Statistical Process Control (FSI-XRP-K)

Academic year 2020/2021
Supervisor: doc. Ing. Róbert Jankových, CSc.  
Supervising institute: ÚVSSR all courses guaranted by this institute
Teaching language: Czech
Aims of the course unit:
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.
Learning outcomes and competences:
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.
Prerequisites:
Knowledge of technology and materials. Knowledge of physics and applied statistics. Knowledge of quality management.
Course contents:
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.
Teaching methods and criteria:
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.
Controlled participation in lessons:
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.
Type of course unit:
    Guided consultation in combined form of studies  1 × 17 hrs. compulsory                  
    Guided consultation  1 × 35 hrs. optionally                  
Course curriculum:
    Guided consultation in combined form of studies 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 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.
Literature - fundamental:
1. Fiala, A. a kol.: Management jakosti s podporou norem ISO 9000:2000. Verlag Dashöfer, Praha, 2000
2. Grant, E.L.; Leavenworth, R.S.: Statistical Quality Kontrol. McGraw-Hill, Inc., New York, 7th ed., 1996
3. Shewhart, W.A.: Statistical Method from the Viewpoint of Quality Control. Dover Publications, INC., New York, 1986
Literature - recommended:
1. Fiala, A.: Statistické řízení jakosti. VUT, Brno, 1997
2. ČSN ISO 8258:1991: Shewhartovy regulační diagramy. ČSNI, Praha, 1991
3. Kupka, K.: Statistické řízení jakosti. TriloByte Statistical Software, Pardubice, 1997
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
N-KSB-K combined study --- no specialisation -- Cr,Ex 5 Compulsory 2 1 S