Course syllabus SMMK2 - Statistical Methods for Quality Management II (ŠAVŠ - WS 2020/2021)

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Course title:
Statistical Methods for Quality Management II
Semester: WS 2020/2021
Course supervisor:
Supervising department:
Department of Quantitative Methods (ŠAVŠ)
Prerequisites for registration:
Bachelor state examination
Time allowance:
full-time, 2/2 (hours of lectures per week / hours of seminars per week)
part-time, 0/16 (lectures per period / seminars per period)
Type of study:
Form of teaching:
lecture, seminar
Mode of completion and credits:
Exam (5 credits)
Course objective:
The aim is to deepen the knowledge of basic statistical tools for quality control and to acquaint students with the advanced statistical methods used for quality improvement.
Course methods:
Seminars with the use of Excel and Statgraphics. Individual work at the end of each seminar.
Two midterm tests in the 5. and 10. seminar.
Course content:
Introduction (allowance 2/2)
Pareto analysis

Statistical process control. (allowance 2/2)
Shewhart control charts for variables.
Properties of Shewhart control charts.

Process capability. (allowance 2/2)
Capability and performance indices.
b.Estimation of indices.

Statistical process control. (allowance 2/2)
a.Shewhart control charts for attributes.

Statistical process control. (allowance 2/2)
b.1. midterm test

Acceptance sampling. (allowance 2/2)
Types of acceptance sampling.
Attribute acceptance sampling plans based on AQL.

Acceptance sampling (allowance 2/2)
System of acceptance plans.
Acceptance sampling by variables.

Reliability (allowance 2/2)
Characteristics of reliability.
b.Exponential distribution model.

Reliability (allowance 2/2)
Weibull analysis.

10.Experimental design. (allowance 2/2)
Aims of experiments. Basic techniques of experimentation.
b.Completely randomized design, randomized blocks.
Evaluation methods, t-test, ANOVA.

Experimental design. (allowance 2/2)
Full and fractional factorials.

Experimental design. (allowance 2/2)
Evaluation of factorial experiments in Statgraphics.
Experiments for measurement system analysis.

Learning outcomes and competences:
After completing the course, student:
Will be able to analyse a process and assess its ability to meet customer expectations
Will be able to design an experiment to study effects of one or more factors, analyse data, and interpret results
-Will be able to estimate major reliability measures based on a given model and interpret their values
-Will be able to explain the basis of statistical process control, choose a suitable type of the Shewhart chart for a given case, apply the chart and interpret the results
-Will be able to identify the most important causes of problems through the Pareto chart
Will be able to list and clarify types of acceptance sampling plans, explain the relationship between parameters of a plan and its effectiveness

Teaching methods and workload (hours of workload):
Type of teaching method
Daily attendance
Combined form
Direct teaching
     Attendance of lectures
24 h
0 h
     Attendance of courses/seminars/tutorials24 h16 h
     Consultations with teacher (part-time form of study)
0 h
8 h
     Course reading and ongoing preparation12 h
12 h
     Ongoing evaluation24 h
32 h
     Composing of individual (seminar) work
24 h
32 h
     Preparation for final test32 h
40 h
140 h
140 h
Assessment methods:
Requirement type
Daily attendance
Combined form
Active lecture/seminar/workshop/tutorial participation
10 %0 %
Term paper
0 %
10 %
Mid-term test(s)
30 %
30 %
Final test
60 %
60 %
Total100 %
100 %
Course completion:
Course grade will be determined on the basis of the individual work in seminars (10%), two midterm tests (2x15%) and a final test (60%).

100-90 - excellent
89 -75 - very good
74 -60 - good
less then 60 - failed
Support for combined/distance forms of study:
Study support guide for part-time mode of study is available in the AIS.
Examples from exercises with solution are available in the AIS.
Individual consultation on students request.
Reading list:
Language of instruction: Czech
JAROŠOVÁ, E. Statistické metody řízení jakosti pro kombinovanou formu studia. 1st ed. Mladá Boleslav: Škoda Auto a. s., 2011. ISBN 978-80-87042-37-3.
ČSN ISO 2859-1.: Statistické přejímky srovnáváním - část 1: Přejímací plány AQL pro kontrolu každé dávky v sérii. Praha: Český normalizační institut, 2000.
Regulační diagramy - Část 2: Shewhartovy regulační diagramy: ČSN ISO 7870-2. Úřad pro technickou normalizaci, metrologii a státní zkušebnictví, 2018. 48 p.
SIBERT, N M. Cepi, signaly, systemy 1. Moskva: MOSKVA, 1988. 336 p.
JAROŠOVÁ, E. Statistické metody managementu kvality pro prezenční a kombinovanou formu studia. 1st ed. ŠAVŠ o.p.s., 2019. 158 p. ISBN 978-80-87042-73-1.

MONTGOMERY, D.C.: Statistical quality control. 7th ed. Hoboken: John Wiley and Sons, 2012. ISBN 978-1-118-14681-1.
Language of instruction: Czech
JAROŠOVÁ, E. -- NOSKIEVIČOVÁ, D. Pokročilejší metody statistické regulace procesu. Praha: Grada Publishing, a.s., 2015. 290 p. ISBN 978-80-247-5355-3.
JAROŠOVÁ, E. Navrhování experimentů a jejich analýza. Praha: ČSJ, 2007. ISBN 978-80-02-01985-5.
KŘEPELA, J. -- FABIAN, F. -- HORÁLEK, V. Statistické metody řízení jakosti. Praha: ČSJ, 2007. 390 p. ISBN 978-80-02-01897-1.

Study plans:
Track N-EMCZ-NRMDR International Supply Chain Management, part-time form, initial period SS 2018/2019, place of teaching Mladá Boleslav
Track N-EMCZ-NRMDR International Supply Chain Management, full-time form, initial period SS 2018/2019, place of teaching Praha
Track N-EMCZ-NRMDR International Supply Chain Management, full-time form, initial period WS 2019/2020, place of teaching Praha
Track N-EMCZ-NRMDR International Supply Chain Management, part-time form, initial period WS 2019/2020, place of teaching Mladá Boleslav
Run in the period of:
SS 2019/2020, WS 2019/2020, SS 2018/2019, WS 2018/2019, SS 2017/2018, WS 2017/2018 (and older)
Course tutor:
doc. Ing. Eva Jarošová, CSc. (examiner, instructor, lecturer, supervisor)
Teaching language:
Mladá Boleslav, Praha

Last modification made by Ing. Lucie Bydžovská on 04/07/2020.

Type of output: