Subject Description Form
Subject Code
ISE442
Subject Title
Design of Experiments
Credit Value
3
Level
4
Pre-requisite/Corequisite/Exclusion
ISE206 Quantitative Methods or AMA1104 Introductory Probability or
Equivalent
Objectives
This subject provides students with the knowledge to
Intended Learning
Outcomes
Subject Synopsis/
Indicative Syllabus
1.
use statistics in experimentation;
2.
understand the important role of experimentation in new product design,
manufacturing process development, and process improvement;
3.
analyze the results from such investigations to obtain conclusions;
4.
become familiar methodologies that can be used in conjunction with
experimental designs for robustness and optimization.
Upon completion of the subject, students will be able to
a.
plan, design, and conduct experimental investigations efficiently and
effectively;
b.
understand strategy in planning and conducting experiments;
c.
choose an appropriate experiment to evaluate a new product design or
process improvement through experimentation strategy, data analysis, and
interpretation of experimental results.
1.
Strategy of Experimentation
Brief history of statistical design, Design concept of Six Sigma, Statistical
principles in experimental design, Guidelines for designing experiments
2.
Design and Analysis with Factorial Structure
Analysis of variance, Factorial experiments in completely randomized
designs, Fractional factorial orthogonal arrays
3.
Design and Analysis with Random Effects
Randomized block designs, Variance-component estimation, Latin-square
and crossover designs, Nested designs
4.
Special designs for product/process improvement
Response surface methodology, Evolutionary operations, Taguchi’s
18.3.2014
robust product design approach, Parameter design, Customer tolerance,
Types of quality loss functions; Tolerance design
Teaching/Learning
Methodology
A mixture of lectures and tutorials is used to achieve the objectives of this
subject. Students also have the opportunity to use the computer package to
perform data analysis.
The lectures are aimed at providing students with the integrated knowledge
required to hone expertise and master procedures necessary to perform,
evaluate, and arrive at decisions using designed experiments.
The tutorials are aimed at enhancing design and analysis techniques. Tutorials
and case studies are based on real-world applications of experimental design
and are drawn from a number of different fields of engineering.
The software packages are introduced in lectures and are used in tutorials and
cases studies to handle the analysis of experiments.
Assessment Methods
in Alignment with
Intended Learning
Outcomes
Specific assessment
methods/tasks
%
weighting
Intended subject learning outcomes to
be assessed
a
b
c
1.Examination
60%



2. Assignments
30%



3.Test
10%
Total
100%

The continuous assessment comprises of two components: a test (10%) and
three tutorials (30%). The test is aimed at assessing the knowledge gained by
the students. The tutorials are designed to assess students’ ability to design
experiments and analyze results of the experiment.
The examination, which covers all the intended learning outcomes, is used to
assess the knowledge and skills acquired by the students.
Student Study
Effort Expected
Class contact:

Lecture
2 hours/week for 13 weeks
26 Hrs.

Tutorial & Test
1 hour/week for 13 weeks
13 Hrs.
Other student study effort:

Assignments
26 Hrs.

Self Study
52 Hrs.
Total student study effort
18.3.2014
117 Hrs.
Reading List and
References
18.3.2014
1.
C.F. Jeff Wu & Michael Hamada 2009, Experiments-Panning, Analysis,
and Parameter Design Optimization, 2nd edn, John Wiley & Sons. Inc.
2.
D.C. Montgomery 2013, Design and Analysis of Experiments, 7th edn,
John Wiley & Sons. Inc.
3.
R. L. Mason, R. F. Gunst & J.L. Hess 2003, Statistical Design and
Analysis of Experiments with Applications to Engineering and Science,
2nd edn, John Wiley & Sons. Inc.