Understanding Machining Process Parameters and Optimization of High-Speed Turning of NiTi SMA Using Response Surface Method (RSM) and Genetic Algorithm (GA)

Author:

Zhao Yanzhe1ORCID,Cui Li1,Sivalingam Vinothkumar23ORCID,Sun Jie2

Affiliation:

1. School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai 201209, China

2. Key Laboratory of High-Efficiency and Clean Mechanical Manufacture, National Demonstration Center for Experimental Mechanical Engineering Education, School of Mechanical Engineering, Shandong University, Jinan 250061, China

3. Department of Mechanical Engineering, Saveetha School of Engineering, SIMATS, Chennai 602105, India

Abstract

This study aimed to optimize machining parameters to obtain better surface roughness and remnant depth ratio values under dry turning of NiTi-shape memory alloy (SMA). During the turning experiments, various machining parameters were used, including three different cutting speeds vc (105, 144, and 200 m/min), three different feed rates f (0.05, 0.1, and 0.15 mm/rev), and three different depths of cut ap (0.1, 0.15, and 0.2 mm). The effects of machining parameters in turning experiments were investigated on the response surface methodology (RSM) with Box–Behnken design (BBD) using the Design Expert 11; how the cutting parameters affect the surface quality is discussed in detail. In this context, the cutting parameters were successfully optimized using a genetic algorithm (GA). The optimized processing parameters are vc = 126 m/min, f = 0.11 mm/rev, ap = 0.14 mm, resulting in surface roughness and remnant depth ratio values of 0.489 μm and 64.13%, respectively.

Funder

Future for Young Scholars of Shandong University

Scientific Research Foundation of Shanghai Polytechnic University

Shanghai Natural Science Foundation

Key Research and development program of Shandong province

Publisher

MDPI AG

Subject

General Materials Science

Reference39 articles.

1. Design Optimization and Uncertainty Analysis of SMA Morphing Structures;Oehler;Smart Mater. Struct.,2012

2. A Review of Shape Memory Alloy Research, Applications and Opportunities;Leary;Mater. Des.,2014

3. Biomedical Applications of Shape Memory Alloys;Petrini;J. Metall.,2011

4. A Review on Machining of NiTi Shape Memory Alloys: The Process and Post Process Perspective;Kaya;Int. J. Adv. Manuf. Technol.,2019

5. A Review on Machinability of Shape Memory Alloys Through Traditional and Non-Traditional Machining Processes: A Review;Korkmaz;İmalat Teknol. Uygulamaları,2022

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