Academic Journal of Engineering and Technology Science, 2025, 8(3); doi: 10.25236/AJETS.2025.080306.
Zheng Peng
Suzhou Manaqiu Electromechanical Equipment Co., Ltd., Suzhou, 215131, China
With the evolution of manufacturing towards intelligence and automation, traditional production line scheduling methods can no longer meet the demands of modern production. This paper focuses on the development and application of an intelligent automated production line scheduling system, aiming to achieve efficient, intelligent, and automated production scheduling through advanced intelligent algorithms and information technology. By conducting an in-depth analysis of the current status and problems of the production line in the target enterprise, the functional and performance requirements of the system development are clarified. Based on a layered architecture design, intelligent scheduling algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) are selected, combined with industrial internet technology to realize real-time data collection and interaction. During the system development process, modules such as production plan management, real-time scheduling, resource management, and data interaction and visualization were meticulously designed and implemented in the target enterprise. The application results show that the system significantly improves production efficiency, optimizes resource utilization, reduces production costs, enhances product quality, and strengthens the enterprise’s market competitiveness. This research not only provides technical support for the intelligent transformation of manufacturing but also offers reference value for academic research in related fields.
Intelligent automation; production line scheduling; system development; application; genetic algorithm; particle swarm optimization; industrial internet; production efficiency; resource optimization; cost control
Zheng Peng. Development and Application Research of Intelligent Automated Production Line Scheduling System. Academic Journal of Engineering and Technology Science (2025), Vol. 8, Issue 3: 33-40. https://doi.org/10.25236/AJETS.2025.080306.
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