Course detail
Statistical Process Control
FSI-XRPAcad. year: 2025/2026
The subject “Statistical Process Control” will familiarize students with the basic methods of process control, systemic and statistical analysis applicable in management of an organization and subordinate processes. Students will also understand the rules for identification of processes and selection of statistical variables for serial and piece production processes. The students will master the rules of data collection and sorting, their analysis and use for statistical process control.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Entry knowledge
Rules for evaluation and completion of the course
The exam has both written and oral parts. Exam evaluation is graded on the ECTS grading scale: excellent (90-100 points), very good (80-89 points), good (70-79 points), satisfactory (60-69 points), sufficient (50-59 points), failed (0-49) points.
Attendance in lectures is recommended. The attendance at seminars is compulsory. In case of excused absence, the teacher may decide on an appropriate substitute assignment.
Aims
The subject “Statistical Process Control” allows students to gain knowledge of methods of statistical process control as a part of complex quality management of a company. Students will also master identification of processes suited for statistical control. They will learn to apply individual methods of statistical quality control when solving problems, which may arise in manufacturing companies as well as service companies. Students will also learn to identify the key and supporting processes and to practically apply the methods of statistical quality control.
Study aids
Prerequisites and corequisites
Basic literature
Michálek, J. Vyhodnocování způsobilosti a výkonnosti výrobního procesu. Praha: CQR, 2009. ISBN 978-80-903834-2-5. (CS)
MONTGOMERY, D. C. Introduction to Statistical Quality Control, Sixth Edition. Jefferson City: John Wiley & Sons, Inc., 2009. ISBN 978-0-470-16992-6. (EN)
Shewhart, W.A. Statistical Method from the Viewpoint of Quality Control. New York: Dover Publication, INC., 1986. (EN)
Tošenovský, J. a Noskievičová, D. Statistické metody pro zlepšování jakosti. Ostrava: Montanex a.s., 2000. ISBN 80-7225-040-X. (CS)
Recommended reading
Kupka, K. Statistické řízení jakosti. Pardubice: TriloByte Statistical Software, 1997. ISBN 80-238-1818-X. (CS)
Classification of course in study plans
- Programme N-KSB-P Master's 1 year of study, summer semester, compulsory
- Programme N-SLE-P Master's 1 year of study, summer semester, compulsory
- Programme RRTES_P Master's
specialization RRTS , 1 year of study, summer semester, compulsory-optional
- Programme C-AKR-P Lifelong learning
specialization CLS , 1 year of study, summer semester, elective
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
1. Processes in the product life cycle. Variability of processes. Statistical process control (SPC) methods.
2. Identification of different types of processes. Selection of statistical variables for process control. Statistical population and sample, characteristics of location and dispersion.
3. Collection of data, statistical tables and graphs. Theoretical
distributions and their use in SPC.
4. Histograms as quality management tools. Identification of systemic influences using histograms. Testing the fit of a theoretical distribution to measured data.
5. Cause and effect analysis. Ishikawa diagram.
6. Distinguishing critical and inconsequential causes – Pareto analysis.
7. Statistical process control. General rules for statistical control.
8. Statistical control by measurement. Control charts.
9. Process capability. Indices of short-term and long-term capability.
10. Gauge capability.
11. Statistical control by comparison. Control charts.
12. Use of regression and correlation analysis in process control.
13. Quality journal.
Computer-assisted exercise
Teacher / Lecturer
Syllabus
1. Descriptive statistics, basic use of statistical software.
2. Probability distributions – properties and uses.
3. Histograms, tests of good fit.
4. Cause and effect analysis - Ishikawa diagram.
5. Pareto analysis. Assignment 1.
6. Student presentations – assignment 1.
7. - 9. Control charts.
10. Process capability. Assignment 2.
11. Student presentations – assignment 2.
12. Gage capability. Assignment 3.
13. Student presentations – assignment 3. Course-unit credit.