Investigating the Effect of Machining Parameters On Tool Life For Turning of En 08

2012 ◽  
Vol 2 (6) ◽  
pp. 248-249
Author(s):  
Vishal Francis ◽  
◽  
Sumit k Singh Sumit k Singh
Keyword(s):  
Tool Life ◽  
Machining Parameters

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.

Machining parameters effect in dry turning of AISI 316L stainless steel using coated carbide tools

2015 ◽  
Vol 231 (4) ◽  
pp. 676-683 ◽  
Author(s):  
Rusdi Nur ◽  
MY Noordin ◽  
S Izman ◽  
D Kurniawan
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Power Consumption ◽  
Cutting Force ◽  
Tool Life ◽  
Cutting Speed ◽  
Cutting Fluid ◽  
Machining Parameters ◽  
Aisi 316L ◽  
Coated Carbide

Austenitic stainless steel AISI 316L is used in many applications, including chemical industry, nuclear power plants, and medical devices, because of its high mechanical properties and corrosion resistance. Machinability study on the stainless steel is of interest. Toward sustainable manufacturing, this study also includes the power consumption during machining along with other machining responses of cutting force, surface roughness, and tool life. Turning on the stainless steel was performed using coated carbide tool without using cutting fluid. The turning was performed at various cutting speeds (90, 150, and 210 m/min) and feeds (0.10, 0.16, and 0.22 mm/rev). Response surface methodology was adopted in designing the experiments to quantify the effect of cutting speed and feed on the machining responses. It was found that cutting speed was proportional to power consumption and was inversely proportional to tool life, and showed no significant effect on the cutting force and the surface roughness. Feed was proportional to cutting force, power consumption, and surface roughness and was inversely proportional to tool life. Empirical equations developed from the results for all machining responses were shown to be useful in determining the optimum cutting parameters range.

End-Milling Machinability of Inconel 718

1996 ◽  
Vol 210 (1) ◽  
pp. 11-23 ◽  
Author(s):  
M Alauddin ◽  
M A El Baradie ◽  
M S J Hashmi
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Inconel 718 ◽  
End Milling ◽  
Milling Process ◽  
Machining Parameters ◽  
Life Tests ◽  
Life Values ◽  
Published Research ◽  
Carbide Inserts

Most published research works on machining Inconel 718 have been mainly concerned with turning, while the milling process has received little attention due to the complexity of the process. In this paper a series of end-milling experiments of Inconel 718 has been carried out in order to: (a) optimize cutting variables, (b) investigate tool life values and relationships and (c) investigate surface roughness. The machining parameters have been optimized by measuring cutting forces. Tool life tests have been carried out using carbide inserts and the surface roughness has been analysed.

Machinability Investigation of HSLA Steel in Hard Turning with Coated Ceramic Tool: Assessment, Modeling, Optimization and Economic Aspects

2019 ◽  
Vol 18 (04) ◽  
pp. 625-655 ◽  
Author(s):  
Asutosh Panda ◽  
Sudhansu Ranjan Das ◽  
Debabrata Dhupal
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Hard Turning ◽  
Flank Wear ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Ceramic Tool ◽  
Life Estimation

The present study addresses the machinability investigation in finish dry hard turning of high strength low alloy steel with coated ceramic tool by considering cutting speed, feed and depth of cut as machining parameters. The technological parameters like surface roughness, flank wear, chip morphology and economical feasibility have been considered to investigate the machinability performances. Twenty seven set of trials according to full factorial design of experiments are performed and analysis of variance, multiple regression method, Taguchi method, desirability function approach and finally Gilbert’s approach are subsequently applied for parametric influence study, mathematical modeling, multi-response optimization, tool life estimation and economic analysis. Results indicated that feed and cutting speed are the most significant controlled as well as dominant factors for hard turning operation if the minimization of the machined surface roughness and tool flank wear is considered. Abrasions, adhesion followed by plastic deformation have been observed to be the principal wear mechanism for tool life estimation and observed tool life for coated ceramic insert is 47[Formula: see text]min under optimum cutting conditions. The total machining cost per part is ensued to be lower ($0.29 only) as a consequence of higher tool life, reduction in downtime and enhancement in savings, which finds economical benefits in hard turning. The current work demonstrates the substitution of conventional, expensive and slow cylindrical grinding process, and proposes the most expensive CBN tool alternative using coated ceramic tools in hard turning process considering techno-economical and ecological aspects.

Machining nickel base superalloys: Inconel 718

1998 ◽  
Vol 212 (3) ◽  
pp. 195-206 ◽  
Author(s):  
I A Choudhury ◽  
M A El-Baradie
Keyword(s):  
Tool Life ◽  
Cutting Forces ◽  
Inconel 718 ◽  
Flank Wear ◽  
Cutting Conditions ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Coated Tools ◽  
Nickel Base ◽  
Better Than

A series of machining experiments of Inconel 718 has been carried out using coated and uncoated carbides. The paper describes the effects of cutting variables (speed, feed and depth of cut) on cutting forces and tool life. Carbide tools in the form of 80° rhomboid shaped inserts without any chip breaker have been used at different cutting conditions. The machining parameters have been optimized by measuring cutting forces. Flank wear was considered as the criterion for tool life. A comparison between the uncoated and coated tools has been made using the Taylor's tool life exponents of speed, feed and depth of cut. The tool life of coated tools was not found to be better than that of the uncoated tools.

