| Aims: |
To present various standard acceptance sampling plans,
quality control methods for monitoring the quality of manufactured items, time series
methods for the modelling of data and forecasting using these models. |
| Intended
Learning Outcomes: |
On completion of the course students will be able to:
- Design single and double sampling plans with optimum properties;
- Construct quality control limits and assess their merits;
- Fit simple time series models to real data and calculate forecasts and their standard
errors.
|
| Pre-requisites: |
114, 257 (Statistical Theory and Methods). |
| Dependent Courses: |
None. |
| Course Description: |
Modern quality control has evolved from a purely
statistically based sampling procedure to a toolkit of techniques widely used under
quality assurance (QA). Statistical Process Control (SPC) and Total Quality Management
(TQM) are largely concerned with trouble shooting and early detection of abnormal process
operation. The modern quality specialist requires a broad knowledge of the operation of
such procedures. Forecasting is an important part of general management; and time series
models are often used for forecasting. A brief description of the methods and techniques
will be given. |
| Teaching Mode: |
2 Lectures per week |
|
1 Tutorial per week |
| Private
Study: |
5 hours per week |
| Recommended Texts: |
Jerry Banks, Principles of Quality Control, 1989, Wiley. |
|
C Chatfield, The Analysis of Time Series: Theory and
Practice, 1996, Chapman-Hall. |
|
D C Montgomery, Statistical Quality Control, (2nd edition),
1991, Wiley. |
|
G B Wetherill, Sampling Inspection and Quality Control, 1969,
Methuen. |
|
G B Wetherill, D W Brown, Statistical Process Control -
Theory and Practice, 1991, Chapman and Hall. |
| Assessment Methods: |
Coursework: 20% |
|
Coursework Mode: Tests in Weeks 8 and 11 |
|
Examination: 80% |
|
Examination is of 2 hours duration at the end of the First
Semester. |