Course detail

ÚSI-RTSRPAcad. year: 2020/2021

The subject “Statistical Process Control” will familiarize students with the basic methods of process control, systemic and statistical analysis applicable in the management of an organization and subordinate processes. Students will also understand the rules for the identification of processes and the selection of statistical variables for serial and piece production processes. Students will master the rules of data collection and sorting, as well as the analysis and use of data for statistical process control.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

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 the comprehensive quality management of a company. Students will also master the 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 providers. Students will also learn to identify key and supporting processes, and to apply the methods of statistical quality control in practice.

Prerequisites

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

Co-requisites

Not applicable.

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 the practical application of the topics presented in the 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

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

Course curriculum

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 populations and sampling, 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 via measurement. Control charts.
9. Process capability. Indices of short-term and long-term capability.
10. Gauge capability.
11. Statistical control via comparison. Control charts.
12. Use of regression and correlation analysis in process control.
13. Quality journal.


Seminars in computer labs
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. Gauge capability. Assignment 3.
13. Student presentations – assignment 3. Course unit credit.

Work placements

Not applicable.

Aims

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 improvements to the quality management system.

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

Attendance in lectures is recommended. Attendance at seminars is compulsory. In the case of an excused absence, the teacher may decide on an appropriate substitute assignment.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

JURAN, J. M. a GODFREY, A. B. Juran´s Quality Handbook, Fifth Edition. New York: McGraw-Hill, 1999. ISBN 0-07-034003-X. (CS)
MONTGOMERY, D. C. Introduction to Statistical Quality Control, Sixth Edition. Jefferson City: John Wiley & Sons, Inc., 2009. ISBN 978-0-470-16992-6. (CS)
TOŠENOVSKÝ, J. a NOSKIEVIČOVÁ, D. Statistické metody pro zlepšování jakosti. Ostrava: Montanex a.s., 2000. ISBN 80-7225-040-X. (CS)
JAROŠOVÁ, E. a NOSKIEVIČOVÁ, D. Pokročilejší metody statistické regulace procesu. Praha: Grada Publishing, 2015. ISBN 978-80-247-5355-3. (CS)

Recommended reading

JANKOVÝCH, R. a MAJTANÍK, J., Quality of Weapons and Ammunition I. 1. vyd. Brno: Univerzita obrany, 2008. 84 s. ISBN 978-80-7231-585-7. (CS)
JANKOVÝCH, R. a MAJTANÍK, J., Jakost zbraní a střeliva. Ostrava: Vysoká škola báňská – Technická univerzita Ostrava 2006, 103 s. ISBN 80-248-1208-8. (CS)
KUPKA, K. Statistické řízení jakosti. Pardubice: TriloByte Statistical Software, 1997. ISBN 80-238-1818-X. (CS)

eLearning

Classification of course in study plans

  • Programme RRTES_P Master's

    specialization RRTS , 1. year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Exercise

13 hours, compulsory

Teacher / Lecturer

eLearning