Author(s)

Bin Wang ¹

Affiliation(s)

¹ Jiangxi Rayone Wheels Technology Company Limited, Fuzhou, Jiangxi, 344499, China

Corresponding Author

Bin Wang

ABSTRACT

This research article presents a comprehensive study on intelligent manufacturing processes for automotive wheel rims, focusing on process modeling and performance evaluation. The investigation encompasses the development of a digital twin-based framework to simulate and analyze various manufacturing parameters, including material flow, energy consumption, and production throughput. Advanced optimization algorithms are applied to identify optimal process settings, leading to improvements in efficiency, sustainability, and product quality. A case study involving the production of aluminum alloy wheel rims is conducted to demonstrate the efficacy of the proposed methodology. The results highlight significant enhancements in production efficiency and a reduction in material waste. The integration of machine learning techniques for predictive maintenance is also explored, contributing to a more resilient and reliable manufacturing system. The research provides valuable insights for automotive manufacturers aiming to adopt intelligent manufacturing strategies for enhanced competitiveness and sustainability.

KEYWORDS

Intelligent Manufacturing, Automotive Wheel Rims, Process Modeling, Performance Evaluation, Digital Twin, Optimization Algorithms, Machine Learning

CITE THIS PAPER

Bin Wang. Intelligent Manufacturing of Automotive Wheel Rims: Process Modeling and Performance Evaluation. Industrial Engineering and Innovation Management (2026). Vol. 9, No.1, 11-22. DOI: http://dx.doi.org/10.23977/ieim.2026.090102.

REFERENCES

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