scholarly journals Forces in hard turning of 51CrV4 with wiper cutting tool

2006 ◽  
Vol 11 (5) ◽  
pp. 501-506 ◽  
Author(s):  
Xinfeng He ◽  
Su Wu ◽  
Kratz Hubert
Keyword(s):  
Hard Turning ◽  
Cutting Tool

Surface Roughness and Cutting Force Components Evaluation in Hard Turning by Differently Shaped Cutting Tools

2016 ◽  
Vol 862 ◽  
pp. 26-32 ◽  
Author(s):  
Michaela Samardžiová
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Hard Turning ◽  
Cutting Tool ◽  
Single Point ◽  
Machining Process ◽  
Tool Geometry ◽  
Machined Surface ◽  
Cutting Force Components ◽  
Force Components

There is a difference in machining by the cutting tool with defined geometry and undefined geometry. That is one of the reasons of implementation of hard turning into the machining process. In current manufacturing processes is hard turning many times used as a fine finish operation. It has many advantages – machining by single point cutting tool, high productivity, flexibility, ability to produce parts with complex shapes at one clamping. Very important is to solve machined surface quality. There is a possibility to use wiper geometry in hard turning process to achieve 3 – 4 times lower surface roughness values. Cutting parameters influence cutting process as well as cutting tool geometry. It is necessary to take into consideration cutting force components as well. Issue of the use of wiper geometry has been still insufficiently researched.

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.

Cutting Tool Failure and Surface Finish Analysis in Pulsating MQL-Assisted Hard Turning

2020 ◽  
Vol 20 (4) ◽  
pp. 1274-1291
Author(s):  
Soumikh Roy ◽  
Ramanuj Kumar ◽  
Ashok Kumar Sahoo ◽  
Amlana Panda
Keyword(s):  
Surface Finish ◽  
Hard Turning ◽  
Cutting Tool ◽  
Tool Failure

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.

Wear mechanisms of several cutting tool materials in hard turning of high carbon–chromium tool steel

2014 ◽  
Vol 70 ◽  
pp. 148-154 ◽  
Author(s):  
M.A. Shalaby ◽  
M.A. El Hakim ◽  
Magdy M. Abdelhameed ◽  
J.E. Krzanowski ◽  
S.C. Veldhuis ◽  
...  
Keyword(s):  
Tool Steel ◽  
Wear Mechanisms ◽  
Hard Turning ◽  
Cutting Tool ◽  
High Carbon ◽  
Tool Materials ◽  
Cutting Tool Materials

scholarly journals Analysis of The Tool-Chip Interface Temperature In Cryogenic Hard Turning of Aisi D6 Tool Steel

2021 ◽  
Author(s):  
Edmilson Dantas de Lima ◽  
Anderson Clayton Alves De Melo ◽  
Adilson José de Oliveira ◽  
Júlio César Giubilei Milan ◽  
Álisson Rocha Machado
Keyword(s):  
Tool Wear ◽  
Liquid Nitrogen ◽  
Tool Steel ◽  
Hard Turning ◽  
Cutting Tool ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Promising Alternative ◽  
Cutting Tool Wear

Abstract Hard turning is considered a strong candidate to partially replace grinding in finishing operations. However, as in the grinding operation, hard turning produces high temperatures that contributes to accelerate the cutting tool wear. In order to minimize this effect, cutting fluids can be applied as an alternative, even when PCBN inserts are used as cutting tools. However, there are many drawbacks associated with the use of cutting fluids, particularly those of mineral base, as they are hazardous to the environment. In this context, the need for more eco-friendly cutting fluids is growing and liquid nitrogen (LN2) offers a promising alternative. Previous studies have shown that LN2 can significantly reduce the cutting tool wear rate in comparison with other cooling strategies, and this is normally attributed to a reduction in the tool-chip interface temperature. However, investigations on the tool-chip interface temperature in cryogenic machining are scarce in the literature, particularly with regard to the turning of tool steels, and this study was performed to partially fill this gap. The tool-chip interface temperature during the turning of quenched and tempered AISI D6 tool steel, under dry conditions and using LN2, was investigated. A tool-workpiece thermocouple system was developed for this purpose and calibrated using a data acquisition system based on the low-cost Arduino Uno platform. In the turning tests, liquid nitrogen was delivered at the tool flank face of PCBN inserts at three cutting speeds with a constant feed rate and depth of cut. The results showed that LN2 was effective in reducing the tool-chip interface temperature at the lowest cutting speed; however, when this cutting parameter was increased, the reduction in the interface temperature was minimal as compared with the dry condition.

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