Predictive modeling for flank wear progression of coated carbide tool in turning hardened steel under practical machining conditions

2014 ◽  
Vol 76 (5-8) ◽  
pp. 1185-1201 ◽  
Author(s):  
Satish Chinchanikar ◽  
S. K. Choudhury
2019 ◽  
Vol 1 (9) ◽  
Author(s):  
Feng Gong ◽  
Jun Zhao ◽  
Xiuying Ni ◽  
Changxia Liu ◽  
Junlong Sun ◽  
...  

2017 ◽  
Vol 749 ◽  
pp. 178-184 ◽  
Author(s):  
Israel Martinez ◽  
Ryutaro Tanaka ◽  
Yasuo Yamane ◽  
Katsuhiko Sekiya ◽  
Keiji Yamada ◽  
...  

This study reports an experimental investigation about the wear behavior of TiN and TiCN coated carbide tools during the face milling of pearlitic and ferritic ductile cast iron. Pearlitic ductile cast iron caused the highest cutting forces and flank wear in both TiN and TiCN coated tools. Due to its protective effect, the TiCN coated carbide tool outperformed the TiN coated carbide tool regarding flank wear. The main issue when face milling ferritic ductile cast iron with TiN coated tools was notching wear. The principal reason for notch wear was pointed as adhesive wear caused for the high tendency of ferrite to adhere on the tool. The results demonstrated that the TiCN coating did not showed notching wear when face milling ferritic ductile cast iron, therefore a good choice of coating material can prevent notching wear.


Author(s):  
Lalatendu Dash ◽  
Smita Padhan ◽  
Anshuman Das ◽  
Sudhansu Ranjan Das

The present research addresses the machinability of hardened die steel (AISI D3, 61HRC) in hard turning using multilayer (TiCN/Al2O3/TiN) coated carbide tool under nanofluid based minimum quantity lubrication-cooling condition, where no previous data are available. Power consumption, flank wear, chip morphology and surface integrity (microhardness, residual stress, white layer formation, machined surface morphology, and surface roughness) are considered as technological performance characteristics to evaluate the machinability. Combined approach of central composite design - analysis of variance, response surface methodology and desirability function analysis have been employed respectively for experimental investigation, predictive modelling and multi-response optimization. With a motivational philosophy of “Go Green-Think Green-Act Green”, the work also deals with energy saving carbon footprint analysis and sustainability assessment to recognize the green manufacturing in the context of safer and cleaner production. under environmental-friendly nanofluid assisted minimum quantity lubrication condition. The quantitative analysis revealed that the cutting speed influenced the power consumption during hard machining (75.78%) and flank wear of coated carbide tool (45.67%); feed rate impacted the surface finish of the machined part (68.8%) significantly. Saw tooth shapes of chip produced due to cyclic cracking. Due to low percentage contribution of error (5.32% to Ra, 6.64% to VB, and 7.79% to Pc), a higher correlation coefficient (R2) was obtained with the quadratic regression model, which showed values of 0.9, 0.88 and 0.92 for surface roughness, flank wear, and power consumption, respectively. Optimization with the highest desirability (0.9173) resulted the optimum machining conditions under NFMQL at the cutting speed of 57 m/min, depth of cut 0.1 mm, feed of 0.07 mm/rev, and insert’s nose radius of 0.4 mm. As a result, under NFMQL tool life was improved by 30.8% and 22.6% in respect of flank wear and surface roughness respectively than when machining with MQL technique by adapting the optimum machining condition. Therefore, using hard nanoparticles-reinforced cutting fluid under minimum quantity lubrication condition in practical manufacturing becomes very promising to improve sustainability.


2021 ◽  
Author(s):  
Nurfarahin Zainuddin ◽  
Safian Sharif ◽  
Mohd Azlan Suhaimi ◽  
Amrifan Saladin Mohruni ◽  
Muhammad Yanis ◽  
...  

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