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Modeling of image, video and text fusion quality data packet system for aerospace complex products based on business intelligence

机译:基于商业智能的航空航天复杂产品图像,视频和文本融合质量数据包系统建模

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For the construction of image, video and text fusion quality data packet system during the whole life of complex products, a business intelligence-based logic modeling method is proposed in this paper. As the amount of Polymorphic data from multiple distributed sources continues to grow exponentially, automation tools are becoming critical to decision makers. The balanced scorecard method is used as the basis for modeling, and the traditional dimensions are modified slightly to meet the requirements of quality data management in aerospace enterprises. A data warehouse with predefined fact and dimension tables is created, and a technical solution is provided to meet the requirements and scales of enterprises. In terms of model applications, any enterprise quality manager can extract value from data in the quality data package system for improvement. Online analytical processing (OLAP) cubes support major tasks, such as key quality feature source tracing and analysis, quality issue data mining and integrated quality data delivery. (C) 2018 Published by Elsevier Inc.
机译:为了构建复杂产品整个生命周期中的图像,视频和文本融合质量数据包系统,提出了一种基于商业智能的逻辑建模方法。随着来自多个分布式源的多态数据量呈指数增长,自动化工具对于决策者而言变得至关重要。平衡计分卡法被用作建模的基础,对传统尺寸进行了略微修改以满足航空航天企业质量数据管理的要求。创建具有预定义事实和维度表的数据仓库,并提供技术解决方案以满足企业的需求和规模。在模型应用方面,任何企业质量经理都可以从质量数据包系统中的数据中提取价值以进行改进。在线分析处理(OLAP)多维数据集支持主要任务,例如关键质量特征源跟踪和分析,质量问题数据挖掘以及集成质量数据交付。 (C)2018由Elsevier Inc.发布

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