Adaptive Neuro Fuzzy Inference System to Predict Material Removal Rate during Cryo-Treated Electric Discharge Machining

Inference System ◽

Prediction of Material Removal Rate in Rotary Tool Electric Discharge Machining Using Adaptive Neuro- Fuzzy Inference System

PsycEXTRA Dataset ◽

10.1037/e583142013-002 ◽

2012 ◽

Author(s):

Umesh Kumar Vishwakarma ◽

Akshay Dvivedi ◽

Pradeep Kumar

Keyword(s):

Material Removal Rate ◽

Electric Discharge ◽

Fuzzy Inference System ◽

Material Removal ◽

Fuzzy Inference ◽

Removal Rate ◽

Inference System ◽

Rotary Tool ◽

An Adaptive Neuro-Fuzzy Inference System modeling for material removal rate in stationary ultrasonic drilling of sillimanite ceramic

Expert Systems with Applications ◽

10.1016/j.eswa.2010.02.054 ◽

2010 ◽

Vol 37 (8) ◽

pp. 5590-5598 ◽

Cited By ~ 23

Author(s):

Simranpreet Singh Gill ◽

Jagdev Singh

Keyword(s):

Material Removal Rate ◽

Fuzzy Inference System ◽

Material Removal ◽

Fuzzy Inference ◽

Removal Rate ◽

System Modeling ◽

Inference System ◽

Ultrasonic Drilling ◽

2020 Advances in Science and Engineering Technology International Conferences (ASET) ◽

Prediction on Material Removal Rate in Electrical Discharge Machining Based Upon Adaptive Neuro-Fuzzy Inference System

10.1109/aset48392.2020.9118176 ◽

2020 ◽

Author(s):

Laith Abdullah Al-Juboori ◽

Shukry Hamed

Keyword(s):

Material Removal Rate ◽

Fuzzy Inference System ◽

Electrical Discharge ◽

Material Removal ◽

Fuzzy Inference ◽

Electrical Discharge Machining ◽

Removal Rate ◽

Inference System ◽

Prediction and optimization of tool wear rate during electric discharge machining of Al/Cu/Ni alloy using adaptive neuro-fuzzy inference system

Heliyon ◽

10.1016/j.heliyon.2020.e05308 ◽

2020 ◽

Vol 6 (10) ◽

pp. e05308

Author(s):

Mangesh Phate ◽

Aditya Bendale ◽

Shraddha Toney ◽

Vikas Phate

Keyword(s):

Wear Rate ◽

Tool Wear ◽

Electric Discharge ◽

Fuzzy Inference System ◽

Fuzzy Inference ◽

Tool Wear Rate ◽

Inference System ◽

Neuro Fuzzy ◽

Ni Alloy

Application of a Fuzzy Inference System for the Optimization of Material Removal Rate and Multiple Surface Roughness Characteristics in the Machining of GFRP Polyester Composites

Decision Making in Manufacturing and Services ◽

10.7494/dmms.2013.7.1.19 ◽

2013 ◽

Vol 7 (1-2) ◽

pp. 19

Author(s):

Ankita Singh ◽

Saurav Datta ◽

Siba Sankar Mahapatra

Keyword(s):

Surface Roughness ◽

Material Removal Rate ◽

Fuzzy Inference System ◽

Material Removal ◽

Fuzzy Inference ◽

Removal Rate ◽

Inference System ◽

Polyester Composites

Investigating the effects of electric discharge machining parameters on material removal rate and surface roughness on AISI D2 steel using RSM-GRA integrated approach

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-018-3019-1 ◽

2018 ◽

Vol 101 (5-8) ◽

pp. 1255-1265 ◽

Cited By ~ 12

Author(s):

Muhammad Hanif ◽

Wasim Ahmad ◽

Salman Hussain ◽

Mirza Jahanzaib ◽

Abdul Hakim Shah

Keyword(s):

Surface Roughness ◽

Material Removal Rate ◽

Electric Discharge ◽

Material Removal ◽

Removal Rate ◽

Integrated Approach ◽

Machining Parameters ◽

Aisi D2 ◽

D2 Steel

Advances in Engineering Research and Application - Lecture Notes in Networks and Systems ◽

Material Removal Rate in Electric Discharge Machining with Aluminum Tool Electrode for Ti-6Al-4V Titanium Alloy

10.1007/978-3-030-64719-3_58 ◽

2020 ◽

pp. 527-533

Author(s):

Nguyen Huu Phan ◽

Vu Ngoc Pi ◽

Shailesh Shirguppikar ◽

M. S. Patil ◽

Mohsen Asghari Ilani ◽

...

Keyword(s):

Titanium Alloy ◽

Material Removal Rate ◽

Electric Discharge ◽

Material Removal ◽

Removal Rate ◽

Tool Electrode ◽

Electric Discharge Machining

Effect of Contributing Parameters over Material Removal Rate in Machining Incoloy 825 using Electric Discharge Machining EDM

International Journal of Trend in Scientific Research and Development ◽

10.31142/ijtsrd4609 ◽

2017 ◽

Vol Volume-1 (Issue-6) ◽

pp. 821-824

Author(s):

Vigneshwaran N.K. ◽

Vishnu Prabhu S ◽

Vignesh Kumar S | Ricordey Arumaidoss F ◽

Keyword(s):

Material Removal Rate ◽

Electric Discharge ◽

Material Removal ◽

Removal Rate ◽

Incoloy 825

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

Comparative study of expert predictive models based on adaptive neuro fuzzy inference system, nonlinear autoregressive exogenous and Hammerstein–Wiener approaches for electrical discharge machining performance: Material removal rate and surface roughness

10.1177/0954405415625923 ◽

2016 ◽

Vol 230 (9) ◽

pp. 1690-1701 ◽

Cited By ~ 6

Author(s):

Ehsan Roodgar Amoli ◽

Saeed Salehinia ◽

Majid Ghoreishi

Keyword(s):

Predictive Models ◽

Electrical Discharge ◽

Material Removal ◽

Fuzzy Inference ◽

Electrical Discharge Machining ◽

Removal Rate ◽

Machining Performance ◽

Inference System ◽

Neuro Fuzzy ◽

Nonlinear Autoregressive

Simultaneous optimization of material removal rate and tool wear rate during wire electric discharge machining of Nitinol smart alloy

10.1063/1.5141204 ◽

2019 ◽

Author(s):

Vinayak N. Kulkarni ◽

V. N. Gaitonde ◽

Shubhang G. Kadadevaru ◽

S. R. Karnik

Keyword(s):

Wear Rate ◽

Tool Wear ◽

Material Removal Rate ◽

Electric Discharge ◽

Material Removal ◽

Removal Rate ◽

Simultaneous Optimization ◽

Tool Wear Rate ◽

Wire Electric Discharge Machining