scholarly journals Prediction of Surface Roughness using Sensor Fusion Regression Model

2019 ◽  
Vol 8 (12S) ◽  
pp. 538-540
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Regression Model ◽  
Sensor Fusion ◽  
Cutting Temperature ◽  
Machining Parameters ◽  
Direct Influence ◽  
Machining Processes ◽  
H13 Steel

Surface roughness decides the quality of machined components during machining processes. Output parameters namely cutting temperature, cutting force, tool wear, vibration etc. have direct influence on surface roughness of machined components. It is anticipated that better prediction would be possible if the above mentioned parameters are collectively considered with machining parameters. In this investigation, an effort was made to fuse machining parameters with cutting temperature to predict surface roughness while machining H13 steel. The developed regression model was tested for its ability to predict surface quality. The results proved that the developed sensor fusion regression model can be used for better prediction of cutting performance

Sensor Fusion Strategy in the Monitoring of Cutting Tool Wear

2006 ◽  
Vol 306-308 ◽  
pp. 727-732 ◽  
Author(s):  
Muslim Mahardika ◽  
Zahari Taha ◽  
Djoko Suharto ◽  
Kimiyuki Mitsui ◽  
Hideki Aoyama
Keyword(s):  
Tool Wear ◽  
Sensor Fusion ◽  
Cutting Tool ◽  
Fusion Technology ◽  
Machining Processes ◽  
Fusion Strategy ◽  
Cutting Tool Wear ◽  
Single Sensor ◽  
Paper Sensor

Cutting tool wear is a major problem in machining processes. It has a great effect on the quality of a workpiece. Thus, monitoring cutting tool wear is very important in order to maintain the workpiece quality as well to reduce production rate and production time. The use of a single sensor in a monitoring system may not be accurate to detect cutting tool wear. In this paper, sensor fusion technology is introduced for monitoring cutting tool wear.

scholarly journals Estimation of Tool Wear and Surface Roughness Development Using Deep Learning and Sensors Fusion

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5338
Author(s):  
Pao-Ming Huang ◽  
Ching-Hung Lee
Keyword(s):  
Surface Roughness ◽  
Deep Learning ◽  
Tool Wear ◽  
Sensor Fusion ◽  
Sensor Selection ◽  
Numerical Control ◽  
Estimation Accuracy ◽  
Machining Parameters ◽  
Estimation Model ◽  
Selection Analysis

This paper proposes an estimation approach for tool wear and surface roughness using deep learning and sensor fusion. The one-dimensional convolutional neural network (1D-CNN) is utilized as the estimation model with X- and Y-coordinate vibration signals and sound signal fusion using sensor influence analysis. First, machining experiments with computer numerical control (CNC) parameters are designed using a uniform experimental design (UED) method to guarantee the variety of collected data. The vibration, sound, and spindle current signals are collected and labeled according to the machining parameters. To speed up the degree of tool wear, an accelerated experiment is designed, and the corresponding tool wear and surface roughness are measured. An influential sensor selection analysis is proposed to preserve the estimation accuracy and to minimize the number of sensors. After sensor selection analysis, the sensor signals with better estimation capability are selected and combined using the sensor fusion method. The proposed estimation system combined with sensor selection analysis performs well in terms of accuracy and computational effort. Finally, the proposed approach is applied for on-line monitoring of tool wear with an alarm, which demonstrates the effectiveness of our approach.

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.

Diamond Turning of Special Stainless Steel by Applying Ultrasonic Vibration with Gas Shield

2006 ◽  
Vol 532-533 ◽  
pp. 57-60 ◽  
Author(s):  
Yuan Liang Zhang ◽  
Zhi Min Zhou ◽  
Zhi Hui Xia
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Tool Wear ◽  
Ultrasonic Vibration ◽  
Diamond Tool ◽  
Flank Wear ◽  
Cutting Temperature ◽  
Cutting Parameters ◽  
Diamond Turning

Ultrasonic vibration is applied to diamond turning of special stainless steel to decrease diamond tool wear and improve the surface quality of the workpieces. It reviews the principle of diamond turning of special stainless steel by applying ultrasonic vibration combined with gas shield. Compared with the ordinary machining method, cutting temperature and cutting force are greatly reduced when machining by application of ultrasonic vibration, and the appetency between a diamond tool and Ferrous atom of a workpiece is also minimized as gas shield application. The Experiments of cutting special stainless steel workpieces show that the surface roughness Ra is less than 0.15μm and flank wear-width is less than 5μm when cutting distance is up to 2000m. It takes research on the effect of cutting parameters to surface roughness and tool wear. The experiment result shows that the amplitude is the most important factor which effects tool wear and surface roughness most.

Investigation on Precision Turning of Titanium Alloys

2012 ◽  
Vol 622-623 ◽  
pp. 399-403 ◽  
Author(s):  
Tarun Thomas George ◽  
J. Venugopal ◽  
M. Anthony Xavior ◽  
R. Vinayagamoorthy
Keyword(s):  
Surface Roughness ◽  
Titanium Alloys ◽  
Working Conditions ◽  
Cutting Temperature ◽  
Machining Process ◽  
Machining Processes ◽  
Machined Surface ◽  
Percentage Contribution ◽  
Precision Turning

The quality of a machined surface is becoming more and more important to satisfy the increasing demands of sophisticated component performance, longevity, and reliability. The objective of this paper is to analyze the performance of precision turning using conventional lathe on Ti6Al4V under dry working conditions. Various parameters that affect the machining processes were identified and a consensus was reached regarding its values. The proposed work is to perform machining under the selected levels of conditions and parameters and to estimate the, cutting temperature and surface roughness generated as the result of the machining process. ANOVA is used to find the percentage contribution of each parameter to the surface roughness and cutting temperature.

