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.
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.
| Original language | English |
|---|---|
| Title of host publication | Advanced teaching and process monitoring environment for the factory of the future |
| Publication status | Published - 23 Mar 2017 |
| MoE publication type | D3 Professional conference proceedings |
| Event | Automaatiopäivät - Vaasa, Finland Duration: 23 Mar 2017 → 24 Mar 2017 Conference number: 22 |
Publication series
| Name | Automaatiopäivät22 Proceedings |
|---|---|
| Publisher | Suomen Automaatioseura |
Conference
| Conference | Automaatiopäivät |
|---|---|
| Country/Territory | Finland |
| City | Vaasa |
| Period | 23/03/2017 → 24/03/2017 |
Keywords
- IoT
- cloud computing
- OPC UA
- advanced control