| Course Unit Code | 639-3005/04 |
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| Number of ECTS Credits Allocated | 6 ECTS credits |
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| Type of Course Unit * | Optional |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | |
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| Semester when the Course Unit is delivered | Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | English |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| NOS35 | prof. Ing. Darja Noskievičová, CSc. |
| Summary |
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This subject aims to make deeper students´ theoretical basis and practical
experience with statistical methods for quality management. A big stress is
put on the verification of data pre-conditions, complex solution of problems.Non-traditional methods, especially in the field of statistical process control, are taken into account. |
| Learning Outcomes of the Course Unit |
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Students will:
- be able to select suitable graphical methods and statistical tests for verification of data presumptions
- be able to realize complex statistical data analysis
- be able to select suitable method of random sampling
- be able to select and apply suitable system of sampling plans
- be able to compute a analyze supplier and customer risks
- be able to aplly different methods of acceptance sampling for variables
- be able to compute false and missing signal and ARL for selected control charts
- be able to construct and analyse operational characteristics of selected control charts
- be able to select suitable methods of SPC when presumptions for traditional Shewhart control charts are not met
- be able to apply nontraditional SPC methods (control charts for nonnormaly distributed data, for autocorrelated data, for multivariable characteristics, for short run processes, for little changes of process parameters).
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| Course Contents |
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1. Complex statistical data analysis (verification of normality, homogeneity, data independence – graphical methods).
2. Complex statistical data analysis (verification of normality, homogeneity, data independence - statistical tests).
3. Statistical basis of statistical process control (SPC)
4. Preconditions for the correct application of Shewhart control charts and their verification.
5. Survey and selection of classical Shewhart control charts.
6. Construction and analysis of classical Shewhart control charts.
7. Survey and selection of non-traditional control charts.
8. Control charts for non-normally distributed data.
9. CUSUM and EWMA control charts.
10. Target Short Run control charts.
11. Standardized Short Run control charts.
12. SPC for auto-correlated data.
13. SPC for high-yield processes
14. Basics of acceptance sampling.
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| Recommended or Required Reading |
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| Required Reading: |
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MONTGOMERY, D. C. Statistical quality control: A modern introduction. Hoboken: J. Wiley, 2013. ISBN 978-1118146811.
MITRA, A. Fundamentals of quality control and improvement. Hoboken: Wiley, 2016. ISBN: 978-1-118-70514-8.
RYAN, T. P. Statistical methods for quality improvement. Hoboken: J. Wiley and Sons, 2011. ISBN 978-1-118-05811-4.
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http://katedry.fmmi.vsb.cz/Opory_FMMI/639/639-Noskievicova-Specialni-statistika.pdf.
JAROŠOVÁ, E. a D. NOSKIEVIČOVÁ. Pokročilejší metody statistické regulace procesu. Praha: Grada, 2015. ISBN 978-80-247-5355-3.
MONTGOMERY, D. C. Statistical quality control: A modern introduction. Hoboken: J. Wiley, 2013. ISBN 978-1118146811.
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| Recommended Reading: |
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NOSKIEVIČOVÁ, D. Special Statistical Methods for Quality Management. Ostrava: VŠB-TUO, 2012. Available from: http://katedry.fmmi.vsb.cz/Opory_FMMI_ENG/QM/Special%20Statistical%20Methods.pdf.
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http://katedry.fmmi.vsb.cz/Opory_FMMI_ENG/QM/Special%20Statistical%20Methods.pdf.
MITRA, A. Fundamentals of quality control and improvement. Hoboken: Wiley, 2016. ISBN: 978-1-118-70514-8.
TOŠENOVSKÝ, J. a D. NOSKIEVIČOVÁ. Statistické metody pro zlepšování jakosti. Ostrava: Montanex, 2000. ISBN 978-8-072-25040-0.
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| Planned learning activities and teaching methods |
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| Lectures, Tutorials, Project work |
| Assesment methods and criteria |
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| Tasks are not Defined |