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2010/11 Undergraduate Module Catalogue

MECH1220 Computers in Engineering Analysis

20 creditsClass Size: 200

Module manager: Professor Richard M Hall
Email: R.M.Hall@leeds.ac.uk

Taught: Semesters 1 & 2 (Sep to Jun) View Timetable

Year running 2010/11

Module replaces

MECH1560 Computers in Engineering Analysis 1, MECH2550 Computers in Engineering Analysis 2

This module is not approved as an Elective

Objectives

On completion of this module, students should be able to:
1. Appreciate the importance of computers and computational instruments to the development of engineering science in analytical and communication roles.
2. Understand the concepts of simple programming including logical structures, loops and subroutines and be able to develop simple programmes to solve engineering science problems.
3. Plan experiments that are statistically valid, including evaluating different designs and sample size analysis.
4. Display, analyse and present a range of experimental data using both graphical and inferential statistical techniques.
5. Process data from a range of sources and display appropriate output.
6. Understand the practicalities of data acquisition.
7. Apply quantitative methods and computer software to solve engineering problems.
8. Ability to work with technical uncertainty.

Skills outcomes
Written communication, analysis, criticality and argument; problem solving; TCT skills


Syllabus

Introduction to IT:
This will be delivered by the ISS during the first week of term and will cover such issues as MS Office, using email and accessing the internet

Matlab:
Students should be able to use Matlab to:
1. Understand generic concepts of programming including:
- input and output / mathematical syntax / conditional statements / for and while loops / subroutines.
2. Use Matlab to display 2D and 3D plots.
3. Manipulate matrices, vectors.
4. Develop simple engineering programs.
5. Statistical Software Package.

The students should demonstrate an understanding in the following areas:
a. Relate to the idea of measurement and variability, relate to industrial process engineering
b. Uncertainty in Engineering, precision, accuracy and trueness. Error propagation.
c. Experimental design
d. Perform exploratory data
e. Explore differences between sets of data using inferential statistics
f. Deduce the relationships between data using regression and correlation
g. Statistical Process Control, simple charts for variables - X-bar and R charts

Labview:
Students should be able to use Labview to:
1. Develop appropriate graphical interfaces for end-users.
2. Be able to wire diagrams using appropriate functions for performing mathematical operations, use conditional statements and loops and subroutines.
3. Process, display and output experimental data.
4. Develop simple engineering programmes.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Lecture82.0016.00
Lecture141.0014.00
Practical162.0032.00
Private study hours138.00
Total Contact hours62.00
Total hours (100hr per 10 credits)200.00

Private study

Planning assignments 20 hour
Solving assignments 35 hour
Completing Study workbooks 50 hour
Reading material for lecture preparation 18 hour
Preparation for class test 15 hour

Opportunities for Formative Feedback

The module is assessed through coursework - students will be given feedback on all summative assessments. In addition, students will complete work books and computer programmes on which formative feedback will be given.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
Computer ExerciseMatlab exercise40.00
Computer ExerciseStatistics exercise30.00
Computer ExerciseLabview exercise30.00
Total percentage (Assessment Coursework)100.00

Students wishing to re-sit this module will be required to prepare a portfolio of work over the summer that includes the work books and development of computer programmes.

Reading list

The reading list is available from the Library website

Last updated: 13/04/2011

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