Optimization of Process Parameters for FSP Surface-Modified Al6061 Reinforced with Nano TiAl Sheets Using TOPSIS Multi-Criteria Decision-Making (MCDM) Technique

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Authors: Kondaveeti Chandra Sekhar, Potnuru Srikar, Immanuel Rajan Jose, Thipparthi Raja gopala chary, Muddu Allaparthi
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Abstract

Friction Stir Processing (FSP) is a solid-state, environmentally benign method that has emerged as a viable surface composite production approach. Because intense plastic deformation during FSP not only synthesizes the reinforcement phase in the matrix in situ but also shears and diffuses the particles and advances the reaction between aluminum and added particles quickly. It is more appealing to synthesize reinforcing particles in an aluminum matrix using FSP than to fabricate conventional AMMCs. The Taguchi concept is a standard optimization procedure, but it has the limitation of not being capable of solving multi-objective problems simultaneously. The Multi-Criteria Decision-Making (MCDM) method can be used to solve multiple objectives simultaneously and effectively. The Al-6061 alloy as matrix is reinforced with nanoTiAl as workpiece, and H13 tool steel is used as the tool material. The important process parameters considered are rotational speed, transverse speed, and plunge depth with different tool profiles. The response parameters selected are tensile strength and microhardness of the modified surface area. Process parameters are optimized using the TOPSIS-MCDM method, and the optimum values obtained are a rotational speed of 1400 rpm, a transverse speed of 40 mm/min, and a plunge depth of 2°. It is understood that better tensile strength and microhardness of the FSP modified area at optimized conditions are due to adequate material flow, fine grain size, and pulsating action. The MCDM method has a simple calculation procedure and an easier solving methodology for FSP parameters optimization.

Fields of Study & Subjects

Advanced Welding Techniques Analysis Aluminum Alloys Composites Properties Advanced machining processes and optimization

Publication details

Journal / source
CRC Press eBooks
Pages
279–292
Publication date
30 January 2026
Language
EN
Document type
Book chapter