Performance evaluation of the WEDM process of aeronautics super alloy. Issue 16 (10th December 2018)

• Record Type: Journal Article
• Authors: Nain, Somvir Singh; Garg, Dixit; Kumar, Sanjeev
• Is Part Of: Materials and manufacturing processes. Volume 33:Issue 16(2018)
• Page Start: 1793
• Page End: 1808
• Publication Date: 2018-12-10
• Subjects: Analysis -- diffraction analysis -- forest -- M5P -- optimization -- random -- sensitivity -- tree -- X-ray; Manufacturing processes -- Periodicals; Materials -- Periodicals; Manufactured Materials; 670.5
• DOI: 10.1080/10426914.2018.1476761
• Languages: English
• ISSNs: 1042-6914

Abstract

ABSTRACT: The current studies aim to enhance the outcome of wire electric discharge machining of the aeronautics alloy by applying machine learning algorithms and optimization approaches. The Taguchi L27 is employed to formulate the experimental work. The random forest, M5P tree approaches are employed for modeling the wire electric discharge machining process. The sensitivity analysis test has been conducted on the dominant model. The particle swarm optimization approach is employed to attain the optimal grouping of process variables of wire electric discharge machining process. The surface integrity evaluation tests have been conducted to observe the changes that took place on the surface of the material after wire electric discharge machining.