Reporting system for large process plants
Eiranto, Seppo (2022)
Eiranto, Seppo
2022
Automaatiotekniikan DI-ohjelma - Master's Programme in Automation Engineering
Tekniikan ja luonnontieteiden tiedekunta - Faculty of Engineering and Natural Sciences
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Hyväksymispäivämäärä
2022-04-20
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202203232717
https://urn.fi/URN:NBN:fi:tuni-202203232717
Tiivistelmä
Reporting is an integral part of the automation systems of process plants. Process plants require extensive daily and monthly reports, that combine production and expenditures, to help with business decision making. These kinds of reports support production and warehouse status monitoring. However current solutions make this kind of reporting cumbersome and use a lot of computing resources because of the scope of these reports.
The amount of data in automation systems has risen rapidly in the past years. Data is collected in time continuous databases and is not easily always addressed to the correct day or event. To use this data to support business decisions it needs to be processed and possibly integrated from multiple sources which requires computing resources.
A popular way to solve these kinds of problems in computing systems has been extract, transform, load (ETL) systems and the goal of this thesis was to find out the requirements for an ETL based system in the context of Valmet DNA. The second goal of this thesis was to find out how to implement it. Research of this thesis included reviewing database technologies and their respective properties, and different ETL systems. In addition common problems of aggregating time series data is researched and a validation procedure is implemented to correct these issues manually where they couldn’t be fixed at the source.
The results of the thesis show the implementation and results seen in the prototype of this software. These values are compared to existing systems results.
The amount of data in automation systems has risen rapidly in the past years. Data is collected in time continuous databases and is not easily always addressed to the correct day or event. To use this data to support business decisions it needs to be processed and possibly integrated from multiple sources which requires computing resources.
A popular way to solve these kinds of problems in computing systems has been extract, transform, load (ETL) systems and the goal of this thesis was to find out the requirements for an ETL based system in the context of Valmet DNA. The second goal of this thesis was to find out how to implement it. Research of this thesis included reviewing database technologies and their respective properties, and different ETL systems. In addition common problems of aggregating time series data is researched and a validation procedure is implemented to correct these issues manually where they couldn’t be fixed at the source.
The results of the thesis show the implementation and results seen in the prototype of this software. These values are compared to existing systems results.