Transforming Manufacturing with Intelligent Technologies: Process Optimization and Industry Applications

Arizona College of Technology, Hebei University of Technology, Tianjin, 300000, China

^* Corresponding author: 225787@stu.hebut.edu.cn

Abstract

With globalization and intensified market competition, traditional manufacturing faces numerous challenges, including rising labor costs, low production efficiency, and unstable product quality. Intelligent manufacturing, which integrates advanced digital, information, and automation technologies, offers promising solutions. This paper explores the application of intelligent manufacturing technologies across various industries, examining process optimization methods, system design and implementation, current research, and challenges. Data-driven optimization methods significantly enhance production efficiency and product quality in processes such as welding and assembly through real-time monitoring and feedback control. Industry-specific applications demonstrate substantial improvements in design and production efficiency in sectors like bus manufacturing, lifting machinery, shipbuilding, and textiles. The study highlights the importance of optimizing and adaptively controlling automated production lines, emphasizing the role of intelligent technologies and modular design in creating scalable and maintainable systems. Despite these advancements, intelligent manufacturing technologies face challenges such as complex technology integration, high demands for system reliability and real-time performance, and the need for improved data processing and algorithm optimization. To address these issues, recommendations include enhancing research in key areas, promoting standardization, deepening international cooperation, focusing on talent development, and increasing government support. This comprehensive exploration provides valuable insights and practical guidance for the transformation and upgrading of manufacturing enterprises.