Optimizacija procesa prikupljanja i obrade podataka u proizvodnim sustavima

master's thesis

• Title (english): Optimization of data collection and processing in manufacturing systems
• Author: Ana Primorac
• Mentor: Miro Hegedić (mentor)
• Mentor: Mihael Gudlin (komentor)
• Granter: University of Zagreb; Faculty of Mechanical Engineering and Naval Architecture; Zagreb
• Defense date and country: 2024-03-28, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mechanical Engineering; Production Mechanical Engineering

Abstract

Ovaj diplomski rad fokusira se na primjenu softverskog rješenja kako bi se odgovorilo na specifične izazove unutar proizvodnje. Kroz analizu i obradu podataka koristeći Mailab softver, istražuju se mogućnosti optimizacije proizvodnih procesa primjenom algoritama umjetne inteligencije i znanosti o podacima. Cilj istraživanja je pružiti uvid u važnost softvera u rješavanju kompleksnosti proizvodnih okruženja te demonstrirati konkretnu primjenu MaiLab-a u prikupljanju, analizi i optimizaciji podataka. Kroz studiju slučaja, rad ilustrira kako se ovi alati mogu integrirati u stvarna proizvodna okruženja radi postizanja učinkovitijih i optimalnih procesa. Kroz ovu analizu, istraživanje također pokušava identificirati buduće smjerove razvoja i unapređenja kako bi se dodatno potaknula integracija softverskih rješenja u proizvodne sektore.

Abstract (english)

This paper focuses on the application of software solution to address specific challenges within manufacturing. Through the analysis and processing of data using Mailab software, the possibilities of optimizing manufacturing processes are explored by applying artificial intelligence algorithms and data science. The research aims to provide insights into the importance of software in tackling the complexities of manufacturing environments and to demonstrate the practical application of Mailab in data collection, analysis, and optimization. Through a case study, the paper illustrates how these tools can be integrated into real manufacturing environments to achieve more efficient and optimal processes. In this analysis, the research also attempts to identify future development directions and improvements to further encourage the integration of software solutions in manufacturing sectors.

• Keywords: znanost o podacima; umjetna inteligencija; strojno učenje; analiza podataka; optimizacija; proizvodni procesi
• Keywords (english): data science; artificial intelligence; machine learning; data analysis; optimization; production processes
• Language: croatian
• URN:NBN: urn:nbn:hr:235:718227
• Study programme: Title: Mechanical Engineering; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka strojarstva (magistar/magistra inženjer/inženjerka strojarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-03-21 10:44:11