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Streaming Machine Generated Data to Enable a Third-Party Ecosystem of Digital Manufacturing Apps

机译:流式机器生成数据以启用数字制造应用程序的第三方生态系统

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The digital factory of the future will be driven by the integration of physical smart machine tools and cyber-enabled software, working seamlessly to increase manufacturing intelligence, flexibility, agility and production efficiency. The objective of this study is develop and demonstrate a middleware software architecture to interface physical machines on a shop floor with client manufacturing applications. We have connected both legacy and modern 'smart' machines to a highly scalable database capable of storing streaming time-series data generated by on-board sensors and machine controllers. Three client applications were developed to demonstrate the mechanism through which third-party apps can be written without direct physical communications with machines on the shop-floor. The first, is an application that resides within the Digital Manufacturing Commons (DMC) which demonstrates the ability to query data from any physical machine on the floor; the 2nd application demonstrates a python app which compares digital product data with machine generated data; and the 3rd application demonstrates building a LabView app built to interface with the middleware service. This proposed architecture enables an ecosystem of smart manufacturing applications to be built and deployed on the shop-floor through open-sourced software and hardware devices thereby reducing cost of manufacturing software development.
机译:未来的数字工厂将由物理智能机床和网络软件集成,无缝工作,以提高制造智能,灵活性,敏捷性和生产效率。本研究的目的是开发和展示中间件软件架构,以在商店地板上与客户的制造应用接口物理机器。我们已将旧版和现代的“智能”机器连接到高度可扩展的数据库,该数据库能够存储由板载传感器和机器控制器生成的流式时序序列数据。开发了三个客户应用程序,以演示第三方应用程序的机制,而不会与商店地板上的机器直接进行直接的物理通信。首先,是驻留在数字制造公约(DMC)内的应用程序,该应用程序演示了从地板上的任何物理机器查询数据的能力;第二应用程序演示了一个Python应用程序,它将数字产品数据与机器生成的数据进行比较;第3个应用程序演示构建建立与中间件服务接口的LabVIEW应用程序。该拟议的架构使智能制造应用程序的生态系统能够通过开放的软件和硬件设备在商店地板上构建和部署,从而降低了制造软件开发的成本。

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