摘要
汽车制造柔性化、定制化转型背景下,传统厂内物流存在动态生产适配不足、人工分拣依赖、数据协同低效等痛点。本文聚焦汽车入厂物流智能化升级需求与分拣效率瓶颈问题,研究厂内物流模式的技术优化空间与智能技术融合路径,提出“智能仓储–精准分拣–全链路协同”三位一体智能化升级路径及技术方案。通过优化仓储、提升分拣精准度、强化数据协同,破解物流低效僵化问题,推动行业向“低延迟响应、低差执行”智能生态演进,为数字化转型提供参考建议。
In the context of flexible and customized transformation of automobile manufacturing, traditional in-plant logistics has pain points such as insufficient dynamic production adaptation, dependence on manual sorting, and inefficient data collaboration. This paper focuses on the demand for intelligent upgrading of automobile inbound logistics and the bottleneck of sorting efficiency, studies the integration path of technical optimization space and intelligent technology of in-factory logistics mode, and proposes the three-in-one intelligent upgrade path and technical scheme of “intelligent warehousing-precise sorting-full-link collaboration”. By optimizing warehousing, improving sorting accuracy, and strengthening data collaboration, we can solve the problem of inefficient and rigid logistics, promote the industry’s evolution to an intelligent ecosystem of “low-latency response and low-difference execution”, and provide reference suggestions for digital transformation.
出处
《传感器技术与应用》
2025年第4期685-691,共7页
Journal of Sensor Technology and Application
基金
国家级大学生创新创业训练计划项目(202411058043):“汽车零部件物流智能化分拣关键技术研究”。
