639-0934/03 – Selected Methods of Industrial Statistics (MPS)
| Gurantor department | Department of Quality Management | Credits | 10 |
| Subject guarantor | prof. Ing. Darja Noskievičová, CSc. | Subject version guarantor | prof. Ing. Darja Noskievičová, CSc. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2019/2020 | Year of cancellation | |
| Intended for the faculties | FMT | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Offering a student deeper theoretical basis of statistical proces control (SPC)and training him in practical applications of basic and advanced methods of SPC using specialized SW are the main goals of this subject. The student will be able to make the complex analysis of the properties of explored data and to choose and apply the most suitable control chart based on this data analysis.
Teaching methods
Individual consultations
Project work
Summary
Subject offers a student deeper theoretical basis of statistical proces control (SPC) and training him in practical applications of basic and advanced methods of SPC using specialized SW. The student will be able to make the complex analysis of the properties of explored data and to choose and apply the most suitable control chart based on this data analysis.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
E-learning
Other requirements
Elaboration of seminar work on a given topic and its defence in the frame of the exam.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Process variability basis. Basic models of the process variability. Statistical basis of SPC.
2 .Selected practical aspects of SPC.
3. Verification of assumptions about data.
4. Selection of the suitable control chart in relation to the results of the data assumptions verification.
5. Control charts for non-normally distributed data.
6. Control charts for processes with non-constant mean.
7. Control charts for detection of medium and small process changes.
8. Control charts for auto-correlated data.
9. Multivariate control charts.
10. Short run control charts.
11. Control charts for high yield processes.
12. SPC and EPC (Engineering Process Control).
13. Adaptive and nonparametric approaches in SPC.
14. Process capability assessment (conventional and nonconventional approaches).
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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