Machine learning integration to conditional monitoring system in industrial automation: Data clustering case study
No Thumbnail Available
URL
Journal Title
Journal ISSN
Volume Title
Sähkötekniikan korkeakoulu |
Master's thesis
Authors
Date
2020-06-15
Department
Major/Subject
Control, Robotics and Autonomous Systems
Mcode
ELEC3025
Degree programme
Master’s Programme in Automation and Electrical Engineering
Language
en
Pages
62 + 2
Series
Abstract
Machine learning applications are becoming more and more popular in numerous sectors of the industry nowadays. Industrial automation in general and factory automation in particular is a big market in which a large number of enterprises have tried to put their footprint onto this highly potential market. Our company - InSolution Oy, like others, found a demand for a machine learning system to integrate into its existing conditional monitoring platform. While a large number of enterprises have implemented their machine learning systems locally, the others have chosen to build with cloud computing platforms. However, generally, those machine learning applications are standalone and rarely integrate into conditional monitoring system. This thesis provides a particular method and solution for integrating machine learning applications into the industrial automation sector based on a case study from InSolution Oy. Also, this project presents a comprehensive comparison among different popular cloud platforms to offer InSolution Oy an overview of the machine learning development feasibility in a cloud platform.Description
Supervisor
Vyatkin, ValeriyThesis advisor
Katajisto, JuhaKeywords
machine learning, integration, conditional monitoring, industrial automation, factory automation, architecture