摘 要
随着工业4.0的深入推进，自动化生产线在现代制造业中的地位日益凸显，其高效运行依赖于机电一体化系统的优化调度。本研究旨在针对当前自动化生产线中调度效率低、资源利用率不足等问题，提出一种基于多目标优化算法的机电一体化调度策略。通过融合遗传算法与粒子群优化算法的优势，构建了适用于复杂生产环境的混合智能优化模型，并结合实际生产线数据进行仿真验证。研究结果表明，所提出的优化方法能够显著提升生产线的整体效率，降低能耗并减少设备磨损，同时具备较强的鲁棒性和适应性。此外，本研究创新性地引入了动态优先级调整机制，使调度系统能够在实时变化的生产需求下灵活响应，进一步提高了系统的智能化水平。最终结论显示，该优化调度策略不仅有效解决了传统调度方法中存在的静态性和局限性问题，还为未来智能制造领域的调度技术发展提供了新的思路和理论支持，具有重要的学术价值和应用前景。关键词：自动化生产线；多目标优化算法；机电一体化调度；动态优先级调整；智能优化模型
Abstract
With the deepening of Industry 4.0, the role of automated production lines in modern manufacturing has become increasingly prominent, and their efficient operation relies on the optimal scheduling of mechatronics systems. This study aims to address the issues of low scheduling efficiency and insufficient resource utilization in current automated production lines by proposing a mechatronics scheduling strategy based on multi-ob jective optimization algorithms. By integrating the advantages of genetic algorithms and particle swarm optimization, a hybrid intelligent optimization model suitable for complex production environments was constructed and validated through simulation using real production line data. The results indicate that the proposed optimization method significantly enhances the overall efficiency of the production line, reduces energy consumption, and minimizes equipment wear, while demonstrating strong robustness and adaptability. Furthermore, this study innovatively introduces a dynamic priority adjustment mechanism, enabling the scheduling system to respond flexibly to real-time changes in production demands and thereby enhancing the system's level of intelligence. The final conclusion reveals that this optimized scheduling strategy not only effectively resolves the static and limited nature of traditional scheduling methods but also provides new insights and theoretical support for the development of scheduling technologies in future smart manufacturing, showcasing significant academic value and application potential..
Key Words：Automation Production Line；Multi-ob jective Optimization Algorithm；Mechatronics Scheduling；Dynamic Priority Adjustment；Intelligent Optimization Model
目 录
摘 要 I
Abstract II
第1章 绪论 1
1.1 自动化生产线优化调度的研究背景 1
1.2 机电一体化优化调度的意义与价值 1
1.3 国内外研究现状与发展趋势 1
1.4 本文研究方法与技术路线 2
第2章 自动化生产线的系统建模与分析 3
2.1 生产线系统架构与功能分解 3
2.2 机电一体化系统的数学建模 3
2.3 关键设备性能参数分析 4
2.4 调度问题的形式化描述 4
2.5 系统建模中的约束条件 5
第3章 优化调度算法的设计与实现 6
3.1 调度优化的目标函数定义 6
3.2 常见调度算法的适用性分析 6
3.3 基于混合智能的优化算法设计 7
3.4 算法复杂度与收敛性分析 7
3.5 算法实现的关键技术与工具 8
第4章 实验验证与结果分析 9
4.1 实验平台搭建与数据采集 9
4.2 不同调度策略的对比实验 9
4.3 优化调度效果的定量评估 10
4.4 实验结果的可视化与解读 10
4.5 实际应用中的挑战与改进建议 11
结 论 11
参考文献 13
致 谢 14
