scholarly journals Influence of Previous Structure on Laser Surface Hardening of AISI 1045 Steel.

1995 ◽  
Vol 35 (11) ◽  
pp. 1394-1399 ◽  
Author(s):  
V. López ◽  
B. Fernández ◽  
J. Ma. Belló ◽  
J. Ruiz ◽  
F. Zubiri
2019 ◽  
Vol 31 (3) ◽  
pp. 1091
Author(s):  
Chi-Liang Kung ◽  
Hao-En Shih ◽  
Chao-Ming Hsu ◽  
Cheng-Yi Chen

2017 ◽  
Vol 143 ◽  
pp. 1183-1190 ◽  
Author(s):  
Bang-ping Gu ◽  
Xiong Hu ◽  
Li Zhao ◽  
De-jun Kong ◽  
Zhen-sheng Yang ◽  
...  

2011 ◽  
Vol 486 ◽  
pp. 262-265
Author(s):  
Amit Kohli ◽  
Mudit Sood ◽  
Anhad Singh Chawla

The objective of the present work is to simulate surface roughness in Computer Numerical Controlled (CNC) machine by Fuzzy Modeling of AISI 1045 Steel. To develop the fuzzy model; cutting depth, feed rate and speed are taken as input process parameters. The predicted results are compared with reliable set of experimental data for the validation of fuzzy model. Based upon reliable set of experimental data by Response Surface Methodology twenty fuzzy controlled rules using triangular membership function are constructed. By intelligent model based design and control of CNC process parameters, we can enhance the product quality, decrease the product cost and maintain the competitive position of steel.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eduardo da Rosa Vieira ◽  
Luciano Volcanoglo Biehl ◽  
Jorge Luis Braz Medeiros ◽  
Vagner Machado Costa ◽  
Rodrigo Jorge Macedo

AbstractQuench hardening aims at the microstructural transformation of steels in order to improve hardness and mechanical strength. The aim phase is, in most cases, the martensite. It is necessary to heat the material until it obtains its austenitization and quenching by immersion in a fluid. Currently, it is common to use watery polymeric solutions in this procedure. These fluids, which are the mixture of polymers in water, vary their thermal exchange capacity depending on the concentrations applied. The increase in concentration minimizes the removal of heat from the part, reducing the formation capacity of martensite, and developing a lower hardness and strong steel. In this work, microstructural characteristics and properties of AISI 1045 steel quenched in solutions based on polyvinylpyrrolidone (PVP) in 10, 15, 20, and 25% concentration were evaluated. The microstructural characterization quantified the percentage of the phases in each concentration, demonstrating a reduction of martensite as the concentrations were high. The investigation of the samples by x-ray diffraction confirmed the absence of austenite retained in the material. Furthermore, a microhardness scale between the core and the surface was constructed, in which a reduction gradient of the indices of this property towards the core of the sample was evidenced.


Author(s):  
L. Orazi ◽  
A. Rota ◽  
B. Reggiani

AbstractLaser surface hardening is rapidly growing in industrial applications due to its high flexibility, accuracy, cleanness and energy efficiency. However, the experimental process optimization can be a tricky task due to the number of involved parameters, thus suggesting for alternative approaches such as reliable numerical simulations. Conventional laser hardening models compute the achieved hardness on the basis of microstructure predictions due to carbon diffusion during the process heat thermal cycle. Nevertheless, this approach is very time consuming and not allows to simulate real complex products during laser treatments. To overcome this limitation, a novel simplified approach for laser surface hardening modelling is presented and discussed. The basic assumption consists in neglecting the austenite homogenization due to the short time and the insufficient carbon diffusion during the heating phase of the process. In the present work, this assumption is experimentally verified through nano-hardness measurements on C45 carbon steel samples both laser and oven treated by means of atomic force microscopy (AFM) technique.


2021 ◽  
Vol 1070 (1) ◽  
pp. 012107
Author(s):  
Ganesh Dongre ◽  
Avadhoot Rajurkar ◽  
Ramesh Gondil ◽  
Nandan Jaju

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