Application of Artificial Neural Network and Response Surface Methodology in Modeling of Surface Roughness in WS2 Solid Lubricant Assisted MQL Turning of Inconel 718

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/346/1/012085 ◽

2018 ◽

Vol 346 ◽

pp. 012085 ◽

Cited By ~ 4

Author(s):

Uma Maheshwera Reddy Paturi ◽

Harish Devarasetti ◽

David Abimbola Fadare ◽

Suresh Kumar Reddy Narala

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Inconel 718 ◽

Solid Lubricant ◽

Artificial Neural

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On the Modeling of Surface Roughness and Cutting Force when Turning of Inconel 718 Using Artificial Neural Network and Response Surface Methodology: Accuracy and Benefit

Periodica Polytechnica Mechanical Engineering ◽

10.3311/ppme.8742 ◽

2017 ◽

Vol 61 (1) ◽

pp. 1-11 ◽

Cited By ~ 16

Author(s):

Hamid Tebassi ◽

◽

Mohamed Athmane Yallese ◽

Ikhlas Meddour ◽

Francois Girardin ◽

...

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Cutting Force ◽

Response Surface ◽

Inconel 718 ◽

Artificial Neural

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Prediction of surface roughness in turning of duplex stainless steel (DSS) using response surface methodology (RSM) and artificial neural network (ANN)

Materials Today Proceedings ◽

10.1016/j.matpr.2021.05.118 ◽

2021 ◽

Author(s):

Mahesh Gopal

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Stainless Steel ◽

Response Surface Methodology ◽

Duplex Stainless Steel ◽

Response Surface ◽

Artificial Neural ◽

Artificial Neural Network Ann

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Modeling and Correlations Between Parameters of Roller Burnishing Process on Surface Roughness for Aluminum 63400 Using Response Surface Methodology and Artificial Neural Network

Advanced Science Engineering and Medicine ◽

10.1166/asem.2018.2266 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1071-1076

Author(s):

Vijay Kurkute ◽

Sandip T. Chavan

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Roller Burnishing ◽

Burnishing Process ◽

Artificial Neural

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Artificial neural network–based and response surface methodology–based predictive models for material removal rate and surface roughness during electro-discharge diamond grinding of Inconel 718

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

10.1177/0954405415619347 ◽

2016 ◽

Vol 230 (11) ◽

pp. 2082-2091 ◽

Cited By ~ 15

Author(s):

Deepak Rajendra Unune ◽

Harlal Singh Mali

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Material Removal Rate ◽

Predictive Models ◽

Inconel 718 ◽

Material Removal ◽

Removal Rate

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Mathematical Modelling and Optimization of Cutting Force, Tool Wear and Surface Roughness by Using Artificial Neural Network and Response Surface Methodology in Milling of Ti-6242S

Applied Sciences ◽

10.3390/app7101064 ◽

2017 ◽

Vol 7 (10) ◽

pp. 1064 ◽

Cited By ~ 37

Author(s):

Erol Kilickap ◽

Ahmet Yardimeden ◽

Yahya Hışman Çelik

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Tool Wear ◽

Mathematical Modelling ◽

Cutting Force ◽

Response Surface ◽

Artificial Neural ◽

Modelling And Optimization

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Navigating viscosity of ferrofluid using response surface methodology and artificial neural network

Journal of Materials Research and Technology ◽

10.1016/j.jmrt.2020.11.087 ◽

2020 ◽

Vol 9 (6) ◽

pp. 16339-16348

Author(s):

Nidal H. Abu-Hamdeh ◽

Ali Golmohammadzadeh ◽

Aliakbar Karimipour

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Artificial Neural

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Modeling of phenol separation from water by NiFe2O4 nanocomposite using response surface methodology and artificial neural network techniques

Journal of Environmental Chemical Engineering ◽

10.1016/j.jece.2021.105576 ◽

2021 ◽

pp. 105576

Author(s):

Leili Mohammadi ◽

Muhammad Nadeem Zafar ◽

Maqzia Bashir ◽

Sajjad Hussain Sumrra ◽

Syed Salman Shafqat ◽

...

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Artificial Neural

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Comparative study of response surface methodology and artificial neural network in the optimization of the ultrasound-assisted extraction of diarylheptanoid phytoestrogens from Curcuma comosa rhizomes

Chemical Engineering and Processing - Process Intensification ◽

10.1016/j.cep.2021.108461 ◽

2021 ◽

Vol 165 ◽

pp. 108461

Author(s):

Bancha Yingngam ◽

Abhiruj Navabhatra ◽

Wandee Rungseevijitprapa ◽

Chutinun Prasitpuriprecha ◽

Adelheid Brantner

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Comparative Study ◽

Response Surface ◽

Ultrasound Assisted Extraction ◽

Curcuma Comosa ◽

Assisted Extraction ◽

Ultrasound Assisted ◽

Artificial Neural

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Analysis and prediction of the performance of free- piston Stirling engine using response surface methodology and artificial neural network

Applied Thermal Engineering ◽

10.1016/j.applthermaleng.2021.116557 ◽

2021 ◽

Vol 188 ◽

pp. 116557

Author(s):

Wenlian Ye ◽

Xiaojun Wang ◽

Yingwen Liu ◽

Jun Chen

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Stirling Engine ◽

Free Piston ◽

Artificial Neural ◽

Free Piston Stirling Engine

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Evaluating the fluidized-bed drying of rice using response surface methodology and artificial neural network

LWT ◽

10.1016/j.lwt.2021.111589 ◽

2021 ◽

Vol 147 ◽

pp. 111589

Author(s):

Sara Nanvakenari ◽

Kamyar Movagharnejad ◽

Asefeh Latifi

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Fluidized Bed ◽

Fluidized Bed Drying ◽

Artificial Neural

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