Reference no: EM133124194

KB7043 Multidisciplinary Design & Engineering Optimisation

Learning Outcome 1: A systematic understanding of knowledge which is at the forefront of modern engineering design and optimisation
Learning Outcome 2: Knowledge of conducting essential calculations for reliability driven design and design under uncertainties
Intellectual / Professional skills & abilities:
Learning Outcome 3: Ability to plan design optimisation processes for complex engineering problems and to formulate their corresponding optimisation problem and identifying the best applicable search method
Learning Outcome 4: Skill of using optimisation methods to find the optimum solution for a given optimisation problem and develop critiques of the methods and the optimality of the solution
Learning Outcome 5: Increase proficiency in applying new design and optimisation techniques towards designing products and processes with improved performance and less environmental impact.

Coursework Overview

Tower cranes are a common machine at any major construction site. The construction workers employ the tower crane to lift heavy and bulky stuff, such as steel, concrete, large tools and a wide variety of other building materials.

Design an optimised tower crane jib to lift required stuffs. Make use of ANSYS Workbench, ANSYS Mechanical and ANSYS DesignXplorer to conduct the study. Investigate the effect of uncertainty in the design parameters on the performance of the tower crane using the Six Sigma Analysis from the ANSYS DesignXplorer toolbox.

Each student will have a unique set of data provided to them by the module tutor. This unique data set includes:
• the materials parameters of the tower crane jib and cables supporting the jib
• the maximum reach of the jib
• maximum load of the tower crane

Coursework Tasks to be Completed by Students
The following tasks are to be completed on the chosen design problem:

• Provide a description of the design. Include a drawing/sketch/model of the tower crane jib clearly showing the parameters.
• Discuss the model setup in ANSYS Workbench indicating the diffirent steps required to perform the analysis. Explain how the response surface is created focusing on the theory of generating reduced order meta-models.
• Present and interpret the results obtained from the response surface.
• Present and interpret the results obtained from the response surface optimisation. Clearly indicate the implications for the design and the optimal values of the selected parameters
• Investigate the range of performance as the design and operating parameters vary by performing a Six Sigma Analysis in ANSYS Workbench.
• Conclude the report with the major findings.

Expected Size of Submission
The main body of the report shall be no more than 15 A4 pages from the introduction to conclusion with single line spacing, 11pt Calibri (Body) font.

Referencing Style

Attachment:- Multidisciplinary Design.rar