface roughness of 60.9%. (3) significant effect between cutting thickness on surface roughness level of 0.2% (4) significant influence between cutting speed, feed motion, and cutting thickness on the level of surface roughness with a 66.6% influence. Based on data analysis, it can be concluded that cutting speed, feeding motion, cutting thickness are factors that influence the level of steel surface roughness of ST 37 in the scrap process. Keywords: Cutting Speed, Feed Rate, Depth of Cut, Roughness Level, Experimental.

Effect of machining parameters on the surface finish of a metal matrix composite under dry cutting conditions

2015 ◽  
Vol 231 (6) ◽  
pp. 913-923 ◽  
Author(s):  
Brian Boswell ◽  
Mohammad Nazrul Islam ◽  
Ian J Davies ◽  
Alokesh Pramanik
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composite ◽  
Tool Life ◽  
Surface Finish ◽  
Feed Rate ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting

The machining of aerospace materials, such as metal matrix composites, introduces an additional challenge compared with traditional machining operations because of the presence of a reinforcement phase (e.g. ceramic particles or whiskers). This reinforcement phase decreases the thermal conductivity of the workpiece, thus, increasing the tool interface temperature and, consequently, reducing the tool life. Determining the optimum machining parameters is vital to maximising tool life and producing parts with the desired quality. By measuring the surface finish, the authors investigated the influence that the three major cutting parameters (cutting speed (50–150 m/min), feed rate (0.10–0.30 mm/rev) and depth of cut (1.0–2.0 mm)) have on tool life. End milling of a boron carbide particle-reinforced aluminium alloy was conducted under dry cutting conditions. The main result showed that contrary to the expectations for traditional machined alloys, the surface finish of the metal matrix composite examined in this work generally improved with increasing feed rate. The resulting surface roughness (arithmetic average) varied between 1.15 and 5.64 μm, with the minimum surface roughness achieved with the machining conditions of a cutting speed of 100 m/min, feed rate of 0.30 mm/rev and depth of cut of 1.0 mm. Another important result was the presence of surface microcracks in all specimens examined by electron microscopy irrespective of the machining condition or surface roughness.

scholarly journals Optimization of machining parameters in face milling using multi-objective Taguchi technique

2018 ◽  
Vol 12 (2) ◽  
pp. 104-108 ◽  
Author(s):  
Yusuf Fedai ◽  
Hediye Kirli Akin
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Taguchi Technique ◽  
Average Roughness ◽  
Multi Objective ◽  
Control Factors ◽  
Average Maximum

In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique.

Taguchi Method Based Experiments of Titanium TC11 Flank Milling Parameters

2009 ◽  
Vol 407-408 ◽  
pp. 608-611 ◽  
Author(s):  
Chang Yi Liu ◽  
Cheng Long Chu ◽  
Wen Hui Zhou ◽  
Jun Jie Yi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Flank Milling ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Mill Machining

Taguchi design methodology is applied to experiments of flank mill machining parameters of titanium alloy TC11 (Ti6.5A13.5Mo2Zr0.35Si) in conventional and high speed regimes. This study includes three factors, cutting speed, feed rate and depth of cut, about two types of tools. Experimental runs are conducted using an orthogonal array of L9(33), with measurement of cutting force, cutting temperature and surface roughness. The analysis of result shows that the factors combination for good surface roughness, low cutting temperature and low resultant cutting force are high cutting speed, low feed rate and low depth of cut.

Optimisation of Machining Parameters for Milling Polyetheretherketones (PEEK) Biomaterial

2014 ◽  
Vol 699 ◽  
pp. 198-203 ◽  
Author(s):  
Raja Izamshah Raja Abdullah ◽  
Aaron Yu Long ◽  
Md Ali Mohd Amran ◽  
Mohd Shahir Kasim ◽  
Abu Bakar Mohd Hadzley ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dimensional Precision ◽  
Good Surface

Polyetheretherketones (PEEK) has been widely used as biomaterial for trauma, orthopaedic and spinal implants. Component made from Polyetheretherketones generally required additional machining process for finishing which can be a problem especially to attain a good surface roughness and dimensional precision. This research attempts to optimize the machining and processing parameters (cutting speed, feed rate and depth of cut) for effectively machining Polyetheretherketones (PEEK) implant material using carbide cutting tools. Response Surface Methodology (RSM) technique was used to assess the effects of the parameters and their relations towards the surface roughness values. Based on the analysis results, the optimal machining parameters for the minimum surface roughness values were by using cutting speed of 5754 rpm, feed rate of 0.026 mm/tooth and 5.11 mm depth of cut (DOC).

scholarly journals An Investigation on Optimum Process Parameters in Terms of Surface Roughness for Turning Titanium Alloy Ti-6Al-4V Using Coated Carbide

2019 ◽  
Vol 4 (4) ◽  
pp. 137-145
Author(s):  
Abdul Md Mazid ◽  
Md. Shahanur Hasan ◽  
Kazi Badrul Ahsan
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Real Life ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Ti Alloys ◽  
Machined Parts ◽  
Coated Carbide ◽  
Coated Carbide Tools

