Optimization of Machine Learning for Production and Maintenance Repairs in the Automotive Industry
Year: 2025
Type: article
Abstract: With the rapid advancement of machine learning (ML) and artificial intelligence (AI), these technologies are increasingly being adopted by scholars, researchers, and automotive manufacturers to optimize processes and outcomes across the industry. This study examines how ML enhances automotive production and maintenance, highlighting its transformative effects and exploring future possibilities. By synthesizing insights from ten key studies and analyzing forward-looking projections, the research concludes that the integration of ML into automotive manufacturing is steadily evolving from theoretical exploration to practical application. ML has become a critical driver for optimizing production processes, improving maintenance efficiency, and fostering innovation within the sector. Although many approaches remain in the experimental phases, the potential of this integration is growing rapidly. The adoption of ML in automotive manufacturing and maintenance represents an inevitable and highly promising trend, paving the way for groundbreaking advancements and a significant impact on the industry’s future.
Author: Zhongtian Gu
Institution: Shanghai Maritime University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4409237139