摘 要
随着工业4.0的深入推进，机械制造行业对自动化生产线布局优化的需求日益迫切，以提高生产效率、降低成本并增强市场竞争力为此研究的核心背景和出发点本研究旨在针对机械制造中自动化生产线布局问题，提出一种基于多目标优化算法的系统化解决方案通过分析现有生产线布局存在的瓶颈与不足，结合实际生产需求，构建了包含物流距离、设备利用率及能耗等多维度指标的综合评价模型在此基础上，引入改进的遗传算法与模拟退火算法相结合的混合优化策略，有效克服了传统方法在求解复杂布局问题时易陷入局部最优的缺陷经过多次仿真验证与实际案例测试，结果表明该方法能够在保证计算效率的同时显著提升布局方案的合理性与经济性具体而言，优化后的生产线布局使物流总距离平均减少23%，设备利用率提升18%，整体能耗降低15%以上此外，本研究还开发了一套可视化辅助决策工具，为工程技术人员提供直观便捷的操作界面，进一步提升了方案设计与调整的灵活性与实用性综上所述，本研究不仅为机械制造领域的自动化生产线布局优化提供了理论支持和技术手段，还在算法创新与实际应用方面做出了重要贡献，为未来相关研究奠定了坚实基础
关键词：自动化生产线布局；多目标优化算法；遗传算法
Abstract: With the deepening of Industry 4.0, the demand for optimizing the layout of automated production lines in the machinery manufacturing industry has become increasingly urgent, aiming to improve production efficiency, reduce costs, and enhance market competitiveness. This study focuses on the layout optimization of automated production lines in machinery manufacturing and proposes a systematic solution based on multi-ob jective optimization algorithms. By analyzing the bottlenecks and deficiencies of existing production line layouts and integrating actual production requirements, a comprehensive evaluation model is constructed, incorporating multidimensional indicators such as logistics distance, equipment utilization rate, and energy consumption. On this basis, an improved hybrid optimization strategy combining a modified genetic algorithm with simulated annealing is introduced, effectively addressing the limitation of traditional methods that tend to fall into local optima when solving complex layout problems. After multiple simulation verifications and real-world case tests, the results demonstrate that this method significantly enhances the rationality and cost-effectiveness of the layout solutions while maintaining computational efficiency. Specifically, the optimized production line layout reduces the total logistics distance by an average of 23%, increases equipment utilization by 18%, and lowers overall energy consumption by more than 15%. Furthermore, this study develops a set of visualization-based decision-support tools, providing engineering technicians with an intuitive and user-friendly interface, thereby enhancing the flexibility and practicality of design and adjustment processes. In summary, this research not only provides theoretical support and technical means for the optimization of automated production line layouts in the machinery manufacturing field but also makes significant contributions to algorithm innovation and practical application, laying a solid foundation for future related studies.
Keywords: Automation Production Line Layout; Multi-ob jective Optimization Algorithm; Genetic Algorithm
目 录
1绪论 1
1.1机械制造中自动化生产线布局优化的研究背景 1
1.2自动化生产线布局优化研究的意义与价值 1
1.3国内外自动化生产线布局优化研究现状分析 1
1.4本文研究方法与技术路线设计 2
2自动化生产线布局优化的理论基础 2
2.1自动化生产线布局的基本概念与分类 2
2.2布局优化的核心理论框架解析 3
2.3关键影响因素分析及其作用机制 3
2.4数学建模在布局优化中的应用探讨 4
2.5理论基础对实际应用的指导意义 4
3自动化生产线布局优化的关键技术研究 5
3.1数据驱动的生产线布局优化算法分析 5
3.2智能优化算法在布局设计中的应用实践 5
3.3动态调整技术对生产线效率提升的作用 6
3.4基于仿真技术的布局优化方案评估方法 6
3.5技术集成在复杂布局优化中的实现路径 7
4自动化生产线布局优化的实际案例分析 7
4.1典型机械制造企业的布局优化需求分析 7
4.2实际案例中布局优化的目标与约束条件 8
4.3案例实施过程中的关键技术应用与改进 8
4.4布局优化效果评估与经济效益分析 9
4.5案例经验总结与推广价值探讨 9
结论 11
参考文献 12
致 谢 13
