<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Minimum Quantity Lubrication has enormous influence on the process parameters in machining. The main aim of the present work is to study the effects of spindle speed, depth of cut, tool material, amount of coolant dispensed and type of coolant on surface roughness and tool temperature in EN31 steel die making including Minimum Quantity Lubrication (MQL) by introducing a self-designed MQL setup and to optimize the responses using fuzzy-logic and Particle Swarm Optimization technique.</p></abstract>

Minimum Quantity Lubrication has enormous influence on the process parameters in machining. The main aim of the present work is to study the effects of spindle speed, depth of cut, tool material, amount of coolant dispensed and type of coolant on surface roughness and tool temperature in EN31 steel die making including Minimum Quantity Lubrication (MQL) by introducing a self-designed MQL setup and to optimize the responses using fuzzy-logic and Particle Swarm Optimization technique.

Effect of Minimum Quantity Lubrication on Surface Roughness and Temperature in Milling of EN31 Steel for Die Making

Strojnícky časopis - Journal of Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Minimum Quantity Lubrication has enormous influence on the process parameters in machining. The main aim of the present work is to study the effects of spindle...

Effect of Minimum Quantity Lubrication on Surface Roughness and Temperature in Milling of EN31 Steel for Die Making

Pubblicato online: 31 mag 2019

Pagine: 61 - 68

DOI: https://doi.org/10.2478/scjme-2019-0005

Parole chiave
MQL, EN31 steel die making surface roughness and tool temperature, fuzzy-logic and Particle Swarm Optimization technique

© 2019 Keerthana Bhosetty et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Effect of Minimum Quantity Lubrication on Surface Roughness and Temperature in Milling of EN31 Steel for Die Making

Pubblicato online: 31 mag 2019

Pagine: 61 - 68

DOI: https://doi.org/10.2478/scjme-2019-0005

Parole chiaveMQL, EN31 steel die making surface roughness and tool temperature, fuzzy-logic and Particle Swarm Optimization technique

© 2019 Keerthana Bhosetty et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
MQL, EN31 steel die making surface roughness and tool temperature, fuzzy-logic and Particle Swarm Optimization technique