Title: Machining performance optimisation of MQL-assisted turning of Inconel-825 superalloy using GA for industrial applications
Authors: S.K. Tamang; M. Chandrasekaran; K. Palanikumar; Ramanathan M. Arunachalam
Addresses: Department of Mechanical Engineering, North Eastern Regional Institute of Science & Technology (NERIST), Arunachal Pradesh, India ' Department of Mechanical Engineering, North Eastern Regional Institute of Science & Technology (NERIST), Arunachal Pradesh, India ' Department of Mechanical Engineering, Sri Sai Ram Institute of Technology, Chennai, India ' Department of Mechanical and Industrial Engineering, College of Engineering, Sultan Qaboos University, Sultanate of Oman
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.
Keywords: Inconel 825; machining; minimum quantity lubrication; MQL; tool wear; cutting temperature; surface roughness; optimisation.
International Journal of Machining and Machinability of Materials, 2019 Vol.21 No.1/2, pp.43 - 65
Received: 17 Apr 2018
Accepted: 19 May 2018
Published online: 21 Feb 2019 *