• Lietuvių
    • English
  • English 
    • Lietuvių
    • English
  • Login
View Item 
  •   DSpace Home
  • Universiteto produkcija / University's production
  • Universiteto leidyba / University's Publishing
  • Konferencijų medžiaga / Conference Materials
  • Tarptautinės konferencijos / International Conferences
  • International Conference "Electrical, Electronic and Information Sciences“ (eStream)
  • 2019 International Conference "Electrical, Electronic and Information Sciences“ (eStream)
  • View Item
  •   DSpace Home
  • Universiteto produkcija / University's production
  • Universiteto leidyba / University's Publishing
  • Konferencijų medžiaga / Conference Materials
  • Tarptautinės konferencijos / International Conferences
  • International Conference "Electrical, Electronic and Information Sciences“ (eStream)
  • 2019 International Conference "Electrical, Electronic and Information Sciences“ (eStream)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Machine Learning Application in Predictive Maintenance

Thumbnail
Date
2019
Author
Liulys, Karolis
Metadata
Show full item record
Abstract
Industrial organizations worldwide cannot ignore Industry 4.0 and its impact to their businesses. The biggest struggle is to find the way how to adopt all the possibilities for each plants unique use cases. In those situations where it is hard to find unified solutions internet is playing major part. Inseparable part of Industry 4.0 is Internet of Things (IoT) paradigm, where it is possible to connect all devices into united system. While robust Distributed Control Systems (DCS) are preferred for their safety, Industrial IoT (IIoT) allows next level prospects: big data performance analyzation, control patterns identification and predictive preventative maintenance by using machine learning algorithms. The study shows how implementing open-source software enables engineers to develop predictive maintenance applications with basic programming knowledge. These type of applications can be widely used in industrial field to inform about possible equipment malfunction helping reduce possible damages.
Issue date (year)
2019
Author
Liulys, Karolis
URI
https://etalpykla.vilniustech.lt/handle/123456789/159523
Collections
  • 2019 International Conference "Electrical, Electronic and Information Sciences“ (eStream) [25]

 

 

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjects / KeywordsInstitutionFacultyDepartment / InstituteTypeSourcePublisherType (PDB/ETD)Research fieldStudy directionVILNIUS TECH research priorities and topicsLithuanian intelligent specializationThis CollectionBy Issue DateAuthorsTitlesSubjects / KeywordsInstitutionFacultyDepartment / InstituteTypeSourcePublisherType (PDB/ETD)Research fieldStudy directionVILNIUS TECH research priorities and topicsLithuanian intelligent specialization

My Account

LoginRegister