Essays about: "Learning from Failure."

Showing result 11 - 15 of 129 essays containing the words Learning from Failure..

  1. 11. A Holistic Framework for Analyzing the Reliability of IoT Devices

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

    Author : Leonardo Manca; [2023]
    Keywords : Canvas Learning Management System; Docker containers; Performance tuning Performance tuning; Internet of Things IoT ; Reliability; Failure rate; Availability; Comprehensive framework; IoT architecture; Failure modes; Reliability Block Diagram RBD ; Prestandajustering; Sakernas internet IoT ; Tillförlitlighet; Felfrekvens; Tillgänglighet; Heltäckande ramverk; IoT-arkitektur; Felfunktioner; Till-förlitlighetsblockdiagram RBD Canvas Lärplattform; Dockerbehållare; Prestandajustering;

    Abstract : In the rapidly evolving landscape of the Internet of Things (IoT), ensuring consistency and reliability becomes a top priority for a seamless user experience. In many instances, reliability is assessed through Quality of Service (QoS) metrics, sidelining traditional reliability metrics that thrive on time-dependent failure rates. READ MORE

  3. 12. Failure Inference in Drilling Bits: : Leveraging YOLO Detection for Dominant Failure Analysis

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Gnana Spandana Akumalla; [2023]
    Keywords : Computer vision; Image processing; Drill bit failure detection; CNN; YOLOv5; FNN; YOLOv8; Dataset; StyleGAN-ADA; Ethics; Sustainability; Artificial Intellegence; Tricone drill bit; Object detection.;

    Abstract : Detecting failures in tricone drill bits is crucial in the mining industry due to their potential consequences, including operational losses, safety hazards, and delays in drilling operations. Timely identification of failures allows for proactive maintenance and necessary measures to ensure smooth drilling processes and minimize associated risks. READ MORE

  4. 13. Modelling Large Protein Complexes

    University essay from Uppsala universitet/Institutionen för biologisk grundutbildning

    Author : Ho Yeung Chim; [2023]
    Keywords : Protein Modeling; Monte Carlo Tree Search; Protein Complex;

    Abstract : AlphaFold [Jumper et al., 2021, Evans et al., 2022] is a deep learning-based method that can accurately predict the structure of single- and multiple-chain proteins. However, its accuracy decreases with an increasing number of chains, and GPU memory limits the size of protein complexes that can be predicted. READ MORE

  5. 14. Feature Selection for Sensor Failure Detection in Manufacturing Environment

    University essay from Mälardalens universitet/Akademin för innovation, design och teknik

    Author : Victor Knutmejer; Hannes Elfving; [2023]
    Keywords : AI; Artificiell Intelligens; Maskininlärning; Feature Selection;

    Abstract : Automated manufacturing environments often benefit greatly from the ability to detect patterns that deviate from expected behavior. Anomaly Detection (AD) is vital in automated manufacturing to mitigate risks such as production delays, defects, and safety hazards, ensuring smooth operations and optimal productivity. READ MORE

  6. 15. Anomaly detection for prediction of failures in manufacturing environments : Machine learning based semi-supervised anomaly detection for multivariate time series to predict failures in a CNC-machine

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

    Author : Felix Boltshauser; [2023]
    Keywords : Machine learning; Anomaly Detection; DeepAnT; ROCKET; OCSVM; manufacturing; predictive maintenance; Maskin inlärning; Anomali Detektion; DeepAnT; ROCKET; OCSVM; tillverkning; prediktivt underhåll;

    Abstract : For manufacturing enterprises, the potential of collecting large amounts of data from production processes has enabled the usage of machine learning for prediction-based monitoring and maintenance of machines. Yet common maintenance strategies still include reactive handling of machine failures or schedule-based maintenance conducted by experienced personnel. READ MORE