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Systems integration and verification in an advanced smart factory

机译：先进智能工厂中的系统集成和验证

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In 2014, Raytheon Missile Systems began work on creating a new satellite manufacturing facility in Tucson, AZ. The primary objective of this new factory was to minimize costly human-based oversight inspection while increasing the level of quality assurance related to the assembly process. Unlike assembly lines which produce hundreds or even thousands of the same item on a continuous basis, the new factory had to be adaptable to doing "one-of-a-kind" production. In order to assure a high-level of confidence in the proper assembly and testing of such unique space assets, the Raytheon team architected an approach that incorporated some of the newest advances in information technology and robotic testing. The factory relies on an event-driven architecture that incorporates streaming analytics as the basis for removing human quality control observers. An integrated sensor network and a supporting information system powered by open source software securely receives, stores, and analyzes the data streams. The data management platform known as the Open Manufacturing Information System or OMIS, is based on the Apache Hadoop environment. Hadoop provides the power and flexibility that enables rapid adjustment to changing customer requirements and differences between each satellite that is brought into the factory.
机译：2014年，雷神导弹系统公司开始在亚利桑那州图森创建新的卫星制造工厂。这个新工厂的主要目标是最大程度地减少成本高昂的基于人的监督检查，同时提高与组装过程相关的质量保证水平。与连续生产成百上千个相同项目的装配线不同，新工厂必须适应进行“独一无二”的生产。为了确保对这种独特的太空资产的正确组装和测试有高度的信心，雷神团队设计了一种方法，该方法结合了信息技术和机器人测试中的一些最新进展。该工厂依赖于事件驱动的体系结构，该体系结构将流分析作为消除人工质量控制观察员的基础。由开源软件提供支持的集成传感器网络和支持信息系统可以安全地接收，存储和分析数据流。称为开放制造信息系统或OMIS的数据管理平台基于Apache Hadoop环境。 Hadoop提供了强大的功能和灵活性，可以快速调整以适应不断变化的客户需求以及工厂中每颗人造卫星之间的差异。

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