Analysis of cutting forces and surface roughness in hard turning of AISI 4340 using multilayer coated carbide tool

2014 ◽  
Vol 16 (2) ◽  
pp. 169 ◽  
Author(s):  
S. Basavarajappa ◽  
R. Suresh ◽  
V.N. Gaitonde ◽  
G.L. Samuel
Keyword(s):  
Surface Roughness ◽  
Cutting Forces ◽  
Hard Turning ◽  
Carbide Tool ◽  
Coated Carbide Tool ◽  
Coated Carbide ◽  
Aisi 4340

Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool

Measurement ◽  
2012 ◽  
Vol 45 (7) ◽  
pp. 1872-1884 ◽  
Author(s):  
R. Suresh ◽  
S. Basavarajappa ◽  
G.L. Samuel
Keyword(s):  
Hard Turning ◽  
Carbide Tool ◽  
Aisi 4340 Steel ◽  
Coated Carbide Tool ◽  
4340 Steel ◽  
Coated Carbide ◽  
Aisi 4340

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.

Wear mechanism of a coated carbide tool in cryogenic machining of AISI 4340

2019 ◽  
Vol 72 (4) ◽  
pp. 509-514 ◽  
Author(s):  
Shalina Sheik Muhamad ◽  
Jaharah A. Ghani ◽  
Che Hassan Che Haron ◽  
Hafizal Yazid
Keyword(s):  
Wear Mechanisms ◽  
Cutting Speed ◽  
Optical Microscope ◽  
Carbide Tool ◽  
Cryogenic Machining ◽  
Content Type ◽  
Coated Carbide Tool ◽  
Adhesion Wear ◽  
Coated Carbide ◽  
Aisi 4340

Purpose The purpose of this study is to investigate wear mechanisms of a multi-layered TiAlN/AlCrN-coated carbide tool during the milling of AISI 4340 steel under cryogenic machining. Design/methodology/approach The wear progression was measured using a toolmaker microscope and an optical microscope. Later, a field emission scanning electron microscope and energy-dispersive X-ray analysis were used to investigate the wear mechanisms in detail. Findings A comprehensive analysis revealed that the main causes of tool wear mechanisms were abrasion and adhesion wear on the flank face. Originality/value The investigations presented in this paper may be used by the machining industry to prolong the tool life at higher cutting speed by the application of liquid nitrogen.

Study of Surface Quality and Cutting Parameter Optimization in Side Milling CFRP With Diamond Coated Carbide Tool

2016 ◽  
Author(s):  
Weiwei Liu ◽  
Yuan Hu ◽  
Jianwu Zhou ◽  
Renjie Lu ◽  
Chengzhou Wang
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Carbide Tool ◽  
Side Milling ◽  
Coated Carbide Tool ◽  
Conflicting Objectives ◽  
Cutting Parameter Optimization ◽  
Optimal Cutting Parameters ◽  
Coated Carbide

Composite machining is one of the hot researches currently, and optimal cutting parameters are particularly important to get ideal surface and reduce processing cost of workpiece. By comparison, the present paper selects the surface root mean square deviation Sq as the three-dimensional evaluation parameter of surface roughness to reflect the special appearance after cutting accurately. The single-factor experiment and orthogonal experiment were conducted to study the machining defects emerged and effect of parameters on surface roughness when side milling CFRP (Carbon Fiber Reinforced Plastics) with diamond coated carbide tool. The mapping relationship between cutting parameters and surface roughness was established based on the experiment results. Then, the cutting parameters were optimized by using genetic algorithm with two conflicting objectives: material removal rate and surface roughness. The experiment results show that the proposed method is feasible and effective, and can provide references for the actual processing of CFRP.

Measurement of surface roughness through RSM: effect of coated carbide tool on 6061-t4 aluminium

2010 ◽  
Vol 4 (2) ◽  
pp. 136 ◽  
Author(s):  
Mukesh Kumar Barua ◽  
Jyoti Sagar Rao ◽  
S.P. Anbuudayasankar ◽  
Tom Page
Keyword(s):  
Surface Roughness ◽  
Carbide Tool ◽  
Coated Carbide Tool ◽  
Coated Carbide
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