Description
Aim:
To develop skills in undertaking an individual research project in the area of data-driven materials manufacturing. These include: critical literature survey, research design, execution and management of automated experiments, collection of data for system characterisation, data analysis and modelling, design of innovative and sustainable automated systems, presentation of results, conclusions and recommendations.Ìý
Synopsis:
This module is centered around an individual research project that is supervised by a member of academic staff working in the area of material manufacturing and/or process digitisation.ÌýÌý
Students should make a selection of three projects, ranking in order of preference, from a list of potential research projects. After the project selection deadline, each student will be allocated one of the projects based on their three preferred choices. The allocation will be done by the module coordinator and the Programme Director in consultation with supervisors based on an overall assessment of the project, the background of the student and the teaching load of the supervisors.Ìý As far as possible, projects will be allocated based on the preferred students’ choices.ÌýÌý
All topics covered in the proposed research projects will contain elements of accelerated data-driven or computational materials manufacturing including: advanced synthesis or characterisation of materials, automation, systems modelling and data-driven analysis. An emphasis will be made on the seamless integration of experimental and computational components for the design of sustainable automated systems.Ìý Industrial partners will be invited to provide topics in close collaboration with UCL academics.Ìý
Learning Outcomes:
- Execute and manage automated experiments for the synthesis and characterisation of advanced materials.Ìý
- Proficiently use the relevant engineering/mathematical software for data analysis and system modelling.Ìý
- Design innovative, sustainable manufacturing systems by integrating software and hardware elements for automated, smart experimentation.Ìý
- Critically analyse research results aided by the appropriate use of statistical data analysis and modelling techniques.ÌýÌý
- Produce accurate and defensible written and oral reports on the independent research conducted in digital materials manufacturing.Ìý
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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