Distributed data management of automation system
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Automation system produces enormous amounts of data. Data is collected from the production process, automation equipment and several other functions related to production. Data is used in reporting, product quality control, maintenance of the automation equipment and improving the production process. Several important issues have to be taken into consideration when planning and implementing data management. Properties of data quality are for example data accuracy and availability. Different kinds of automation applications must be able to access the data and applications also must be able to trust the data. In case of faulty data, reports produced by the application are incorrect. The consequences can be expensive; in the worst case, the whole production line must be shut down when trying to find the source of the incorrect information. In this thesis, the data management of various automation applications was studied. The applications included in the study are used in automation systems in different industries. The objectives for the application study were finding out what kind of data the applications need, what kind of data the application produce, how the collected data is stored and how the stored data is used in further data processing. One objective for this thesis was to find out the problems in the current data management of the automation applications. One problem is the scalability of the automation application in different sized system deliveries. Many of the automation applications require commercial software products, such as operating system and databases. The license fees of these products have a big part in the total cost of a small-sized system delivery. Solution for this problem could be the utilization of Open Source software products. Many Open Source based software products would be feasible, however, there are difficult issues related to the utilization of Open Source products. The license terms of Open Source products and the lack of necessary support are often showstoppers for choosing them. Thesis also investigates effects of new technologies, such as cloud based services and big data, on the data management of automation system. Cloud based services enable the development of new business models. The selection of the cloud provider must be done carefully in order to avoid becoming too dependent on one cloud technology. Changing the technology used in implementing cloud based services could become difficult and very expensive.