Application of Machine Learning in Printing Circuit Board of Electric Vehicle: Enhancing Manufacturing Processes and Product Quality
Yiming Zhang
DOI: https://doi.org/10.59429/esta.v10i6.1674
Keywords: Electric Vehicle; Machine Learning; Circuit Board
Abstract
The electric vehicle industry are growing rapidly due to the increasing demand for sustainable transportation solutions. However, the production of electric vehicles involves complex manufacturing processes that require high precision and accuracy to ensure the quality of the final product. One of the critical components of electric vehicles is their printed circuit boards (PCB), which play a crucial role in controlling and regulating the vehicle’s electronic systems. The application of machine learning in electric vehicle printing can enhance the manufacturing processes and product quality by providing real-time monitoring, prediction, and optimization capabilities. And this study concentrates on two main problems: firstly inadequate load capacity, that circuit boards can’t load high current and voltage and secondly reliability issues caused by harsh working environments, such as large temperature fluctuations, high humidity, strong vibrations, and excessive dust, which can easily lead to circuit board failure.One of the biggest innovation of this paper is using machine learning to analyze the relationship between some factors and circuit board lifespan.
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