Module Details
| Module Code: |
PHYS8019 |
| Title: |
Statistics and Quality Methods
|
|
Long Title:
|
Statistics and Quality Management
|
| NFQ Level: |
Advanced |
| Valid From: |
Semester 1 - 2022/23 ( September 2022 ) |
| Field of Study: |
4411 - Physics
|
| Module Description: |
This module deals with methods of statistical quality measurement and quality management methods applicable to an industrial process environment.
|
| Learning Outcomes |
| On successful completion of this module the learner will be able to: |
| # |
Learning Outcome Description |
| LO1 |
Explain the relevance of statistical concepts and techniques underlying statistical quality control. |
| LO2 |
Perform correlation and regression analysis including testing for significance. |
| LO3 |
Plan, organise and use quality management techniques. |
| LO4 |
Implement a management strategy to deal with a variety of quality issues. |
| LO5 |
Perform case study applications concerning statistical quality techniques. |
| Dependencies |
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
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Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
|
| No incompatible modules listed |
Co-requisite Modules
|
| No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
|
| No requirements listed |
| Indicative Content |
|
Statistical Inference
Sampling distributions and Central Limit Theorem; one and two-sided confidence intervals for population mean and variance; hypothesis testing for population mean, variance and difference in means. Use of normal, t, F and chi-square distributions.
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Regression and Correlation
Simple linear regression and correlation, testing for significance, introduction to multiple regression
|
|
Economic Models for Quality
Traditional and Modern Economic Models.
Conformance of costs. Cost of quality.
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Problem solving techniques
Just-in-Time (JIT) Production. Kanban systems. Performance measurement. Process Management. Six Sigma methods and case studies
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Reliability
Product Life Characteristic Curve, Reliability Function, Accelerated life testing
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Module Content & Assessment
|
| Assessment Breakdown | % |
|---|
| Coursework | 50.00% |
| End of Module Formal Examination | 50.00% |
Assessments
| End of Module Formal Examination |
|
|
| Reassessment Requirement |
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
|
The University reserves the right to alter the nature and timings of assessment
Module Workload
| Workload: Full Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lecture |
Contact |
Theory |
Every Week |
4.00 |
4 |
| Independent Learning |
Non Contact |
Self-directed study of theory |
Every Week |
3.00 |
3 |
| Total Hours |
7.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
4.00 |
| Workload: Part Time |
| Workload Type |
Contact Type |
Workload Description |
Frequency |
Average Weekly Learner Workload |
Hours |
| Lecture |
Contact |
Theory |
Every Week |
3.00 |
3 |
| Lecturer-Supervised Learning (Contact) |
Contact |
Directed study |
Every Week |
1.00 |
1 |
| Independent Learning |
Non Contact |
Self-directed study of theory |
Every Week |
3.00 |
3 |
| Total Hours |
7.00 |
| Total Weekly Learner Workload |
7.00 |
| Total Weekly Contact Hours |
4.00 |
|
Module Resources
|
| Recommended Book Resources |
|---|
-
David Moore, George McCabe, Bruce Craig. (2017), Introduction to the Practice of Statistics, WH Freeman, [ISBN: 9781319013387].
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Bilal Ayyub. (2011), Probabilty, Statistics and Reliability for Engineers and Scientists, Taylor and Francis, [ISBN: 9781439809518].
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Douglas C. Montgomery. (2019), Statistical Quality Control - A Modern Introduction, 8th. John Wiley & Sons, [ISBN: 9781118322574].
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J.R. Evans, W.M.Lindsay. (2004), The Management and Control of Quality, 6th. 17, West Publishing Company, U.S.A, p.767, [ISBN: 9780324202236].
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Barrie Dale. (2003), Managing Quality, 4th. 23, Blackwell Business, U.K., p.470, [ISBN: 9780631236146].
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Tim Stapenhurst. (2005), Mastering Statistical Process Control: A handbook for performance improvement using cases, Taylor and Francis, [ISBN: 9780750665292].
| | Supplementary Book Resources |
|---|
-
James T. McClave, P.George Benson, Terry Sincich. (2017), Statistics for Business and Economics, 13th. Pearson Education Ltd, [ISBN: 9780134506593].
| | Recommended Article/Paper Resources |
|---|
-
Enrique Del Castillo , James M. Grayson
, Douglas C. Montgomery & George C.
Runger. (2007), A review of statistical process control
techniques for short run manufacturing
systems, Communications in Statistics - Theory
and Methods, 25, p.1996,
| | This module does not have any other resources |
|---|
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