Course syllabus SMMK2 - Statistical Methods for Quality Management II (ŠAVŠ - SS 2018/2019)

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Course title:
Statistical Methods for Quality Management II
Semester: SS 2018/2019
Course supervisor:
Supervising department: Department of Logistics, Quality and Automotive Technology (ŠAVŠ)
Prerequisites for registration: Bachelor state examination
Time allowance: full-time, 2/2 (hours of lectures per week / hours of seminars per week)
Type of study:
usual
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/tutorials24 h
     Consultations with teacher (part-time form of study)
0 h
Self-study
     Course reading and ongoing preparation
12 h
     Ongoing evaluation
24 h
     Composing of individual (seminar) work
24 h
     Preparation for final test
32 h
Total
140 h
 
Assessment methods:
Requirement typeDaily attendance
Active lecture/seminar/workshop/tutorial participation10 %
Term paper
0 %
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.

Recommended:
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.
ČSN ISO 8258.: Shewhartovy regulační diagramy. Praha,: 1993. 35 p.
MONTGOMERY, D. Statistical quality control. A modern introduction. 6. vyd. Hoboken: John Wiley and Sons, 2009. 734 p. ISBN 978-0-470-23397-9.

Study plans:
Field of study N-EM-MP Business Administration and Operations, full-time form, initial period WS 2017/2018, place of teaching Mladá Boleslav
Field of study N-EM-MP Business Administration and Operations, full-time form, initial period SS 2017/2018, place of teaching Mladá Boleslav
 
Run in the period of: WS 2020/2021, SS 2019/2020, WS 2019/2020, WS 2018/2019, SS 2017/2018, WS 2017/2018 (and older)
Course tutor:
doc. Ing. Eva Jarošová, CSc. (examiner, instructor, lecturer, supervisor)
Teaching language:
Czech
Room:
Mladá Boleslav


Last modification made by Mgr. Luděk Švejdar on 11/12/2018.

Type of output: