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汽车涂装专业数智制造研究与应用OA

Research and Application of Professional Digital Intelligent Manufacturing in Automotive Coating

中文摘要英文摘要

汽车市场竞争加剧,整车制造成本优化及营销效益提升的压力剧增.为此提出借助数智化手段,构建敏捷数智生产组织,降本增效、提升产品竞争力.通过梳理涂装车间经营的核心业务,结合从整车制造分工抽象出的智能制造切片模型,提出"一个大脑,五觉感知"的数智化框架.在管理平台大脑层面,重点基于高质量构建,围绕现场作业、输出评价、环境条件3个方面,设计实现了过程质量数字管理系统;围绕安全及项目管理、基础业务管理、维修费用管控,设计实现了设备数字化管理系统.在感知应用层面,重点围绕视觉应用,设计实现了滑橇尺寸在线检测、车身堵件错漏装自动检测.生产现场实践运用结果表明,所提敏捷数智生产组织方案可有效提升相关业务管理的及时性、准确性,敏捷业务信息决策过程,提升车间业务管理水平.

The competition in the automobile market is increasing,and the pressure of optimizing vehicle manufacturing cost and improving marketing efficiency is intensified.In view of this,an agile digital intelligence production organization is built by means of digital intelligence to reduce cost and increase efficiency and enhance product competitiveness.By combing the core business of the coating shop and combining with the intelligent manufacturing slice model abstracted from the division of labor of vehicle manufacturing,the digital intellectualization framework of"one brain,five senses perception"is proposed.At the brain level of management platform,the process quality digital management system is designed and implemented based on high-quality construction,focusing on three aspects:field operation,output evaluation and environmental conditions.Focusing on security and project management,basic business management and maintenance cost control,the equipment digital management system is designed and implemented.On the perception application level,focusing on the visual application,the design and realization of the skid size online detection,the automatic detection of the body plug parts.The practical application results show that the proposed agile digital intelligence production organization scheme can effectively improve the timeliness and accuracy of related business management,agile business information decision-making process,and improve the level of business management in the workshop.

关林君;黄龙武;肖方挺;王煜

一汽-大众汽车有限公司佛山分公司,广东佛山 528200

机械工程

整车制造数智化过程质量设备管理感知应用

vehicle manufacturingdigital intelligenceprocess qualitydevice managementperceptual application

《机电工程技术》 2024 (008)

172-176,190 / 6

10.3969/j.issn.1009-9492.2024.08.037

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