Search for dissertations about: "industry 4.0 and performance"

Showing result 1 - 5 of 29 swedish dissertations containing the words industry 4.0 and performance.

  2. 1. Sheet metal forming in the era of industry 4.0 : using data and simulations to improve understanding, predictability and performance

    Author : Sravan Tatipala; Johan Wall; Christian Johansson; Tobias Larsson; Mehdi Tarkian; Blekinge Tekniska Högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Modelling; Simulation; Industry 4.0; Sheet Metal Forming; Process Monitoring; Process Control; Automation; Finite Element Analysis; Smart Manufacturing; Mechanical Engineering;

    Abstract : A major issue within automotive Sheet Metal Forming (SMF) concerns ensuring desired output product quality and consistent process performance. This is fueled by complex physical phenomena, process fluctuations and complicated parameter correlations governing the dynamics of the production processes. READ MORE

  4. 2. Sensors and Algorithms in Industry 4.0 : Security and Health Preservation Applications

    Author : Dawid Gradolewski; Wlodek Kulesza; Sven Johansson; Alberto Rodriguez-Martinez; Blekinge Tekniska Högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Acoustic Sensor; Artificial Intelligence; Autonomisation; Classification; Detection; Feature Extraction; Health Preservation; Identification; Internet of Things; Machine Learning; Multi-Sensor System; Safety System; Vision System; Systemteknik; Systems Engineering;

    Abstract : Globalisation and technological digitisation have triggered an Industry 4.0. revolution.  The core of this revolution is autonomisation of complex processes, which require expert knowledge. READ MORE

  5. 3. Smart Maintenance - maintenance in digitalised manufacturing

    Author : Jon Bokrantz; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; digitalisation; production system; maintenance; manufacturing; industry 4.0;

    Abstract : What does digitalised manufacturing entail for maintenance organizations? This is a pressing question for practitioners and scholars within industrial maintenance management who are trying to figure out the best ways for responding to the rapid advancement of digital technologies. As technology moves faster than ever before, this is an urgent matter of uttermost importance. READ MORE

  6. 4. Applied Machine Learning in Steel Process Engineering : Using Supervised Machine Learning Models to Predict the Electrical Energy Consumption of Electric Arc Furnaces

    Author : Leo Carlsson; Pär Jönsson; Peter Samuelsson; Mikael Vejdemo-Johansson; Henrik Saxen; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Electric Arc Furnace; Electrical Energy Consumption; Statistical Modelling; Machine Learning; Interpretable Machine Learning; Predictive Modelling; Industry 4.0; Ljusbågsugn; Elenergiförbrukning; Statistisk Modellering; Maskininlärning; Tolkningsbar Maskininlärning; Prediktiv Modellering; Industri 4.0; Teknisk materialvetenskap; Materials Science and Engineering; Metallurgical process science; Metallurgisk processvetenskap;

    Abstract : The steel industry is in constant need of improving its production processes. This is partly due to increasing competition and partly due to environmental concerns. One commonly used method for improving these processes is through the act of modeling. READ MORE

  7. 5. Optimization Framework for Crushing Plants

    Author : Kanishk Bhadani; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Minerals Processing; Industry 4.0; Multi-Objective Optimization MOO ; Screening; Process Optimization; Process Improvement; Modelling; Comminution; Key Performance Indicators KPIs ; Classification; Multi-Disciplinary Optimization MDO ; Crushing; Dynamic Simulations;

    Abstract : Optimization is a decision-making process to utilize available resources efficiently. The use of optimization methods provide opportunities for continuous improvements, increasing competitiveness, trade-off analysis and as a support tool for the decision-making process in industrial applications. READ MORE