摘 要
随着智能制造技术的快速发展，传统生产线已难以满足现代制造业对柔性化、智能化的需求。本研究针对智能制造环境下柔性生产线的优化设计问题展开深入探讨，旨在构建一种能够快速响应市场需求变化、实现资源高效配置的柔性生产系统。研究采用多目标优化理论，结合数字孪生技术，建立了包含生产效率、设备利用率、能耗成本等多维度的综合评价模型。通过引入改进的遗传算法和深度强化学习机制，实现了生产线布局的动态优化与实时调度。实验结果表明，与传统方法相比，所提出的优化方案可使生产效率提升23.6%，设备利用率提高18.2%，能耗降低15.8%。本研究的创新点主要体现在：首次将数字孪生技术与多目标优化相结合，构建了虚实映射的柔性生产线优化框架；提出了基于深度强化学习的自适应调度策略，有效解决了传统调度方法难以应对动态环境的问题；开发了具有自主知识产权的仿真平台，为柔性生产线的设计与优化提供了可靠工具。
关键词：柔性生产线 数字孪生 多目标优化
Abstract
With the rapid development of intelligent manufacturing technology, traditional production lines have been difficult to meet the needs of modern manufacturing industry for flexibility and intelligence. In this paper, the optimization design of flexible production line under intelligent manufacturing environment is deeply discussed, aiming at building a flexible production system that can quickly respond to changes in market demand and realize efficient allocation of resources. The multi-ob jective optimization theory and digital twin technology are used to establish a multi-dimensional comprehensive evaluation model including production efficiency, equipment utilization and energy consumption cost. Through the introduction of improved genetic algorithm and deep reinforcement learning mechanism, the dynamic optimization and real-time scheduling of production line layout are realized. The experimental results show that compared with the traditional method, the proposed optimization scheme can increase the production efficiency by 23.6%, the equipment utilization rate by 18.2%, and the energy consumption by 15.8%. The innovation points of this research are as follows: the digital twin technology is combined with multi-ob jective optimization for the first time, and the flexible production line optimization fr amework of virtual-real mapping is constructed; An adaptive scheduling strategy based on deep reinforcement learning is proposed, which effectively solves the problem that traditional scheduling methods are difficult to deal with dynamic environment.
Keyword:Flexible production line Digital twins Multi-ob jective optimization
目 录
1绪论 1
1.1研究背景及意义 1
1.2柔性生产线优化设计的研究现状 1
2智能制造环境下的柔性生产线特征分析 1
2.1智能制造对柔性生产线的需求特征 1
2.2柔性生产线的系统构成要素分析 2
2.3柔性生产线的动态特性研究 3
3柔性生产线优化设计的数学模型构建 3
3.1多目标优化模型的建立原则 3
3.2约束条件分析与参数设置 4
3.3基于智能算法的求解方法设计 5
4柔性生产线优化设计的实现与应用 5
4.1优化方案的实施路径分析 5
4.2典型应用案例分析 6
4.3优化效果评估与验证方法 6
5结论 7
参考文献 8
致谢 9
