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

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.