Numéro |
Matériaux & Techniques
Volume 108, Numéro 4, 2020
|
|
---|---|---|
Numéro d'article | 402 | |
Nombre de pages | 12 | |
Section | Métaux et alliages / Metals and alloys | |
DOI | https://doi.org/10.1051/mattech/2020035 | |
Publié en ligne | 21 décembre 2020 |
Regular Article
Dry machining of Inconel 718 super alloys using uncoated tool: Experimental and numerical analysis
Department of Mechanical Engineering, National Institute of Technology,
Rourkela
769008,
Odisha, India
* e-mail: sdattaju@gmail.com
Received:
14
February
2020
Accepted:
10
November
2020
Aerospace super alloy Inconel 718 is difficult to process through conventional machining operation. Alloys with high strength at high temperatures and high strain hardening, high chemical affinity (towards tool material, and Co binder) etc. impose adverse effects towards smooth machining. Poor thermal conductivity of Inconel 718 promotes excessive temperature rise at the chip-tool interface which causes rapid tool wear, and degraded surface integrity of the end product. Adequate understanding of machining process phenomena along with precise control of machining parameters may yield satisfactory result. Trial, and error experimentation is indeed uneconomical; hence, in the present reporting, Finite Element (FE) based numerical simulation is attempted to model machining responses in the extent of cutting force, tool-tip temperature, depth of flank wear progression, chip-tool contact length, and finally, chip reduction coefficient. Simulation results are verified through experimental tests. Simulation results are found in good agreement with experimental results. Therefore, simulation results can reliably be used as an alternative instead of actual experimental effort.
Key words: super alloy / Inconel 718 / tool wear / Finite Element (FE) / numerical simulation
© SCF, 2020
Les statistiques affichées correspondent au cumul d'une part des vues des résumés de l'article et d'autre part des vues et téléchargements de l'article plein-texte (PDF, Full-HTML, ePub... selon les formats disponibles) sur la platefome Vision4Press.
Les statistiques sont disponibles avec un délai de 48 à 96 heures et sont mises à jour quotidiennement en semaine.
Le chargement des statistiques peut être long.