Affiliation:
1. Symbiosis Institute of Technology, Symbiosis International (Deemed
University), Department of Mechanical Engineering, India
2. Parul Institute of Engineering and Technology, Department of
Aeronautical Engineering, India
Abstract
<div>This research examines the impact of different amounts of copper (Cu) powder on
the wear characteristics of acrylonitrile butadiene styrene (ABS)–Cu composites.
Various formulations of ABS–Cu composites have been produced using injection
molding, with different amounts of surfactant. Wear properties were evaluated by
conducting tribological testing in accordance with ASTM standards. The findings
indicated a decrease in wear loss, particularly when using a mixture consisting
of 23% ABS, 70% Cu, and 7% surfactant. Machine learning regression algorithms
successfully forecasted wear behavior with R-squared values over 0.97. The
models used in the analysis included linear, stepwise linear, tree, support
vector machine (SVM), efficient linear, Gaussian progression, ensemble, and
neural network regression models. This research emphasizes the significance of
composite materials in fulfilling contemporary technical requirements. The
acquired insights enable the development of materials with customized wear
characteristics. These findings have important consequences for a range of
industrial applications.</div>