摘 要
机械制造是现代工业的重要组成部分，其产品质量直接关系到整个产业链的稳定与发展。为提高机械制造过程中的产品质量，确保产品性能与可靠性，本文聚焦于质量控制与检测技术的研究。通过对国内外相关研究现状的分析，发现现有质量控制体系在实时性、精确度和智能化方面存在不足。为此，本研究提出了一种基于物联网与大数据分析的智能质量控制系统，该系统集成了在线监测、数据采集、故障诊断等功能模块。通过在实际生产线上应用高精度传感器网络，实现了对加工参数的实时监控；利用机器学习算法对海量生产数据进行深度挖掘，建立了预测性维护模型。实验结果表明，该系统能够有效降低次品率约30%，缩短检测周期达40%，显著提高了生产效率。此外，本文还探讨了不同检测技术（如无损检测、光学测量等）的应用场景及其优缺点，提出了多模态融合检测方案，以应对复杂工件的质量评估需求。
关键词：机械制造质量控制 智能质量控制系统 物联网与大数据分析
Abstract
Machinery manufacturing is an important part of modern industry, and its product quality is directly related to the stability and development of the whole industrial chain. In order to improve the product quality in the mechanical manufacturing process and ensure the product performance and reliability, this paper focuses on the research of quality control and testing technology. Through the analysis of relevant research status at home and abroad, it is found that the existing quality control system is insufficient in real-time, accuracy and intelligence. To this end, this study proposes an intelligent quality control system based on Internet of Things and big data analysis, which integrates functional modules such as online monitoring, data acquisition and fault diagnosis. By applying high-precision sensor network to the real production line, the real-time monitoring of processing parameters is realized to mine massive production data and establish predictive maintenance model. The experimental results show that the system can effectively reduce the defective product rate by about 30%, shorten the detection cycle by 40%, and significantly improve the production efficiency. In addition, this paper also discusses the application scenarios and their advantages and disadvantages of different detection technologies (such as nondestructive testing, optical measurement, etc.), and proposes a multi-mode fusion detection scheme to meet the quality assessment requirements of complex artifacts.
Keyword:Mechanical Manufacturing Quality Control Intelligent Quality Control System Internet Of Things And Big Data Analysis
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3研究方法与技术路线 2
2质量控制体系构建 2
2.1质量控制的基本原则 2
2.2标准化流程的建立 3
2.3关键工序的质量管理 3
3检测技术的应用与发展 4
3.1常用检测技术概述 4
3.2在线检测技术应用 4
3.3检测数据的分析处理 5
4质量改进与持续优化 5
4.1质量问题的识别与分析 6
4.2改进措施的制定与实施 6
4.3持续优化的长效机制 7
结论 7
参考文献 9
致谢 10
