Registry
Module Specifications
Archived Version 2021 - 2022
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Description The objectives of this module are to provide skills to the participants to identify experimental design and data analysis requirements for Industry 4.0/5.0. The module will equip students with planning and analysing controlled tests to evaluate processing factors. The participants will be learn statistical design of experiments, factorial design, Box-Behnken design, artificial neural networks and related models for data analysis and process optimisation. The participants will learn Big data and Machine Learning tools for data analysis in Industry 4.0 and advanced manufacturing. The participants will get training on use of data analysis tools for real-world challenges for specific application areas. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Design data analysis tools for Advanced Manufacturing. 2. Formulate experimental design and analysis methods to determine processing factors impact on response. 3. Apply and evaluate data analysis tools for discrete advanced manufacturing scenarios 4. Apply Artificial Intelligence tools for process optimisation | |||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and
Learning Activities Introduction to Data Analysis for Industry 4.0Statistical Design of Experiments; Factorial Design; Box-Behnken Response Surface Methodology; Data analysis requirements for Industry 4.0/5.0Predictive AnalysisIntroduction to predictive analysis for Industry 4.0; Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System; Machine Learning in Industry 4.0Data Analysis Case StudiesData analysis for laser based material processing techniques; Data analysis for defect detection | |||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
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