scholarly journals FEM Modelling of Tool Wear in Hard Turning Operations

2021 ◽  
Vol 1190 (1) ◽  
pp. 012023
Author(s):  
Cristian Cappellini ◽  
Franco Concli
Keyword(s):  
Tool Wear ◽  
Hard Turning ◽  
Turning Operations ◽  
Fem Modelling

Analysis on Finish Hard Turning of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si Alloy

2009 ◽  
Vol 626-627 ◽  
pp. 225-230 ◽  
Author(s):  
Wei Wei Ming ◽  
Ming Chen ◽  
Bin Rong
Keyword(s):  
Corrosion Resistance ◽  
Elevated Temperature ◽  
Tool Wear ◽  
Hard Turning ◽  
Density Ratio ◽  
High Strength ◽  
Excellent Performance ◽  
Good Corrosion Resistance ◽  
Tool Wear Mechanism ◽  
Finish Hard Turning

Titanium alloys are extensively applied in aerospace, automotive, biomedical, and chemical industries owing to their excellent performance combining high strength-to-density ratio, good corrosion resistance, and high strength at elevated temperature. Ti-6.5Al-3.5Mo-1.5Zr-0.3Si (TC11) alloys are used to replace the most common Ti-6Al-4V in some important applications such as some parts in aerospace engine. The purpose of this paper is to evaluate the machinability of TC11 alloys in the finish hard turning conditions. The paper presents the machinability results of TC11 alloys compared with Ti-6Al-4V, and analyzes the variables such as cutting force, surface integrity, and tool wear mechanism in the experiments.

scholarly journals Artificial neural network based tool wear estimation on dry hard turning processes of AISI4140 steel using coated carbide tool

2017 ◽  
Vol 65 (4) ◽  
pp. 553-559 ◽  
Author(s):  
D. Rajeev ◽  
D. Dinakaran ◽  
S.C.E. Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Tool Wear ◽  
Hard Turning ◽  
Cutting Tool ◽  
Carbide Tool ◽  
Online Tool ◽  
Coated Carbide Tool ◽  
Tool Wear Estimation ◽  
Coated Carbide

AbstractNowadays, finishing operation in hardened steel parts which have wide industrial applications is done by hard turning. Cubic boron nitride (CBN) inserts, which are expensive, are used for hard turning. The cheaper coated carbide tool is seen as a substitute for CBN inserts in the hardness range (45–55 HRC). However, tool wear in a coated carbide tool during hard turning is a significant factor that influences the tolerance of machined surface. An online tool wear estimation system is essential for maintaining the surface quality and minimizing the manufacturing cost. In this investigation, the cutting tool wear estimation using artificial neural network (ANN) is proposed. AISI4140 steel hardened to 47 HRC is used as a work piece and a coated carbide tool is the cutting tool. Experimentation is based on full factorial design (FFD) as per design of experiments. The variations in cutting forces and vibrations are measured during the experimentation. Based on the process parameters and measured parameters an ANN-based tool wear estimator is developed. The wear outputs from the ANN model are then tested. It was observed that as the model using ANN provided quite satisfactory results, and that it can be used for online tool wear estimation.

scholarly journals Cutting Mechanics and Surface Finish for Turning with Differently Shaped CBN Tools

2017 ◽  
Vol 64 (3) ◽  
pp. 347-357
Author(s):  
Krzysztof Żak
Keyword(s):  
Surface Roughness ◽  
Hard Turning ◽  
Cutting Parameters ◽  
Material Distribution ◽  
Roughness Parameters ◽  
Turning Operations ◽  
Cutting Power ◽  
Finish Turning ◽  
Corner Radius ◽  
Relevant Material

Abstract In this paper, the basic cutting characteristics such as cutting forces, cutting power and its distribution, specific cutting energies were determined taking into account variable tool corner radius ranging from 400 to 1200 µm and constant cutting parameters typical for hard turning of a hardened 41Cr4 alloy steel of 55±1 HRC hardness. Finish turning operations were performed using chamfered CBN tools. Moreover, selected roughness profiles produced for different tool corner radius were compared and appropriate surface roughness parameters were measured. The measured values of Ra and Rz roughness parameters are compared with their theoretical values and relevant material distribution curves and bearing parameters are presented.

