35355 Quality Control
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particular session, location and mode of offering is the authoritative source
of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
Subject handbook information prior to 2018 is available in the Archives.
Credit points: 6 cp
Result type: Grade and marks
Requisite(s): 35353c Regression Analysis OR 35252 Mathematical Statistics
The lower case 'c' after the subject code indicates that the subject is a corequisite. See definitions for details.
These requisites may not apply to students in certain courses. See access conditions.
Description
This subject shows how to use statistical methods to improve the quality of manufactured goods and services. The topics covered include control charts, acceptance sampling plans, process capability and reliability measures. Applications to health and health-related quality of life are also discussed.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | manage their own work, including the importance of time management and the need to accept responsibility for their own decisions; |
|---|---|
| 2. | identify the underlying problem in an unfamiliar situation and the appropriate technique(s) needed to solve the problem, and to apply the techniques to solve the problem; |
| 3. | produce a written solution to a problem using appropriate professional language and presentation; |
| 4. | locate, critically assess and apply information gained from academic publications and the internet; |
| 5. | locate and apply appropriate information technology tools to unfamiliar problems. |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of following course intended learning outcomes:
- An understanding of the nature, practice and application of the chosen science discipline.Disciplinary knowledge and its appropriate application (1.0)
Contribution to the development of graduate attributes
This subject contributes to the development of the following graduate attributes:
1. Disciplinary knowledge and its appropriate application
The lectures, weekly laboratories and assignment impart skills necessary in a number of mathematical disciplines and demonstrate how to apply these skills to a variety of problems.
2. An Inquiry-oriented approach
The weekly laboratories and assignment present a number of problems where the student has to decide which of the techniques covered in lectures is the most appropriate to deal with the problem. Critical thinking is essential.
3. Professional skills and their appropriate application
This subject helps students learn to manage their own work and to accept responsibility for their own learning. Examples and problems are drawn from typical real life situations. The subject also shows students how to find and assess information from other sources, both academic and computational, and the assignment provides a chance for students to demonstrate their mastery of this aspect of the subject. Statisticians who work in industry are often required to monitor quality and this subject imparts the skills necessary to do so.
4. Communication skills
Presentation of written solutions to problems using appropriate professional language is also emphasised by the assignment.
Teaching and learning strategies
Weekly on campus: 2 hr lecture, 2 hr laboratory, supported by at least four hours per week of individual or group study.
Content (topics)
This subject covers topics from introduction to total quality management; control charts; process capability; acceptance sampling; tolerance analysis; reliability and rates of failure; life testing; discussion of application of principles to health-related quality of life (HRQOL).
Assessment
Assessment task 1: Weekly Labs
| Objective(s): | This assessment task contributes to the development of course intended learning outcome(s): 1.0 |
|---|---|
| Weight: | 20% |
| Criteria: | There are ten computer labs to be handed in weekly. The best 8 will be used for 20% of the marks in the subject. |
Assessment task 2: Assignment
| Objective(s): | This assessment task contributes to the development of course intended learning outcome(s): 1.0 |
|---|---|
| Weight: | 20% |
Assessment task 3: Examination - open book
| Objective(s): | This assessment task contributes to the development of course intended learning outcome(s): 1.0 |
|---|---|
| Weight: | 60% |
| Length: | 3 hours plus ten minutes reading time |
Minimum requirements
In order to pass this subject, a student must achieve a final result of 50% or more and must receive at least 40% of the marks available for the final examination. If they do not, they will be awarded an X (fail) grade regardless of the total marks obtained in the subject.
Required texts
There is no set text for this subject.
The most useful reference is Montgomery, D.C., Introduction to Statistical Quality Control, 5th Edition, John Wiley, 2005.Recommended texts
References
Grant, E.L. and Leavenworth, R.S., Statistical Quality Control, 7th Edition, McGraw-Hill, 1996.
Hubbard, M.R., Statistical Quality for the Food Industry, 2nd Edition, Chapman and Hall, 1996.
