prikaz prve stranice dokumenta Process monitoring and predictive diagnostics
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undergraduate thesis
Process monitoring and predictive diagnostics
Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology, 2019. urn:nbn:hr:149:648802
Brzović, Adriana
University of Zagreb
Faculty of Chemical Engineering and Technology

Institutional repository: Repository of Faculty of Chemical Engineering and Technology University of Zagreb

Cite this document

Brzović, A. (2019). Process monitoring and predictive diagnostics (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology. Retrieved from https://urn.nsk.hr/urn:nbn:hr:149:648802

Brzović, Adriana. "Process monitoring and predictive diagnostics." Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2019. https://urn.nsk.hr/urn:nbn:hr:149:648802

Brzović, Adriana. "Process monitoring and predictive diagnostics." Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, 2019. https://urn.nsk.hr/urn:nbn:hr:149:648802

Brzović, A. (2019). 'Process monitoring and predictive diagnostics', Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, accessed 25 August 2024, https://urn.nsk.hr/urn:nbn:hr:149:648802

Brzović A. Process monitoring and predictive diagnostics [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Chemical Engineering and Technology; 2019 [cited 2024 August 25] Available at: https://urn.nsk.hr/urn:nbn:hr:149:648802

A. Brzović, "Process monitoring and predictive diagnostics", Undergraduate thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:149:648802

Metadata
TitleProcess monitoring and predictive diagnostics
Title (croatian)Nadziranje i prediktivna dijagnostika procesa
AuthorAdriana Brzović
MentorNenad Bolf (mentor)
Committee memberNenad Bolf (predsjednik povjerenstva)
Committee memberAleksandra Sander (član povjerenstva)
Committee memberŽeljka Ujević Andrijić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Chemical Engineering and Technology
Zagreb
Defense date and country2019-09-19, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Chemical Engineering
Abstract
As technology advances, particularly in the IT sector, more and more companies running large-scale industrial operations look to computer based solutions to replace expensive monitoring and maintenance methods. Machine learning is one such solution gaining popularity in the last couple of years. This paper explores how machine learning models can be used for preventative and predictive maintenance of an industrial heat exchanger by continuously detecting fouling formation. The results of the neural network model show successful prediction of fouling formation in the heat exchanger. Random forest model does not successfully predict fouling formation as it cannot extrapolate on new data. The results of this study show great potential in application of machine learning methods in the industry for improving production processes in terms of greater efficiency, energy and raw material saving.
Abstract (croatian)
Uz napredak tehnologije, posebno IT sektora, javlja se sve veća potreba za računalnim rješenjima koja bi zamijenila skupe metode nadziranja i održavanja procesa u velikim proizvodnim pogonima. Jedno od takvih rješenja s rastućom popularnošću u zadnjih nekoliko godina je strojno učenje. Ovaj rad istražuje primjenu modela strojnog učenja za nadziranje i prediktivnu dijagnostiku industrijskog izmjenjivača topline pomoću kontinuiranog praćenja nastajanja naslaga. Razvijen je model neuronske mreže i model slučajnih šuma. Rezultati razvijenog modela neuronske mreže pokazuju uspješno predviđanje nastajanja naslaga u izmjenjivaču topline. Model slučajnih šuma ne predviđa uspješno nastajanje naslaga zbog nemogućnosti ekstrapoliranja na novim podatcima. Rezultati ostvareni u ovom radu pokazuju veliki potencijal primjene metoda strojnog učenja u industriji za poboljšanje proizvodnih procesa u pogledu veće učinkovitosti, uštede energije i sirovina.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:149:648802
Study programmeTitle: Chemical Engineering - Undergraduate study
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka kemijskog inženjerstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka kemijskog inženjerstva)
Type of resourceText
File originBorn digital
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Created on2023-02-14 08:42:35