Course syllabus for Engineering design and optimization

The course syllabus contains changes
See changes

Course syllabus adopted 2019-02-18 by Head of Programme (or corresponding).

Overview

  • Swedish nameKonstruktionsoptimering
  • CodePPU191
  • Credits7.5 Credits
  • OwnerMPPDE
  • Education cycleSecond-cycle
  • Main field of studyAutomation and Mechatronics Engineering, Mechanical Engineering, Industrial Design Engineering
  • DepartmentINDUSTRIAL AND MATERIALS SCIENCE
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language English
  • Application code 33118
  • Maximum participants60
  • Block schedule
  • Open for exchange studentsNo

Credit distribution

0117 Written and oral assignments 3 c
Grading: UG		3 c
0217 Examination 4.5 c
Grading: TH		4.5 c
  • 28 Okt 2020 am J
  • 07 Jan 2021 am J
  • 25 Aug 2021 am J

In programmes

Examiner

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Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

- CAD
- Machine Elements, Applied Mechanics or similar
- FEM
- Programming (Matlab)
- Material science
- Manufacturing technology
- Mechanics
- Solid mechanics
- Mathematics equivalent to 30 credits, including multivariate analysis and numerical analysis

Aim

The course aims at integrating traditional design methodologies with concepts and techniques of modern optimization theory and practice. Furthermore the course aims to:
- Demonstrate different tools and methods for optimization of mechanical products and structures
- Design for improvement of components in products and systems
- Demonstrate the iterative nature of the development chain including modelling-analysis-test
- Use and familiarize students with modern CAE tools
- Incorporate material selection as a part of the product development process

Learning outcomes (after completion of the course the student should be able to)

  • Master the complete development chain including modelling-analyses-test-evaluation
  • Identify areas for improvement in a new or an existing product design
  • Identify and choose appropriate material alternatives for a product
  • Apply previously-learned design methods and tools to practical problems
  • Create appropriate simulation models of the design problem
  • Use Computer Aided Engineering (CAE) tools to design and simulate product performance
  • Apply previous knowledge in mathematics and mechanics to formulate and solve optimization problems.
  • Formulate design optimization problems based on project or product requirements
  • Apply numerical optimization techniques and computer tools to solve optimization problems
  • Interpret optimization results for design decision making (e.g., material selection, geometry, manufacturing, production)
  • Create CAE drawings for use with three-dimensional printing tools
  • Iterate on design solutions to continually improve a product's design and performance
  • Communicate design solutions, including rationales for a given choice, advantages, and disadvantages over alternatives

    • Content

  • Formulate and solve optimization problems
  • Selection of optimization algorithms and tools
  • Identification and classification of design problems and failures
  • Identification of required material properties and selection of materials for design solutions (e.g., using CES Selector)
  • Conversion of requirements and specifications into design objectives and constraints 
  • Modelling-analysis-test methods linking calculations (e.g., MATLAB/Simulink, CAD/CAE (e.g., CATIA, ANSYS,COMSOL), and rapid prototyping (e.g., 3D printing)

    • Organisation

    Lectures, workshops and three assignments on different topics.

    Literature

    Principles of Optimal Design: Modeling and Computation  

    Selected articles

    Examination including compulsory elements

    Written exam (Grade 5, 4, 3, Fail)
    Midterm exam (bonus points for the exam)
    Three (3) approved assignments (Pass/Fail)
    Attended compulsory guest lectures.

    The course syllabus contains changes

    • Changes to examination:
      • 2020-09-30: Grade raising No longer grade raising by GRULG