Development of systems and processes of Mobile Voice Core network operations
Lahtinen, Anton (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051512038
https://urn.fi/URN:NBN:fi:amk-2025051512038
Tiivistelmä
The objective of this thesis was to improve the operational efficiency and documentation practices of Mobile Voice Core network operations at a Finnish telecommunications company. The objective was to reduce manual work, enhance knowledge sharing, and explore opportunities for automation.
The study was based on structured staff surveys and open-ended questions, followed by the technical development and phased implementation of selected solutions. Python-based automation scripts were created to compare configuration files, and operational documentation was restructured into a centralized wiki platform. A password management solution was also evaluated. These activities addressed identified needs and supported daily operational tasks.
The result met the client’s needs by improving visibility into network changes, reducing time spent on routine work, and ensuring consistent access to critical information. The automation solution is already in use, and the improved documentation framework is being gradually adopted by the team.
Further development should focus on integrating more advanced automation features and exploring the application of artificial intelligence in operational monitoring and predictive maintenance.
The study was based on structured staff surveys and open-ended questions, followed by the technical development and phased implementation of selected solutions. Python-based automation scripts were created to compare configuration files, and operational documentation was restructured into a centralized wiki platform. A password management solution was also evaluated. These activities addressed identified needs and supported daily operational tasks.
The result met the client’s needs by improving visibility into network changes, reducing time spent on routine work, and ensuring consistent access to critical information. The automation solution is already in use, and the improved documentation framework is being gradually adopted by the team.
Further development should focus on integrating more advanced automation features and exploring the application of artificial intelligence in operational monitoring and predictive maintenance.