Riad Khettabi

Investigation of the performance of the MQL, dry, and wet turning by response surface methodology (RSM) and artificial neural network (ANN)

Mourad Nouioua, Mohamed Athmane Yallese, Riad Khettabi et al. · The International Journal of Advanced Manufacturing Technology · 2017 · 88 citations

Engineering, Industrial Engineering, Response Surface Methodology +5

Prediction of machining performance using RSM and ANN models in hard turning of martensitic stainless steel AISI 420

Abderrahmen Zerti, Mohamed Athmane Yallese, Oussama Zerti et al. · Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · 2019 · 88 citations

Engineering, Industrial Engineering, Abrasive Machining +12

Design optimization for minimum technological parameters when dry turning of AISI D3 steel using Taguchi method

Oussama Zerti, Mohamed Athmane Yallese, Riad Khettabi et al. · The International Journal of Advanced Manufacturing Technology · 2016 · 69 citations

Engineering, Industrial Engineering, Material Machining +9

Effect of MQL and dry processes on the particle emission and part quality during milling of aluminum alloys

Riad Khettabi, Mourad Nouioua, Abdelhakim Djebara et al. · The International Journal of Advanced Manufacturing Technology · 2017 · 52 citations

Materials Science, Part Quality, Engineering +7

Cutting Conditions Modeling and Optimization in Hard Turning Using RSM, ANN and Desirability Function

Abderrezak Labidi, Hamid Tebassi, Salim Belhadi et al. · Journal of Failure Analysis and Prevention · 2018 · 46 citations

Engineering, Industrial Engineering, Material Machining +10