Course syllabus SMMK2 - Statistical Methods for Quality Management II (ŠAVŠ - SS 2019/2020)

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Course title:
Statistical Methods for Quality Management II
Semester:
SS 2019/2020
Course supervisor:
Supervising department: Department of Quantitative Methods (ŠAVŠ)
Prerequisites for registration:
Time allowance:
full-time, 2/2 (hours of lectures per week / hours of seminars per week)
Type of study:
usual, consulting
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:
1.
Introduction (allowance 2/2)
 
a.
Pareto analysis
b.
Histogram

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

3.
Process capability. (allowance 2/2)
 
a.
Capability and performance indices.
b.
Estimation of indices.
c.
Assumptions.

4.
Statistical process control. (allowance 2/2)
 
a.Shewhart control charts for attributes.

5.
Statistical process control. (allowance 2/2)
 
a.
Summary
b.
1. midterm test

6.
Acceptance sampling. (allowance 2/2)
 
a.Types of acceptance sampling.
b.
Attribute acceptance sampling plans based on AQL.

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

8.
Reliability (allowance 2/2)
 
a.
Characteristics of reliability.
b.Exponential distribution model.

9.
Reliability (allowance 2/2)
 
a.
Weibull analysis.

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

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

12.Experimental design. (allowance 2/2)
 
a.
Evaluation of factorial experiments in Statgraphics.
b.
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
Direct teaching
     Attendance of lectures
24 h
     Attendance of courses/seminars/tutorials
24 h
     Consultations with teacher (part-time form of study)0 h
Self-study
     Course reading and ongoing preparation
12 h
     Ongoing evaluation24 h
     Composing of individual (seminar) work
24 h
     Preparation for final test32 h
Total
140 h
 
Assessment methods:
Requirement type
Daily attendance
Active lecture/seminar/workshop/tutorial participation
10 %
Term paper0 %
Mid-term test(s)30 %
Final test
60 %
Total
100 %
 
Course completion:
Evaluation:
Course grade will be determined on the basis of the individual work in seminars (10%), two midterm tests (2x15%) and a final test (60%).

Grades:
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:
Basic:
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.

Recommended:
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:
Field of study N-EM-MP Business Administration and Operations, full-time form, initial period WS 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 Mladá Boleslav
 
Run in the period of:
Course tutor: doc. Ing. Eva Jarošová, CSc. (examiner, instructor, lecturer, supervisor)
Teaching language: Czech
Room:
Mladá Boleslav


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

Type of output: