# | title |
| 1 | Investigating the Machinability of Al–Si–Cu cast alloy containing bismuth and antimony using coated carbide insert |
| 2 | Surface Roughness Prediction in End-Milling Process |
| 3 | White layer thickness prediction in WEDM-ANFIS modelling |
| 4 | Investigation into effect of silicon morphology on surface roughness while machining Al-Si-Cu-Mg alloy |
| 5 | Enhanced surface roughness of AISI D2 steel machined using nano-powder mixed electrical discharge machining |
| 6 | White layer thickness prediction in Wire-EDM using CuZn coated wire electrode - ANFIS modeling |
| 7 | Development of a new performance criteria for higher wire-electrical discharge machining performance considering the ecological and economical aspects |
| 8 | 1.7 Techniques to Improve EDM Capabilities: A Review |
| 9 | Wire Rupture Optimization in Wire Electrical Discharge Machining Using Taguchi approach |
| 10 | Performance of Electrical Discharge Milling and Sinking in Micro Graphite Powder Mixed Dielectric |
| 11 | INVESTIGATION ON SURFACE FINISH AND TOOL CONDITION WHILE TURNING AL20 Mg2Si METAL MATRIX COMPOSITE |
| 12 | Proposing a new performance index to identify the effect of spark energy and pulse frequency simultaneously to achieve high machining performance in WEDM |
| 13 | Increasing the productivity of the wire-cut electrical discharge machine associated with sustainable production |
| 14 | An electrode wire for use in wire electrical discharge machining |
| 15 | Improve wire EDM performance at different machining parameters – ANFIS modeling |
| 16 | 1.9 Effect of Electrical Discharge Energy on White Layer Thickness of WEDM Process |
| 17 | Review of improvements in wire electrode properties for longer working time and utilization in wire EDM machining |
| 18 | Surface roughness prediction in end milling using multiple regression and adaptive neuro-fuzzy inference system |
| 19 | Investigation of the effect of machining parameters on the surface quality of machined brass (60/40) in CNC end milling—ANFIS modeling |
| 20 | Cutting force-based adaptive neuro-fuzzy approach for accurate surface roughness prediction in end milling operation for intelligent machining |