Browsing Institutt for maskinteknikk og produksjon by Title
Now showing items 2278-2297 of 3970
-
Machinability of Low-Lead and Lead-Free Brass Alloys
(Doctoral thesis, 2024) -
Machine Learning (ML)-Based Prediction and Compensation of Springback for Tube Bending
(Chapter, 2021)Bent tubes are extensively used in the manufacturing industry to meet demands for lightweight and high performance. As one of the most significant behaviors affecting the dimensional accuracy in tube bending, springback ... -
Machine Learning Approach for Hydrogen Safety in Confined Spaces: Forecasting Pressure Peaking Phenomenon
(Master thesis, 2023)Hydrogen is the most abundant element in the universe and has gained significant attention as a clean and renewable energy source. However, hydrogen also poses significant safety risks, especially when it is stored, ... -
A Machine Learning Approach to Analyze Natural Hazards Accidents Scenarios
(Peer reviewed; Journal article, 2022)Climate change has contributed to an increasing frequency and severity of natural hazards accidents over recent years, and the increasing trend is expected to continue and escalate. Globally, demographics are changing and ... -
A machine learning approach to predict chattering alarms
(Peer reviewed; Journal article, 2020)The alarm system plays a vital role to ensure safety and reliability in the process industry. Ideally, an alarm should inform the operator about critical conditions only and provide guidance to a set of corrective actions ... -
A Machine Learning Approach to Predict the Materials' Susceptibility to Hydrogen Embrittlement
(Journal article; Peer reviewed, 2023) -
Machine Learning based Acoustic Anomaly Detection of Gas Leakages in Industrial Environments
(Master thesis, 2022)Målet med denne masteroppgaven var å utvikle en akustisk gasslekkasjedetektor basert på maskinlæring. Gasslekkasjer kan være frustrerende for industrielle anleggseiere da de fører til energiforbruk, høyere kostnader, økt ... -
Machine learning for predicting dimensions of extrusion blow molded parts: A comparison of three algorithms
(Journal article; Peer reviewed, 2023)In the perspective of feed-forward control through a manufacturing process chain, production data can be used downstream to correct subsequent processes and improve product quality. In an extrusion blow-moulding (EBM) use ... -
Machine Learning in Predictive Maintenance of Railway Infrastructures: Implementations and Challenges
(Master thesis, 2022)De nylige teknologiske fremskrittene av Industry 4.0 teknologier har skapt et skifte mot applikasjoner innen maskinlæring (ML) for prediktivt vedlikehold (PdM) og har blitt tatt i bruk av mange bransjer. Derimot finnes det ... -
Machine Learning on Complex Projects: Multivariate time series data analysis through utilization of the sequential algorithm LSTM
(Master thesis, 2021)Bruken av maskinlæring har vokst kraftig i løpet av de siste tiårene, og de mange suksesshistoriene har kastet lys over dens iboende verdi. Flere av disse suksesshistoriene stammer fra selskaper som allerede er i den ... -
Machine Learning on Complex Projects: Multivariate time series data analysis through utilization of the sequential algorithm LSTM
(Master thesis, 2021)Bruken av maskinlæring har vokst kraftig i løpet av de siste tiårene, og de mange suksesshistoriene har kastet lys over dens iboende verdi. Flere av disse suksesshistoriene stammer fra selskaper som allerede er i den ... -
Machine learning techniques for real-time collision detection in a wheeled mobile robot
(Master thesis, 2023)This thesis focuses on the application of various machine learning (ML) techniques to improve the overall dependability of a wheeled mobile robot (WMR) control during a real-time simulation. The whole system consists on a ... -
Machine Learning using High Resolution Zivid Point Clouds on a High Performance Cluster
(Master thesis, 2022)I dette masterprosjektet presenteres det metoder og arbeid som muligjør bruken av høyoppløste Zivid punktskyer i maskinlæringsbiblioteket Minkowski Engine skrevet av Chris Choy. I tillegg har det blitt laget et datasett ... -
Machine learning-based predictive maintenance: A cost-oriented model for implementation
(Journal article; Peer reviewed, 2021)Predictive Maintenance (PdM) is a condition-based maintenance strategy (CBM) that carries out maintenance action when needed, avoiding unnecessary preventive actions or failures. Machine learning (ML), in the form of ... -
Machine Learning-based Time Series Forecasting for Dynamic Reorder Points
(Master thesis, 2023)Etterspørselen etter helsetjenester i Norge øker på grunn av demografiske endringer, inkludert en voksende og aldrende befolkning. Denne økningen i etterspørsel forventes å føre til høyere helseutgifter og øke presset på ... -
Machine Learning-based Time Series Forecasting for Dynamic Reorder Points
(Master thesis, 2023)Etterspørselen etter helsetjenester i Norge øker på grunn av demografiske endringer, inkludert en voksende og aldrende befolkning. Denne økningen i etterspørsel forventes å føre til høyere helseutgifter og øke presset på ... -
Machine learning-guided design of lattice structures
(Master thesis, 2023)For decades, scientists and engineers have been striving to develop materials that are both light-weight and strong, stable, and resilient, with applications ranging from aerospace to the biomedical industry. While ... -
Machine-learning approach to design fatigue-resistant structure inspired by Pogonias cromis
(Master thesis, 2022)Atlanterhavsfisken Pagonias cromis har den høyeste bitekraften per vekt, men det nedre svelgkjevebenet som er ansvarlig for å knuse bløtdyr og skalldyr er relativt porøst sammenlignet med kortikalt bein funnet i pattedyr. ... -
MagnetGym: Resistance altering Gym Equipment with Biofeedback
(Master thesis, 2014)The Master thesis was original intended to be an attempt to make a direct competitive product to today s workout equipment using magnetic resistance. Since the resistance will be controlled digital, the option of making ... -
Maintenance analysis of a two-component load-sharing system
(Journal article, 2017)This paper presents a two-component load-sharing system. The failure rates of the two components are time dependent and load dependent. Whenever one fails, it is imperfectly repaired with a time delay during which the ...