Статья

Optimization of Selective Laser Melting Parameter for Invar Material by Using JAYA Algorithm: Comparison with TLBO, GA and JAYA

Hiren GajeraDepartment of Mechanical Engineering, L D College of Engineering, Ahmedabad 380015, IndiaFaramarz DjavanroodiDepartment of Mechanical Engineering, College of Engineering, Prince Mohammad Bin Fahd University, Al Khobar 31952, Saudi ArabiaSoni KumariDepartment of Mechanical Engineering, GLA University, Mathura 281406, IndiaKumar AbhishekDepartment of Mechanical and Aero-Space Engineering, Institute of Infrastructure, Technology, Research and Management (IITRAM), Ahmedabad 380026, IndiaDin BandhuDepartment of Mechanical Engineering, Indian Institute of Information Technology Design and Manufacturing (IIITDM), Kurnool 518008, IndiaKuldeep K. SaxenaDepartment of Mechanical Engineering, GLA University, Mathura 281406, IndiaMahmoud EbrahimiNational Engineering Research Center of Light Alloy Net Forming and Key State Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaChander PrakashDivision of Research and Development, Lovely Professional University, Phagwara 144011, IndiaD. BuddhiDivision of Research & Innovation, Uttaranchal University, Dehradun 248007, India

2022en

ABI

Аннотация

In this study, the hardness and surface roughness of selective laser-melted parts have been evaluated by considering a wide variety of input parameters. The Invar-36 has been considered a workpiece material that is mainly used in the aerospace industry for making parts as well as widely used in bimetallic thermostats. It is the mechanical properties and metallurgical properties of parts that drive the final product's quality in today's competitive marketplace. The study aims to examine how laser power, scanning speed, and orientation influence fabricated specimens. Using ANOVA, the established models were tested and the parameters were evaluated for their significance in predicting response. In the next step, the fuzzy-based JAYA algorithm has been implemented to determine which parameter is optimal in the proposed study. In addition, the optimal parametric combination obtained by the JAYA algorithm was compared with the optimal parametric combination obtained by TLBO and genetic algorithm (GA) to establish the effectiveness of the JAYA algorithm. Based on the results, an orientation of 90°, 136 KW of laser power, and 650 mm/s scanning speed were found to be the best combination of process parameters for generating the desired hardness and roughness for the Invar-36 material.

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Идентификаторы

DOI: 10.3390/ma15228092

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar