QLTY08016 2013 Experimental Design
Full Title
Experimental Design
Transcript Title
Experimental Design
Code
QLTY08016
Attendance
N/A %
Subject Area
QLTY - Quality
Department
MENG - Mech. and Electronic Eng.
Level
08 - NFQ Level 8
Credit
05 - 05 Credits
Duration
Semester
Fee
€
Start Term
2013 - Full Academic Year 2013-14
End Term
2019 - Full Academic Year 2019-20
Author(s)
JOHN DONOVAN
Programme Membership
SG_EQLTY_K08 201300 Bachelor of Science (Honours) in Quality Management and Tech
SG_EADVA_E08 201500 Level 8 Certificate in Advanced Lean Sigma Quality
SG_ELEAN_E08 201300 Level 8 Certificate in Engineering in Lean Sigma Quality
SG_ELEAN_E08 201400 Level 8 Certificate in Engineering in Lean Sigma Quality
SG_EPOLY_K08 201800 Bachelor of Engineering (Honours) in Engineering in Polymer Processing
Description
This module will provide the student with the tools necessary to plan, conduct and analyse experiments. The analytical interpretation of these results will allow the student to optimise products and processes.
Learning Outcomes
On completion of this module the learner will/should be able to;
1.
Calculate correlation coefficient and conduct a test of significance.
2.
Solve simple linear regression and curvilinear regression problems and make predictions.
3.
Conduct one way and two-way ANOVA including the analysis of residuals.
4.
Conduct and factorial experiments and analyse the resulting data.
5.
Apply Taguchi methods involving calculation of loss function and signal-to-noise ratios.
6.
Describe when and how to apply the appropriate experimental techniques and models
7.
Use a statistical package to analyse and interpret experimental data.
Teaching and Learning Strategies
Real world examples, case studies and published peer reviewed papers will be utilised, where possible.
Module Assessment Strategies
Students will plan, conduct, analyse and interpret their own non-industrial experiment using Minitab software.
Final 2.5 hour written exam.
Module Dependencies
Prerequisites
MATH08005 201300 Statistics
Indicative Syllabus
- Correlation : Meaning of correlation coefficient (r).Hypothesis test on correlation coefficient. Spearman's Rank Order correlation.
- Regression : Simple linear regression. Making predictions. Confidence intervals and hypothesis testing. The coefficient of Determination. Curvilinear regression and use of transformations. Computation of Multiple Regression via computer.
- Analysis of Variance : One and two way ANOVA. Comparison of treatment means - Least Significant difference. Analysis of Residuals. Randomised block designs.
- Factorial designs : Planning and conducting industrial experiments, blocking, replication, randomisation. Analysis of variance. Calculation of main and interaction effects. Development response graphs. Development of a model which relates response to the factors. Model adequacy checking. Dealing with single replicates of a design. Construction of blocks in a design.
- fractional factorial designs : Their construction and analysis. Design resolution, confounding patterns and generating relations. Fold-over designs.
- Taguchi methods: The philosophy. Loss function. Approach to parameter and tolerance design. Inner and outer Arrays. Linear graphs, Data analysis using Taguchi methods. Comparison of Taguchi experimental designs and data analysis methods with western methods.
- Brief introduction to Random vs. Fixed effects models and Crossed vs. Nested designs.
Indicative Projects
- Optimisation of a catapult
- Optimise the cooking of Rice
- Optimisation of a paper airplane
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
20 %
End of Semester / Year Formal Exam
80 %
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Group Project Students will plan, design, conduct, analyse and interpret their own non-industrial experiment | Coursework Assessment | UNKNOWN | 20 % | OnGoing | 1,2,3,4,5,6,7 |
End of Semester / Year Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Final Exam one written paper | Final Exam | UNKNOWN | 80 % | End of Term | 1,2,3,4,5,6,7 |
Full Time Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Not Specified | Lecture | 2 | Weekly | 2.00 |
| Tutorial | Not Specified | Tutorial | 2 | Weekly | 2.00 |
| Independent Learning | UNKNOWN | Independent Learning | 4 | Weekly | 4.00 |
Total Full Time Average Weekly Learner Contact Time 4.00 Hours
Part Time Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Distance Learning Suite | Theory | 2 | Weekly | 2.00 |
| Tutorial | Not Specified | Tutorial | 2 | Weekly | 2.00 |
| Independent Learning | UNKNOWN | Independent Learning | 4 | Weekly | 4.00 |
Total Part Time Average Weekly Learner Contact Time 4.00 Hours
Module Resources
Non ISBN Literary Resources
|
Authors |
Title |
Publishers |
Year |
|
Montgomery, Douglas |
Design and Analysis of Experiments, |
John Wiley & Sons |
2013 |
|
Box, Hunter & Hunter, |
Statistics for Experimenters |
John Wiley & Sons |
2005 |
|
Turner. Charles and Hicks. Kenneth |
Fundamental Concepts in the Design of Experiments |
Oxford University Press. |
1999 |
|
Ross, Phillip |
Taguchi Techniques for Quality Engineering |
McGraw-Hill |
1995 |
|
Roy, Ranjit |
Design of Experiments Using the Taguchi Approach : 16 Steps to Product and Process Improvement,. |
John Wiley & Sons |
2001 |
Other Resources
None
Additional Information
None