Sökning: "Data-driven maintenance"

Visar resultat 21 - 25 av 35 uppsatser innehållade orden Data-driven maintenance.

  1. 21. Data-driven configuration recommendation for microwave networks A comparison of machine learning approaches for the recommendation of configurations and the detection of configuration anomalies

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Simon Pütz; Simon Hallborn; [2020-11-06]
    Nyckelord :Configuration; Recommendation; Machine learning; Microwave network;

    Sammanfattning : As mobile networks grow and the demand for faster connections and a better reachability increases, telecommunication providers are looking ahead to an increasing effort to maintain and plan their networks. It is therefore of interest to avoid manual maintenance and planning of mobile networks and look into possibilities to help automate such processes. LÄS MER

  3. 22. Data Driven Anomaly Control Detection for Railway Propulsion Control Systems

    Magister-uppsats, Mälardalens högskola/Inbyggda system

    Författare :Dzenita Skulj; Ajna Hodzic; [2020]
    Nyckelord :;

    Sammanfattning : The popularity of railway transportation has been on the rise over the past decades, as it has been able to provide safe, reliable, and highly available service. The main challenge within this domain is to reduce the costs of preventive maintenance and improve operational efficiency. LÄS MER

  4. 23. Digital Twin : Visualization-Assisted Corrective Maintenance

    Master-uppsats, KTH/Mekatronik

    Författare :Aamir Malik Shaik; Sidhvin Dulevale Matadha; [2020]
    Nyckelord :;

    Sammanfattning : This thesis evaluates the significance of the Digital Twin based data-driven solution, in helping corrective maintenance technicians leverage their multi-disciplinary engineering skills to solve complex mechatronic problems. Due to the complex mechatronic nature of the faults, human involvement is necessary for corrective maintenance. LÄS MER

  5. 24. Prediction of Component Breakdowns in Commercial Trucks : Using Machine Learning on Operational and Repair History Data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Einar Bremer; [2020]
    Nyckelord :Machine Learning; Data Science; Neural Networks; Recurrent Neural Networks; Random Forest; Autoencoder; Long Short Term Memory;

    Sammanfattning : The strive for cost reduction of services and repairs combined with a desire for increased vehicle reliability has led to the development of predictive maintenance programs. In maintenance plans, accurate forecasts and predictions regarding which components in a vehicle is in risk of a breakdown is bene_cial to obtain since this enables components to be predictively exchanged or serviced before they break down and cause unnecessary downtime. LÄS MER

  7. 25. Time dependent modeling of turbocharger failure using machine learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Felix Liljefors; [2020]
    Nyckelord :;

    Sammanfattning : Data-driven predictive vehicle maintenance can in principle reduce the risk of costly breakdowns, damaged cargo, and increased emissions due to faulty components. However, implementing a cost efficient predictive maintenance policy is far from trivial. LÄS MER