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Showing result 1 - 5 of 129 swedish dissertations matching the above criteria.

2. 1. KPI framework for maintenance management through eMaintenance : Development, implementation, assessment, and optimization

   Author : Esi Saari; Janet Lin; Ramin Karim; Phillip Tretten; David Baglee; Luleå tekniska universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Drift och underhållsteknik; Operation and Maintenance;

   Abstract : Performance measurement is critical if any organization wants to thrive. The motivation for the thesis originated from the project “Key Performance Indicators (KPI) for control and management of maintenance process through eMaintenance (in Swedish: Nyckeltal för styrning och uppföljning av underhållsverksamhet m h a eUnderhåll)”, initiated and financed by a mining company in Sweden. READ MORE

4. 2. Two-Level Multi-Objective Genetic Algorithm for Risk-Based Life Cycle Cost Analysis

   Author : Yamur K. Al-Douri; Uday Kumar; Jan Lundberg; Hussan Hamodi; Ahmed Al-Dubai; Luleå tekniska universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Artificial intelligence AI ; Life cycle cost LCC ; Machine learning ML ; Multi-objective genetic algorithm MOGA ; Risk-based life cycle cost LCC ; Tunnel fans; Two-level system; Operation and Maintenance Engineering; Drift och underhållsteknik;

   Abstract : Artificial intelligence (AI) is one of the fields in science and engineering and encompasses a wide variety of subfields, ranging from general areas (learning and perception) to specific topics, such as mathematical theorems. AI and, specifically, multi-objective genetic algorithms (MOGAs) for risk-based life cycle cost (LCC) analysis should be performed to estimate the optimal replacement time of tunnel fan systems, with a view towards reducing the ownership cost and the risk cost and increasing company profitability from an economic point of view. READ MORE

5. 3. Prognostics and Health Management of Engineering Systems for Operation and Maintenance Optimisation

   Author : Madhav Mishra; Matti Rantatalo; Kai Goebel; Kalevi Huhtala; Luleå tekniska universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Prognostics and Health Management PHM ; Diagnostics; Prognostics; Bayesian; Hierarchical; L10; Prediction; Bearing; Li-ion battery; RUL; Particle filter; Model-based; Data-driven; Algorithms; Railway track geometry; Operation and Maintenance Engineering; Drift och underhållsteknik;

   Abstract : Prognostics and health management (PHM) is an engineering discipline that aims to maintain system behaviour and function and ensure mission success, safety and effectiveness. Prognostics is defined as the estimation of remaining useful life. READ MORE

6. 4. Automation of Load Haul Dump machines : comparative performance analysis and maintenance modeling

   Author : Anna Gustafson; Sunniva Haugen; Luleå tekniska universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Drift och underhållsteknik; Operation and Maintenance Engineering;

   Abstract : The Load Haul Dump (LHD) machine and its operating environment create a complex system. Mine productivity depends on the operation of the LHDs and on the mining environment, including fragmentation, size of boulders, navigation techniques etc. Traditional navigation techniques require a lot of infrastructure to accommodate automatic operation. READ MORE

7. 5. Big Data Analytics for Fault Detection and its Application in Maintenance

   Author : Liangwei Zhang; Ramin Karim; Janet Lin; Benoît Iung; Luleå tekniska universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Big Data analytics; eMaintenance; fault detection; high-dimensional data; stream data mining; nonlinear data; Drift och underhållsteknik; Operation and Maintenance;

   Abstract : Big Data analytics has attracted intense interest recently for its attempt to extract information, knowledge and wisdom from Big Data. In industry, with the development of sensor technology and Information & Communication Technologies (ICT), reams of high-dimensional, streaming, and nonlinear data are being collected and curated to support decision-making. READ MORE