The quality of machined parts and the productivity of machining that leads to economic sustainability.  These factors are also vital for machinability improvement for materials, as well as, for economically sustainable manufacturing. Due to their poor machinability titanium alloys (Ti-alloys) are categorised as difficult-to-machine materials. For the same reason products made of Ti-alloys are highly expensive and are used only in strategic and sophisticated industries.  A series of real-life experimental investigations was carried out to reveal the economic optimal zones of machining parameters that can produce the best possible surface roughness in machining Ti-6Al-4V alloy, using the coated carbide cutting tools, in shortest period of operation time. As the output of the research, for using the coated carbide tools for machining the investigated Ti-alloy, optimal zones of cutting speed, feed rate and depth of cut have been proposed and presented in graphical format. The current research revealed that all three groups (with nose radius Nr = 0.4, 0.8, and 1.2 mm) of coated carbide tools are capable to produce best surface finish, ranging between Ra = 0.5 - 1.0 µm, with cutting speed starting at V = 60 m/min and beyond at least up to V = 250 m/min while keeping the feed rate and depth of cut as constants as f = 0.1 mm/rev and d = 0.5 mm. The data on the graphs may help researchers, engineers and manufacturers to select optimal economic cutting speed, feed rate and depth of cut to achieve a certain level of surface roughness of machined components as assigned by the product designer on the part drawing. This reduces the production cost substantially, reduces number of defect products and improves product quality for machined parts.

The Effect of Cutting Speed and Feed Rate on Surface Roughness and Tool Wear when Machining Machining D2 Steel

2017 ◽  
Vol 909 ◽  
pp. 80-85 ◽  
Author(s):  
Mohd Rasidi Ibrahim ◽  
Tharmaraj Sreedharan ◽  
Nurul Aisyah Fadhlul Hadi ◽  
Mohammad Sukri Mustapa ◽  
Al Emran Ismail ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Surface Quality ◽  
Feed Rate ◽  
Input Parameter ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
D2 Steel

Machining parameters is a main aspect in performing turning operations using lathe machines. Cutting parameters such as cutting speed, feed rate and depth of cut gives big influence on the dynamic behavior of the machining system. In machining parts, surface quality and tool wear are the most crucial customer requirements. This is because the major indication of surface quality on machined part is the surface roughness and the value of tool wear. Hence, to improve the surface roughness and minimize the forming of tool wear, the optimum feed rate and cutting speed will be determined. The input parameter such as cutting speed, feed rate and depth of cut always influence the tool wear, surface roughness, cutting force, cutting temperature, tool life and dimensional accuracy. The D2 steel was being investigated from the perspective of the effect of cutting speed and feed rate on its surface roughness and tool wear. The results show that cutting speed is the main parameter which affects the surface roughness where the most optimum parameter would be at cutting speed of 173, 231 and 288 m/min with feed rate of 0.15 mm/rev. The tool wear strongly affected by feed rate where at 0.15 mm/rev the tool wear value is the lowest. The combination of high cutting speed and low feed rate was the best parameter to achieve smooth surface roughness.

Optimization of Cutting Parameters for Turning Operation of Titanium Alloy Ti-6Al-4V Material Workpiece Using the Taguchi Method

2013 ◽  
Vol 685 ◽  
pp. 57-62
Author(s):  
Seyyed Pedram Shahebrahimi ◽  
Abdolrahman Dadvand
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Taguchi Method ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Material Tool

One of the most important issues in turning operations is to choose suitable parameters in order to achieve a desired surface finish. The surface finish in machining operation depends on many parameters such as workpiece material, tool material, tool coating, machining parameters, etc. The purpose of this research is to focus on the analysis of optimum cutting parameters to get the lowest surface roughness in turning Titanium alloy Ti-6Al-4V with the insert with the standard code DNMG 110404 under dry cutting condition, by the Taguchi method. The turning parameters are evaluated as cutting speed of 14, 20 and 28 m/min, feed rate of 0.12, 0.14 and 0.16 mm/rev, depth of cut of 0.3, 0.6 and 1 mm, each at three levels. The Experiment was designed using the Taguchi method and 9 experiments were conducted by this process. The results are analyzed using analysis of variance method (ANOVA). The results of analysis show that the depth of cut has a significant role to play in producing lower surface roughness that is about 63.33% followed by feed rate about 30.25%, and cutting speed has less contribution on the surface roughness. Also it was realized that with the use of the confirmation test, the surface roughness improved by 227% from its initial state.

scholarly journals Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4377 ◽  
Author(s):  
Mustafa Kuntoğlu ◽  
Abdullah Aslan ◽  
Hacı Sağlam ◽  
Danil Yurievich Pimenov ◽  
Khaled Giasin ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Feed Rate ◽  
Cutting Speed ◽  
Tool Condition Monitoring ◽  
Depth Of Cut ◽  
Optimization Approach ◽  
Machining Parameters ◽  
Tool Condition ◽  
Condition Monitoring System

Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%).

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.

Investigating and Modeling the Machinability of Al 6061 Using Response Surface Methodology

2015 ◽  
Vol 761 ◽  
pp. 267-272
Author(s):  
Basim A. Khidhir ◽  
Ayad F. Shahab ◽  
Sadiq E. Abdullah ◽  
Barzan A. Saeed
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Effect Of Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process

Decreasing the effect of temperature, surface roughness and vibration amplitude during turning process will improve machinability. Mathematical model has been developed to predict responses of the surface roughness, temperature and vibration in relation to machining parameters such as the cutting speed, feed rate, and depth of cut. The Box-Behnken First order and second-order response surface methodology was employed to create a mathematical model, and the adequacy of the model was verified using analysis of variance. The experiments were conducted on aluminium 6061 by cemented carbide. The direct and interaction effect of the machining parameters with responses were analyzed. It was found that the feed rate, cutting speed, and depth of cut played a major role on the responses, such as the surface roughness and temperature when machining mild steel AISI 1018. This analysis helped to select the process parameters to improve machinability, which reduces cost and time of the turning process.

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