Monitoring of Cutting Conditions with Dry Cutting on CNC Turning Machine

2010 ◽  
Vol 443 ◽  
pp. 382-387 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Suthas Ratanakuakangwan
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Cutting Forces ◽  
Cutting Temperature ◽  
Cutting Conditions ◽  
Cutting Condition ◽  
Nose Radius ◽  
Dry Cutting ◽  
Cnc Turning ◽  
Coated Carbide

This paper presents the additional work of the previous research in order to verify the previously obtained cutting condition by using the different cutting tool geometries. The effects of the cutting conditions with the dry cutting are monitored to obtain the proper cutting condition for the plain carbon steel with the coated carbide tool based on the consideration of the surface roughness and the tool life. The dynamometer is employed and installed on the turret of CNC turning machine to measure the in-process cutting forces. The in-process cutting forces are used to analyze the cutting temperature, the tool wear and the surface roughness. The experimentally obtained results show that the surface roughness and the tool wear can be well explained by the in-process cutting forces. Referring to the criteria, the experimentally obtained proper cutting condition is the same with the previous research except the rake angle and the tool nose radius.

Schneidkantenpräparation von VHM-Mikrofräsern*/Cutting edge preparation of cemented carbide micro milling tools – A comparison of different fine machining processes

2015 ◽  
Vol 105 (11-12) ◽  
pp. 805-811
Author(s):  
E. Uhlmann ◽  
D. Oberschmidt ◽  
A. Löwenstein ◽  
M. Polte ◽  
I. Winker
Keyword(s):  
Tool Wear ◽  
Milling Process ◽  
Cutting Edge ◽  
Micro Milling ◽  
Machining Processes ◽  
Process Reliability ◽  
Cutting Edge Preparation ◽  
Milling Tools ◽  
Edge Preparation

Die Prozesssicherheit beim Mikrofräsen lässt sich mit einer gezielten Schneidkantenverrundung erheblich steigern. Dabei werden durch verschiedene Präparationstechnologien unterschiedliche Geometrien und Einflüsse auf den Fräsprozess erzeugt. Der Fachbeitrag behandelt den Einsatz präparierter Mikrowerkzeuge in Zerspanversuchen, in denen auf die Zerspankräfte, den Verschleiß sowie die Oberflächengüten eingegangen wird.   Process reliability in micro milling can be increased by a defined cutting edge preparation. Different cutting edge preparations cause different effects on tool behavior in the downstream micro milling process. In this paper, the process forces, the tool wear and the surface quality of prepared micro milling tools are characterized in cutting tests.

Machining

2013 ◽  
pp. 213-270
Keyword(s):  
Electron Beam ◽  
Tool Wear ◽  
Electrical Discharge ◽  
Cutting Fluids ◽  
Machining Parameters ◽  
Machining Processes ◽  
Wire Cutting ◽  
Grinding Operations ◽  
Conventional Machining

Abstract This chapter covers the practical aspects of machining, particularly for turning, milling, drilling, and grinding operations. It begins with a discussion on machinability and its impact on quality and cost. It then describes the dimensional and surface finish tolerances that can be achieved through conventional machining methods, the mechanics of chip formation, the factors that affect tool wear, the selection and use of cutting fluids, and the determination of machining parameters based on force and power requirements. It also includes information on nontraditional machining processes such as electrical discharge, abrasive jet, and hydrodynamic machining, laser and electron beam machining, ultrasonic impact grinding, and electrical discharge wire cutting.

scholarly journals Findings of performance evaluation of EDM for different materials of electrodes and work pieces- a review

2018 ◽  
Vol 7 (4.5) ◽  
pp. 542
Author(s):  
Harshalkumar R. Mundane ◽  
Dr. A. V. Kale ◽  
Dr. J. P. Giri
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Performance Measure ◽  
Machining Process ◽  
Machining Parameters ◽  
Spark Erosion ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

EDM (Spark erosion) is non-conventional machining process which uses as removing unwanted material by electrical spark erosion. EDM Machining parameters affecting to the performance and the industries goal is to produce high quality of product with less time consuming and cost. To achieve these goals, optimizing the machining parameters such as pulse on time, pulse off time, cutting speed, depth of cut, duty cycle, arc gap, voltage etc. The performance measure of EDM is calculated on the basis of Material Remove Rate(MRR), Tool Wear Rate(TWR), and Surface Roughness(SR).The main objective of present work is to investigate of the influence of input EDM (Electro Discharge Machining) parameters on machining characteristics like surface roughness and the effects of various EDM process parameters such as pulse on time, pulse off time, servo voltage, peak current, dielectric flow rate, on different process response parameters such as material removal rate (MRR), surface roughness (Ra), Kerf (width of Cut), tool wear ratio(TWR)and surface integrity factors. In this paper few selected research paper related to Die-sinker EDM with effect of MRR, TWR, surface roughness (SR) and work piece material have been discussed.   

Sign in / Sign up

Export Citation Format

Share Document