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Advanced teaching and process monitoring environment for the factory of the future

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Kortela, Jukka
dc.contributor.author Nasiri, Babak
dc.contributor.author Lahnalammi, Antton
dc.contributor.author Jämsä-Jounela, Sirkka-Liisa
dc.date.accessioned 2018-12-10T10:25:40Z
dc.date.available 2018-12-10T10:25:40Z
dc.date.issued 2017-03-23
dc.identifier.citation Kortela , J , Nasiri , B , Lahnalammi , A & Jämsä-Jounela , S-L 2017 , Advanced teaching and process monitoring environment for the factory of the future . in Advanced teaching and process monitoring environment for the factory of the future . Automaatiopäivät22 Proceedings , Automaatiopäivät , Vaasa , Finland , 23/03/2017 . en
dc.identifier.other PURE UUID: a4c6cdf1-27d9-4470-91e6-f14e9f6997d2
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/advanced-teaching-and-process-monitoring-environment-for-the-factory-of-the-future(a4c6cdf1-27d9-4470-91e6-f14e9f6997d2).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/17036041/article_automaatiop_iv_t_2017.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/35189
dc.description.abstract ABB Industrial IT Extended Automation System 800xA has been set up for centralized data collection, analysis, real-time monitoring, and advanced control. The ABB system is further expanded by cloud based advanced control and monitoring system. The state-of-the-art ABB setup includes OPC UA, providing a single entry point into a system. Each piece of equipment is automated using a dedicated PLC-station and different fieldbuses, diversifying the teaching and research benefits. The cloud based system will include an OPC UA client which allows access to ABB OPC Server using OPC UA Specifications. OPC UA scales very well in several directions. It allows OPC UA applications to run on embedded devices with very limited hardware resources, as well as on very powerful machines like mainframes. The final set up will run on the high velocity web framework Play that has been especially designed for Java and Scala. Play 2 provides native Akka support (toolkit and runtime) for Play applications enabling writing highly-distributed systems in the cloud. In addition, it follows model–view– controller (MVC) software design pattern, separating the software application into three interconnected parts: models, views, and controllers. The model manages the data, logic, and rules of the application. The monitoring and optimization algorithms are implemented in the model component. In addition, OPC UA client library will be utilized for reading and writing the data from the industrial processes. The proposed advanced teaching and process monitoring system is evaluated with test-algorithms implemented in the Spark cloud and the results are presented, analyzed, and discussed. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Suomen Automaatioseura
dc.relation.ispartof Automaatiopäivät en
dc.relation.ispartofseries Advanced teaching and process monitoring environment for the factory of the future en
dc.relation.ispartofseries Automaatiopäivät22 Proceedings en
dc.rights openAccess en
dc.title Advanced teaching and process monitoring environment for the factory of the future en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.contributor.department Department of Chemical and Metallurgical Engineering
dc.contributor.department School services, CHEM
dc.subject.keyword IoT
dc.subject.keyword cloud computing
dc.subject.keyword OPC UA
dc.subject.keyword advanced control
dc.identifier.urn URN:NBN:fi:aalto-201812106204
dc.type.version proof


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