INVESTIGATION OF WIPER INSERTS EFFECTS IN TURNING AND MILLING PROCESSES

2021 ◽  
pp. 2150111
Author(s):  
MURAT KIYAK
Keyword(s):  
Surface Roughness ◽  
Cost Saving ◽  
Tool Wear ◽  
Feed Rate ◽  
Turning Process ◽  
Nose Radius ◽  
Turning Operations ◽  
Effective Factors ◽  
Milling Operations ◽  
The Many

The surface roughness is a crucial factor in machining methods. The most effective factors on surface roughness are feed rate and tool nose radius. Due to the many advantages of wiper (multi-nose radius) inserts, their importance and use has been increasing recently. The purpose of this paper is to investigate the effect of wiper inserts on surface roughness and tool wear. In this study, conventional inserts and wiper inserts were experimentally compared separately in milling and turning operations. Compared to conventional inserts, the surface roughness values obtained using wiper inserts improved by 33% in turning operations and approximately 40% in milling operations. It was observed that the production time in the turning process was reduced by about 25% in the case of using wiper inserts compared to the use of conventional inserts. In milling, this ratio was determined to be approximately 43% due to the fact that it has multiple cutting edge. It has been observed that the use of wiper inserts in machining methods creates a significant time and cost saving advantage.

Tool wear and chip analysis after the hard turning of AISI D6 steel assisted by LN2

2019 ◽  
Vol 23 (6) ◽  
pp. 886-905 ◽  
Author(s):  
Welber Vasconcelos Leadebal ◽  
Anderson Clayton Alves De Melo ◽  
Adilson José De Oliveira ◽  
Nicolau Apoena Castro
Keyword(s):  
Tool Wear ◽  
Hard Turning ◽  
Aisi D6 Steel ◽  
Chip Analysis

Designing and implementation of a novel online adaptive control with optimization technique in hard turning

2020 ◽  
pp. 095965182095219
Author(s):  
Vahid Pourmostaghimi ◽  
Mohammad Zadshakoyan
Keyword(s):  
Adaptive Control ◽  
Tool Wear ◽  
Hard Turning ◽  
Cutting Tool ◽  
Optimization Technique ◽  
Cutting Parameters ◽  
Numerical Control ◽  
Machining Process ◽  
Machining Parameters ◽  
Optimization Methodology

Determination of optimum cutting parameters is one of the most essential tasks in process planning of metal parts. However, to achieve the optimal machining performance, the cutting parameters have to be regulated in real time. Therefore, utilizing an intelligent-based control system, which can adjust the machining parameters in accordance with optimal criteria, is inevitable. This article presents an intelligent adaptive control with optimization methodology to optimize material removal rate and machining cost subjected to surface quality constraint in finish turning of hardened AISI D2 considering the real condition of the cutting tool. Wavelet packet transform of cutting tool vibration signals is applied to estimate tool wear. Artificial intelligence techniques (artificial neural networks, genetic programming and particle swarm optimization) are used for modeling of surface roughness and tool wear and optimization of machining process during hard turning. Confirmatory experiments indicated that the efficiency of the proposed adaptive control with optimization methodology is 25.6% higher compared to the traditional computer numerical control turning systems.

scholarly journals An experimental study on the effect of tool geometry on tool wear and surface roughness in hard turning

2020 ◽  
Vol 12 (9) ◽  
pp. 168781402095988
Author(s):  
Pham Minh Duc ◽  
Le Hieu Giang ◽  
Mai Duc Dai ◽  
Do Tien Sy
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Inclination Angle ◽  
Hard Turning ◽  
Rake Angle ◽  
Machining Process ◽  
Tool Geometry ◽  
Standard Tool ◽  
Inclination Angles ◽  
Mixed Ceramic

The main purpose of this study is to investigate the influence of tool geometry (cutting edge angle, rake angle, and inclination angle) and to optimize tool wear and surface roughness in hard turning of AISI 1055 (52HRC) hardened steel by using TiN coated mixed ceramic inserts. The results show that the inclination angle is the major factor affecting the tool wear and the surface roughness in hard turning. With the increase in negative rake and inclination angles, the tool wear decreases, and the surface roughness increases. However, the surface roughness will decrease when the inclination angle increases to overpass a certain limit. This is a new and significant point in the research of the hard turning process. From this result, the large negative inclination angle (λ = −10°) should be applied to reduce the surface roughness and the tool wear simultaneously. With the optimal cutting tool angles in the research, the hard machining process is improved remarkably with decreases of surface roughness and tool wear 8.3% and 41.3%, respectively in comparison with the standard tool angles. And the proposed tool-post design approach brings an effective method to change the tool insert angles using standard tool-holders to improve hard or other difficult-to-cut materials turning quality.

Sign in / Sign up

Export Citation Format

Share Document