Essays about: "Prediktivt underhåll"

Showing result 6 - 10 of 28 essays containing the words Prediktivt underhåll.

1. 6. Predictive Maintenance as a Tool for Servitization : The case of a value-added reseller in the construction equipment industry

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Max Kihlborg; Adam Lilja; [2022]
   Keywords : Servitization; Productivity-as-a-Service; Predictive maintenance; Industrial maintenance; Machine learning; Value-added reseller; Construction equipment industry; Tjänstefiering; Prediktivt underhåll; Industriellt underhåll; Maskininlärning; Värdeskapande återförsäljare; Anläggningmaskinsbranschen;

   Abstract : The construction equipment industry has been slow to increase its level of servitization, compared to other related sectors such as the car and flight industries. The fundamental problem is the endless variants of machines and business settings that their customers operate in. READ MORE

3. 7. Predictive Maintenance of Induction Motors using Deep Learning : Anomaly Detection using an Autoencoder Neural Network and Fault Classification using a Convolutional Neural Network

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Diego Andres Moreno Salinas; [2022]
   Keywords : Predictive maintenance; Fault Diagnosis; Anomaly Detection; Deep Learning; Machine Learning; Induction Motors; Prediktivt underhåll; feldiagnostik; upptäckt av avvikelser; djup inlärning; maskininlärning; induktionsmotorer;

   Abstract : With the fast evolution of the Industry 4.0, the increased use of sensors and the rapid development of the Internet of Things (IoT), and the adoption of artificial intelligence methods, smart factories can automate their processes to vastly improve their efficiency and production quality. READ MORE

4. 8. Predictive Maintenance of Construction Equipment using Log Data : A Data- centric Approach

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Bazil Muzaffar Kotriwala; [2021]
   Keywords : Predictive Maintenance; Construction Equipment; Event Log; Sensor Log; Machine Learning; Imbalanced Data; Prediktivt underhåll; byggutrustning; händelselogg; sensorlogg; maskininlärning; obalanserade data;

   Abstract : Construction equipment manufacturers want to reduce the downtime of their equipment by moving from the typical reactive maintenance to a predictive maintenance approach. They would like to define a method to predict the failure of the construction equipment ahead of time by leveraging the real- world data that is being logged by their vehicles. READ MORE

5. 9. Using Machine Learning for Predictive Maintenance in Modern Ground-Based Radar Systems

   University essay from KTH/Matematisk statistik

   Author : Dina Faraj; [2021]
   Keywords : Predictive Maintenance; Machine learning; Isolation forest; K-means clustering; Logistic regression; Radar systems.; Prediktivt underhåll; Maskininlärning; Isolation forest; K-means klustring; Logistisk regression; Radarsystem.;

   Abstract : Military systems are often part of critical operations where unplanned downtime should be avoided at all costs. Using modern machine learning algorithms it could be possible to predict when, where, and at what time a fault is likely to occur which enables time for ordering replacement parts and scheduling maintenance. READ MORE

6. 10. A deep learning based anomaly detection pipeline for battery fleets

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Nabakumar Singh Khongbantabam; [2021]
   Keywords : Forklift batteries; Battery sensors; Data pipeline; Predictive maintenance; Anomaly detection; Deep learning; Battery failure prediction; Time-series; Variational autoencoder; Long short-term memory; LSTM; Gated recurrent unit; GRU; Isolation nearest neighbor; iNNE; Isolation forest; iForest; kth nearest neighbor; kNN.; Gaffeltruckbatterier; Batterisensorer; Datapipeline; Prediktivt underhåll; Avvikelsedetektering; Deep learning; Batterifelsprediktion; Tidsserier; Variationsautokodare; Långt korttidsminne; LSTM; Gated recurrent unit; GRU; Isolation närmaste granne; iNNE; Isolation skog; iForest; kth närmaste granne; kNN.;

   Abstract : This thesis proposes a deep learning anomaly detection pipeline to detect possible anomalies during the operation of a fleet of batteries and presents its development and evaluation. The pipeline employs sensors that connect to each battery in the fleet to remotely collect real-time measurements of their operating characteristics, such as voltage, current, and temperature. READ MORE