Course detail

Statistical Process Control

FSI-XRP-KAcad. year: 2020/2021

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.

Learning outcomes of the course unit

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.


Knowledge of technology and materials. Knowledge of physics and applied statistics. Knowledge of quality management.


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Fiala, A. a kol.: Management jakosti s podporou norem ISO 9000:2000. Verlag Dashöfer, Praha, 2000
Fiala, A.: Statistické řízení jakosti. VUT, Brno, 1997
ČSN ISO 8258:1991: Shewhartovy regulační diagramy. ČSNI, Praha, 1991
Grant, E.L.; Leavenworth, R.S.: Statistical Quality Kontrol. McGraw-Hill, Inc., New York, 7th ed., 1996
Kupka, K.: Statistické řízení jakosti. TriloByte Statistical Software, Pardubice, 1997
Shewhart, W.A.: Statistical Method from the Viewpoint of Quality Control. Dover Publications, INC., New York, 1986

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Seminars are focused on practical application of topics presented in lectures.
Lectures by industry experts and excursions to companies focused on activities related to the course content will be included when possible.

Assesment methods and criteria linked to learning outcomes

The course unit credit requirements: Active participation in seminars, submission and presentation of analyses as assigned by the teacher.
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.

Language of instruction


Work placements

Not applicable.


The first goal of “Statistical Process Control” is to familiarize students with the basic statistical methods of process control. Another goal is to teach students to use the fact, that real processes have a stochastic character, thus the rational approach to their management requires the application of statistical methods. The third goal is to teach students to apply statistical process control tools to standard and specific company processes and to devise appropriate improvement measures in the context of quality management system improvement.

Specification of controlled education, way of implementation and compensation for absences

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.

Classification of course in study plans

  • Programme N-KSB-K Master's, 1. year of study, summer semester, 5 credits, compulsory

Type of course unit


Guided consultation in combined form of studies

17 hours, compulsory

Teacher / Lecturer


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.

Guided consultation

35 hours, optionally

Teacher / Lecturer


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.