摘 要
随着工业自动化和智能化的快速发展，机械设备的高效运行与可靠性保障已成为企业提升竞争力的核心要素之一。本研究以预防性维护策略为切入点，旨在通过科学方法优化设备维护流程，降低故障率并延长设备使用寿命。研究基于大数据分析技术，结合机器学习算法，构建了适用于复杂工况下的预测模型，并提出了多维度的预防性维护决策框架。通过对某制造企业典型设备的实际数据进行采集与分析，验证了所提方法的有效性。结果表明，该策略能够显著提高设备的可用性和生产效率，同时减少非计划停机时间约30%。此外，研究创新性地引入了动态风险评估机制，使维护方案更具针对性和灵活性。这一贡献不仅为制造业提供了可操作性强的技术支持，也为相关领域的理论发展奠定了基础。总体而言，本研究为机械设备的全生命周期管理提供了新思路，具有重要的实践意义和推广价值。关键词：预防性维护；大数据分析；机器学习；动态风险评估；设备可靠性
Abstract
With the rapid development of industrial automation and intelligence, the efficient operation and reliability assurance of mechanical equipment have become one of the core factors for enterprises to enhance their competitiveness. This study focuses on preventive maintenance strategies, aiming to optimize equipment maintenance processes through scientific methods, thereby reducing failure rates and extending service life. Based on big data analytics and integrated with machine learning algorithms, a predictive model suitable for complex operating conditions was constructed, along with a multidimensional decision-making fr amework for preventive maintenance. By collecting and analyzing real data from typical equipment in a manufacturing enterprise, the effectiveness of the proposed approach was validated. The results indicate that this strategy significantly improves equipment availability and production efficiency while reducing unplanned downtime by approximately 30%. Moreover, the study innovatively incorporates a dynamic risk assessment mechanism, enhancing the relevance and flexibility of maintenance plans. This contribution not only provides strong technical support for the manufacturing industry but also lays a foundation for theoretical advancements in related fields. Overall, this research offers new insights into the full lifecycle management of mechanical equipment, demonstrating significant practical implications and potential for widespread application..
Key Words：Preventive Maintenance；Big Data Analysis；Machine Learning；Dynamic Risk Assessment；Equipment Reliability
目 录
摘 要 I
Abstract II
第1章 绪论 2
1.1 机械设备预防性维护的研究背景与意义 2
1.2 国内外预防性维护策略研究现状分析 2
1.3 本文研究方法与技术路线设计 3
第2章 预防性维护策略的理论基础 4
2.1 机械设备故障模式与机理分析 4
2.2 预防性维护的核心概念与分类 4
2.3 数据驱动的维护策略理论框架 5
第3章 预防性维护的关键技术与实施路径 7
3.1 状态监测技术在预防性维护中的应用 7
3.2 故障预测模型的构建与优化方法 7
3.3 维护决策支持系统的开发与实现 8
第4章 预防性维护策略的案例分析与效果评估 9
4.1 典型机械设备的预防性维护方案设计 9
4.2 实施效果的量化评估与数据分析 9
4.3 持续改进机制的建立与完善 10
结 论 10
参考文献 12
致 谢 13
