摘 要
智能制造环境下，机械装备的可靠性设计已成为提升工业生产效率与质量的关键环节。随着工业4.0理念的深入推广，传统机械装备的设计方法已难以满足复杂多变的生产需求，亟需探索适应智能制造特点的可靠性设计策略。本研究旨在通过融合现代信息技术与可靠性工程理论，构建一种面向智能制造环境的机械装备可靠性设计框架。研究采用系统建模与仿真分析相结合的方法，重点探讨了基于大数据的故障预测模型、动态可靠性评估体系以及智能化维护决策机制。结果表明，所提出的框架能够显著提高机械装备在复杂工况下的运行稳定性，并有效降低全生命周期内的故障率。
关键词：智能制造 可靠性设计 大数据故障预测
Abstract
In the intelligent manufacturing environment, the reliability design of mechanical equipment has become the key link to improve the industrial production efficiency and quality. With the further promotion of the concept of industry 4.0, the design method of traditional mechanical equipment has been difficult to meet the complex and changeable production needs, and it is urgent to explore the reliability design strategy adapted to the characteristics of intelligent manufacturing. This study aims to construct a reliability design fr amework for intelligent manufacturing environment by integrating modern information technology and reliability engineering theory. The research adopts the method of combining system modeling and simulation analysis, and focuses on the fault prediction model, dynamic reliability evaluation system and intelligent maintenance decision mechanism based on big data. The results show that the proposed fr amework can significantly improve the operating stability of mechanical equipment under complex working conditions, and effectively reduce the failure rate in the whole life cycle.
Keyword:Intelligent Manufacturing Reliability Design Big Data Fault Prediction
目 录
1绪论 1
1.1智能制造与可靠性设计的背景 1
1.2国内外研究现状分析 1
1.3本文研究方法与技术路线 2
2智能制造环境下的可靠性需求分析 2
2.1智能制造对机械装备可靠性的挑战 2
2.2可靠性设计的关键影响因素 3
2.3数据驱动的可靠性需求评估 3
3智能制造环境下可靠性设计理论与方法 4
3.1基于数字化模型的可靠性设计框架 4
3.2多学科协同的可靠性优化方法 4
3.3智能算法在可靠性设计中的应用 5
4智能制造中可靠性验证与评估技术 5
4.1虚拟仿真在可靠性验证中的作用 5
4.2实时监测与故障预测技术 6
4.3可靠性评估指标体系构建 6
结论 7
参考文献 8
致谢 9
智能制造环境下，机械装备的可靠性设计已成为提升工业生产效率与质量的关键环节。随着工业4.0理念的深入推广，传统机械装备的设计方法已难以满足复杂多变的生产需求，亟需探索适应智能制造特点的可靠性设计策略。本研究旨在通过融合现代信息技术与可靠性工程理论，构建一种面向智能制造环境的机械装备可靠性设计框架。研究采用系统建模与仿真分析相结合的方法，重点探讨了基于大数据的故障预测模型、动态可靠性评估体系以及智能化维护决策机制。结果表明，所提出的框架能够显著提高机械装备在复杂工况下的运行稳定性，并有效降低全生命周期内的故障率。
关键词：智能制造 可靠性设计 大数据故障预测
Abstract
In the intelligent manufacturing environment, the reliability design of mechanical equipment has become the key link to improve the industrial production efficiency and quality. With the further promotion of the concept of industry 4.0, the design method of traditional mechanical equipment has been difficult to meet the complex and changeable production needs, and it is urgent to explore the reliability design strategy adapted to the characteristics of intelligent manufacturing. This study aims to construct a reliability design fr amework for intelligent manufacturing environment by integrating modern information technology and reliability engineering theory. The research adopts the method of combining system modeling and simulation analysis, and focuses on the fault prediction model, dynamic reliability evaluation system and intelligent maintenance decision mechanism based on big data. The results show that the proposed fr amework can significantly improve the operating stability of mechanical equipment under complex working conditions, and effectively reduce the failure rate in the whole life cycle.
Keyword:Intelligent Manufacturing Reliability Design Big Data Fault Prediction
目 录
1绪论 1
1.1智能制造与可靠性设计的背景 1
1.2国内外研究现状分析 1
1.3本文研究方法与技术路线 2
2智能制造环境下的可靠性需求分析 2
2.1智能制造对机械装备可靠性的挑战 2
2.2可靠性设计的关键影响因素 3
2.3数据驱动的可靠性需求评估 3
3智能制造环境下可靠性设计理论与方法 4
3.1基于数字化模型的可靠性设计框架 4
3.2多学科协同的可靠性优化方法 4
3.3智能算法在可靠性设计中的应用 5
4智能制造中可靠性验证与评估技术 5
4.1虚拟仿真在可靠性验证中的作用 5
4.2实时监测与故障预测技术 6
4.3可靠性评估指标体系构建 6
结论 7
参考文献 8
致谢 9
