Google Cloud and solution for industrial automation systems

Abstract

This master’s thesis introduces a possible architecture with the Google cloud platform for storing industrial time-series data from automation programmable logic controller (PLC), and how different messages from PLC are categorized. Master’s thesis introduces three cases of how stored data can be used to gain information from the system. The solution presents a way to divide software responsibilities between local and cloud entity. In the architecture, few cases as to how data is handled locally and writing messages to the cloud are explained with more detail and code examples.

The solution was developed concurrently with a new underlying system and because there was no easy to use and flexible solution that offered needed requirements. The solution includes interfaces and generalization that it is not dependent on the underlying system, and architecture is usable with different systems. The architecture was decided to be de- veloped in a cloud platform that would enable global distribution with additional hosted tools.