Machining performance optimisation of mql-assisted turning of inconel-825 superalloy using ga for industrial applications

S. K. Tamang, M. Chandrasekaran, K. Palanikumar, Arunachalam Ramanathan

Research output: Contribution to journalArticle

Abstract

This work investigates machining performance of Inconel 825 using chemical vapour deposition (CVD) TiN coated inserts in minimum quantity lubrication (MQL) approach. Three important measures in relation to machining of hard-to-cut materials viz., surface roughness (Ra), tool wear (VB), and cutting temperature (CT) have been considered for investigation. The response surface methodology (RSM) modelling and relationship between input and output factors is studied. The machining parameters are optimised individually as well as simultaneously using genetic algorithm (GA). The minimum Ra of 0.39 μm, VB of 15.37 μm and CT of 56.47°C was obtained. The significant contribution of this research is that the values of Ra, VB and CT obtained are quite low when compared to those reported in literatures. For the application in manufacturing industries, a technology table is generated for selection of optimum process parameters having minimum VB or minimum CT satisfying the desired value of surface finish of components produced.

Original languageEnglish
Pages (from-to)43-64
Number of pages22
JournalInternational Journal of Machining and Machinability of Materials
Volume21
Issue number1-2
Publication statusPublished - Jan 1 2019

Fingerprint

Superalloys
Industrial applications
Machining
Temperature
Lubrication
Chemical vapor deposition
Genetic algorithms
Surface roughness
Wear of materials
Industry

Keywords

  • Cutting temperature
  • Inconel 825
  • Machining
  • Minimum quantity lubrication
  • Mql
  • Optimisation
  • Surface roughness
  • Tool wear

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this

Machining performance optimisation of mql-assisted turning of inconel-825 superalloy using ga for industrial applications. / Tamang, S. K.; Chandrasekaran, M.; Palanikumar, K.; Ramanathan, Arunachalam.

In: International Journal of Machining and Machinability of Materials, Vol. 21, No. 1-2, 01.01.2019, p. 43-64.

Research output: Contribution to journalArticle

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