| Course label : | From Generative Design to manufacturing |
|---|---|
| Teaching departement : | MSO / Structures, Mechanisms and Construction |
| Teaching manager : | Mister DENIS LE PICART |
| Education language : | French |
| Potential ects : | 7 |
| Results grid : | |
| Code and label (hp) : | G2_S7_EI_GDM - From Generative Design to manu |
Education team
Teachers : Mister DENIS LE PICART / Madam AMINA TANDJAOUI / Mister Frédéric Gillot / Mister LAURENT PATROUIX / Mister OLIVIER MAYEUR
External contributors (business, research, secondary education): various temporary teachers
Summary
Additive manufacturing, unlike traditional machining techniques, makes it possible to produce parts with complex geometries whose total weight can be optimized using a numerical method called "generative design". This method also allows to maximize the mechanical strength of the created part. Generative design is in fact a sub-field of numerical design which allows to find, thanks to mathematical formulas, the optimal material distribution in a given volume subjected to more or less important mechanical constraints. Generative design consists of "removing" the material where the forces do not pass through, using dedicated software, enabling Eco-Design of mechanical parts. The study of materials as well as recent means of manufacturing (rapid prototyping) are inseparable from topological optimization because they are strong constraints in the use of generative design tools. Indeed, materials selection, process selection and the geometry form a triptych that is essential to respect the requirements of a specification and to achieve the expected mechanical performance. Within today's context of energy efficiency and materials economy, those approaches are off special importance but lack maturity and broad dissemination. For this task, a life cycle assessment analysis (LCA) will drive the achievement of an eco-friendly mechanical part, thus taking into account all the life cycle stages. The objective of this course is to make the student aware of these problems and thus justify the interest of optimization tools.
Educational goals
The targeted competencies of the reference framework are as follows: The “Centralien” engineer creates value through scientific and technical innovation. The “Centralien” engineers master the complexity of the systems and problems they encounter.
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: Individual evaluation: multiple choice questionnaires and/or practical work reports.
Group evaluation: defending results of the mini project
Attendance and investment will be an essential component of the evaluation.
Online resources
Generative design software provided. Online resources of the software. Lessons, exercises et and self-evaluations on Moodle.
Pedagogy
The acquisition of knowledge will follow a red thread that will allow the student to assimilate all the different steps of the methodology. Theoretical results will be confronted with mechanical tests in order to verify their adequacy. Following this knowledge acquisition, students will have to solve an industrial problem in project mode.
Sequencing / learning methods
| Number of hours - Lectures : | 0 |
|---|---|
| Number of hours - Tutorial : | 62 |
| Number of hours - Practical work : | 16 |
| Number of hours - Seminar : | 16 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 48 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
Basis in CAD design. Basis in material behaviour.
Maximum number of registrants
34
Remarks
Keywords: Generative design ; Eco-design ; Mass gain ; Materials ; Manufacturing ; Rapid prototyping ; Aerospace ; Automotive ; Biomedical Engineering