Improve the Material Removal Rate of Electrochemical Grinding on Monel 400 Using RSM

International Journal of Recent Technology and Engineering - India
doi 10.35940/ijrte.b2645.078219
Full Text
Abstract

Available in full text

Date
Authors

Unknown

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Related search

An Analysis of Surface Roughness and Material Removal Rate in Cylindrical Grinding of Hardened OHNS Using Response Suface Method

International Journal of Engineering Research and
2015English

Material Removal Rate and Tool Wear Rate on Machining of Inconel 718 Using Electrical Discharge Machine

Research & Development in Material Science
2018English

Laser Alloying Monel 400 With Amorphous Boron to Obtain Hard Coatings

Materials
Materials ScienceCondensed Matter Physics
2019English

Microstructure and Selected Properties of Monel 400 Alloy After Laser Heat Treatment and Laser Boriding Using Diode Laser

International Journal of Advanced Manufacturing Technology
ControlSystems EngineeringIndustrialMechanical EngineeringManufacturing EngineeringComputer Science ApplicationsSoftware
2018English

Investigation of the Material Removal Mechanism in Electrochemical Discharge Drilling Using a High-Speed Rotating Helical Tool-Electrode

International Journal of Electrochemical Science
Electrochemistry
2019English

Grinding Rate Improvement Using a Composite Grinding Ball Size for an Ultra-Fine Grinding Mill.

Journal of the Society of Powder Technology, Japan
FiltrationFluid FlowProcess ChemistrySeparationTransfer ProcessesCatalysisTechnology
1996English

Analysis of Material Removal Rate in Lapping of the Hard Alloy Rings

Mechanical Engineering and Technology
2015English

An Approach to Residual Stress in the Ground Layer of Ceramics From Material Removal by Grinding.

Zairyo/Journal of the Society of Materials Science, Japan
Mechanics of MaterialsMaterials ScienceCondensed Matter PhysicsMechanical Engineering
1992English

Precision Obtained Using an Artificial Neural Network for Predicting the Material Removal Rate in Ultrasonic Machining

Applied Sciences (Switzerland)
InstrumentationMaterials ScienceFluid FlowEngineeringComputer Science ApplicationsProcess ChemistryTransfer ProcessesTechnology
2017English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy