首页> 外文期刊>Journal of Visual Languages & Computing >Visually enhanced situation awareness for complex manufacturing facility monitoring in smart factories
【24h】

Visually enhanced situation awareness for complex manufacturing facility monitoring in smart factories

机译:视觉增强的态势感知,用于智能工厂中复杂的制造设施监控

获取原文
获取原文并翻译 | 示例

摘要

With the widespread application of networked information-based technologies throughout industry manufacturing, modern manufacturing facilities give rise to unprecedented levels of process data generation. Data-rich manufacturing environments provide a broad stage on which advanced data analytics play leading roles in creating manufacturing intelligence to support operational efficiency and process innovation. In this paper, we introduce a process data analysis solution that integrates the technologies of situation awareness and visual analytics for the routine monitoring and troubleshooting of roller hearth kiln (RHK), a complex key manufacturing facility for lithium battery cathode materials. Guided by a set of detailed scenarios and requirement analyses, we first propose a qualitative and quantitative situation assessment model to generate the comprehensive description of RHK's operating situation. An informative visual analysis system then is designed and implemented to enhance the users' abilities of situation perception and understanding for insightful anomaly root cause reasoning and efficient decision making. We conduct case studies and a user interview together with the managers and operators from manufacturing sites as system evaluation. The result demonstrates its effectiveness and prospects its possible inspiration for other similar scenarios about complex manufacturing facility monitoring in smart factories. (C) 2017 Elsevier Ltd. All rights reserved.
机译:随着基于网络的信息技术在整个工业制造中的广泛应用,现代化的制造设施带来了前所未有的过程数据生成水平。数据丰富的制造环境提供了广阔的舞台,高级数据分析在创建制造智能以支持运营效率和流程创新方面发挥着主导作用。在本文中,我们介绍了一种过程数据分析解决方案,该解决方案集成了态势感知和可视化分析技术,可对辊底窑(RHK)(锂电池正极材料的复杂关键制造设施)进行例行监视和故障排除。在一系列详细的方案和需求分析的指导下,我们首先提出定性和定量的情况评估模型,以全面描述RHK的运营情况。然后,将设计并实施一个信息丰富的视觉分析系统,以增强用户的情境感知和理解能力,从而洞悉异常的根本原因并进行有效的决策。我们与制造现场的经理和操作员一起进行案例研究和用户访谈,作为系统评估。结果证明了其有效性,并有望为其他有关智能工厂中复杂的生产设施监控的类似情况提供灵感。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号