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Title:Optimizacija delovnih tokov v ELEI iC
Authors:ID Mramor, Luka (Author)
ID Kljajić Borštnar, Mirjana (Mentor) More about this mentor... New window
ID Skalja, Matic (Comentor)
Files:.pdf MAG_Mramor_Luka_2025.pdf (4,54 MB, This file will be accessible after 03.07.2028)
MD5: B3138D285C393B1BE7ED5A6520289999
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FOV - Faculty of Organizational Sciences in Kranj
Abstract:Zaključno delo obravnava optimizacijo delovnih tokov v podjetju Elea iC, kjer se projektanti pogosto soočajo s časovno potratnimi in ponavljajočimi se nalogami, ki niso neposredno povezane s končnim izdelkom projekta, a so kljub temu nujne za njegovo izvedbo. Te naloge vključujejo primerjavo različic načrtov, digitalizacijo arhivskih zapisov, preverjanje sprememb v projektni dokumentaciji in iskanje podatkov v notranjih bazah. Glavni cilj dela je preučiti možnosti avtomatizacije teh procesov ter raziskati, kako lahko umetna inteligenca in sodobna digitalna orodja prispevajo k večji učinkovitosti in zmanjšanju obremenitve zaposlenih. Pri raziskavi so uporabljene metode analize obstoječih delovnih procesov in testiranja digitalnih rešitev, ki omogočajo avtomatizacijo ponavljajočih se nalog. Poseben poudarek je na implementaciji programskih skript v jeziku Python za avtomatizacijo procesiranja podatkov, uporabi SQL podatkovnih baz za učinkovitejše upravljanje podatkov ter integraciji orodij, kot sta PyCharm in pgAdmin. Umetna inteligenca se v delu uporablja za preverjanje načrtov, brskanje po internih bazah znanja in izboljšanje dostopa do informacij. Rezultati dela kažejo, da je z ustreznimi tehnološkimi rešitvami mogoče znatno skrajšati čas, potreben za izvedbo podpornih nalog, zmanjšati napake pri obdelavi podatkov ter izboljšati preglednost in dostopnost dokumentacije. Optimizacija delovnih procesov z avtomatizacijo prispeva k večji produktivnosti zaposlenih in omogoča projektantom, da se osredotočijo na ključne faze projektiranja, ne pa na administrativna opravila.
Keywords:optimizacija delovnih tokov, avtomatizacija procesov, umetna inteligenca, digitalizacija podatkov
Place of publishing:Maribor
Year of publishing:2025
PID:20.500.12556/DKUM-92499 New window
COBISS.SI-ID:241233667 New window
Publication date in DKUM:03.07.2025
Views:146
Downloads:0
Metadata:XML DC-XML DC-RDF
Categories:FOV
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:14.04.2025

Secondary language

Language:English
Title:Optimization of workflows at ELEA iC
Abstract:This master's thesis examines the optimization of workflows at Elea iC, where designers often face time-consuming and repetitive tasks that are not directly related to the final project deliverable but are nonetheless essential for its execution. These tasks include comparing different versions of plans, digitizing archival records, verifying changes in project documentation, and searching for data within internal databases. The main objective of the thesis is to explore automation possibilities for these processes and investigate how artificial intelligence and modern digital tools can contribute to increased efficiency and reduced workload for employees. The research applies methods of analyzing existing workflows and testing digital solutions that enable automation of repetitive tasks. A particular focus is placed on implementing Python scripts to automate data processing, utilizing SQL databases for more efficient data management, and integrating tools such as PyCharm and pgAdmin. Artificial intelligence is applied to verify project plans, search internal knowledge bases, and improve access to information. The findings demonstrate that appropriate technological solutions can significantly reduce the time required for executing support tasks, minimize errors in data processing, and enhance the transparency and accessibility of documentation. Optimizing workflows through automation contributes to greater productivity among employees and allows designers to focus on key project phases rather than administrative tasks.
Keywords:workflow optimization, process automation, artificial intelligence, data digitization


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