Reliability Analysis of Cutting Tools

1979 ◽  
Vol 101 (2) ◽  
pp. 185-190 ◽  
Author(s):  
K. Hitomi ◽  
N. Nakamura ◽  
S. Inoue
Keyword(s):  
Tool Wear ◽  
Reliability Analysis ◽  
Tool Life ◽  
Metal Cutting ◽  
Cutting Tools ◽  
Reliability Function ◽  
Statistical Distribution ◽  
Experimental Results ◽  
Machining Parameters ◽  
Cutting Experiments

This paper is concerned with the reliability analysis of tool life based on the tool-wear values obtained from metal cutting experiments. From experimental results, a statistical distribution of tool wear was decided, and the distribution of tool life and the reliability function of cutting tools were derived. Further, it was shown that the reliability of cutting tools at a certain time was easily calculated from machining parameters and tool-wear limits by the use of reliability function.

Prediction of Cutting Tool Life Based on ACO-BP Meural Network

2013 ◽  
Vol 655-657 ◽  
pp. 1714-1717 ◽  
Author(s):  
Tie Liu Wang ◽  
Xian Ming Chen ◽  
Shui Bin Chen
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Tool Life ◽  
Bp Neural Network ◽  
Cutting Tool ◽  
Back Propagation ◽  
Global Search ◽  
Machining Parameters ◽  
The Cost ◽  
Search Capability

For predicting the tool life combine the ant colony optimization(ACO) with the back propagation (BP) neural networks, use the the ACO to train BP neural network, build the prediction model based ACO-BP neural network. Some disadvantages are overcame in the BP algorithm, such as the low convergence speed, easily falling into local minimum point and weak global search capablity in the prediction process. Satisfies the requirement of global search capability and the robustness of the model. The experiment results show the prediction model has high precision in predicting the tool life. By the prediction model can provide a reasonable basis for planing production schedule and cutting tool requirement, calculating the cost, selecting the machining parameters,etc.

scholarly journals Theoretical and Experimental Investigation Into The Machining Performance in Axial Ultrasonic Vibration–Assisted Cutting of Ti6Al4V

2021 ◽  
Author(s):  
He Sui ◽  
Lifeng Zhang ◽  
Shuang Wang ◽  
Zhaojun Gu
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Influencing Factors ◽  
Ultrasonic Vibration ◽  
Tool Life ◽  
Feed Rate ◽  
Rotation Speed ◽  
Machining Parameters ◽  
Machining Performance ◽  
Cutting Depth

Abstract Axial ultrasonic vibration-assisted cutting (AUVC) has proved to have better machining performance compared with conventional cutting methods; however, the effect of numerous and complex influencing factors on machining performance has not been clearly revealed and a recommended combination of cutting conditions has not been proposed yet, especially for difficult-to-machine material such as Ti6Al4V alloy. This paper focuses on experimental and theoretical investigation into machining performance when cutting Ti6Al4V with the AUVC method. First, a retrospective of the separation characteristics of AUVC is provided and the variable parameter cutting characteristics are demonstrated. We classify the influencing factors on machining performance into four categories: machining parameters, vibration parameters, tool choice, and cooling conditions. The relationship between these factors in terms of their effect on machining performance is established theoretically. Then, it describes experiments to determine the influence of these factors on cutting force, tool life, and surface roughness. For absolute influence, the orders for cutting force, tool life, and surface roughness are respectively cutting depth > amplitude > feed rate > rotation speed, rotation speed > feed rate > amplitude > cutting depth, and feed rate > amplitude > cutting depth > rotation speed. However, for relative influence, the order is unified as: amplitude > feed rate > rotation speed > cutting depth. Finally, it suggests a smaller feed rate, larger amplitude, moderate rotation speed, and smaller cutting depth in addition to a WC tool coated with TiAlN and used under HPC cooling condition for optimal performance of AUVC. This recommendation is based on the theoretical analysis and experimental results of cutting force, surface roughness, and tool life.

scholarly journals Vibration-based tool wear monitoring using Artificial Neural Networks fed by Spectral centroid indicator & RMS of CEEMDAN modes

2021 ◽  
Author(s):  
Mourad NOUIOUA ◽  
Mohamed Lamine BOUHALAIS
Keyword(s):  
Tool Wear ◽  
Tool Life ◽  
Laser Doppler Vibrometer ◽  
Machining Parameters ◽  
Machining Processes ◽  
Limit Value ◽  
Aisi 1045 Steel ◽  
Wear Monitoring ◽  
Artificial Neural ◽  
1045 Steel

Abstract In machining processes various phenomena occur during cutting operation. These phenomena can disturb the production through the reduction of part quality and accuracy. Therefore, a mastery of this cutting phenomena is needed to define the machining parameters and take full advantage of manufacturing process. An easy way to classify these phenomena is by monitoring incontrollable parameters, such as generated temperature and vibration. The acquired vibration signals can provide information regarding tool life, cutting performances and workpiece defects. This paper evaluates the possibility of monitoring the tool life during the turning process of AISI 1045 steel using Laser Doppler Vibrometer (LDV), the surface roughness has been measured along with the tool-wear until reaching its limit value of 300µm. Furthermore, this paper also outlines the application of CEEMDAN technique to process the acquired signals for the monitoring processes. RMS and SCI indicators have been used to describe the wear progress, then, the artificial neural network has been adopted to achieve a real time wear monitoring. The obtained results qualified the SCI indicator and ANN for online monitoring.

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