Course detail

Statistical Process Control

FSI-XRP-KAcad. year: 2023/2024

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

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. Róbert Jankových, CSc.

Department

Institute of Production Machines, Systems and Robotics (ÚVSSR)

Entry knowledge

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

Rules for evaluation and completion of the course

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.

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 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.
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

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Fiala, A. a kol.: Management jakosti s podporou norem ISO 9000:2000. Verlag Dashöfer, Praha, 2000
Grant, E.L.; Leavenworth, R.S.: Statistical Quality Kontrol. McGraw-Hill, Inc., New York, 7th ed., 1996
Shewhart, W.A.: Statistical Method from the Viewpoint of Quality Control. Dover Publications, INC., New York, 1986

Recommended reading

ČSN ISO 8258:1991: Shewhartovy regulační diagramy. ČSNI, Praha, 1991
Fiala, A.: Statistické řízení jakosti. VUT, Brno, 1997
Kupka, K.: Statistické řízení jakosti. TriloByte Statistical Software, Pardubice, 1997

Classification of course in study plans

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

Type of course unit

 

Guided consultation in combined form of studies

17 hod., compulsory

Teacher / Lecturer

doc. Ing. Róbert Jankových, CSc.

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.

Guided consultation

35 hod., optionally

Teacher / Lecturer

doc. Ing. Róbert Jankových, CSc.

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.