First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
STATISTICS FOR ECONOMICS AND BUSINESS
Course unit
STATISTICAL QUALITY CONTROL
SCP4063665, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course First cycle degree in
STATISTICS FOR ECONOMICS AND BUSINESS
SC2095, Degree course structure A.Y. 2014/15, A.Y. 2019/20
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination STATISTICAL QUALITY CONTROL
Website of the academic structure http://www.stat.unipd.it/studiare/ammissione-lauree-triennali
Department of reference Department of Statistical Sciences
Mandatory attendance No
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge GUIDO MASAROTTO SECS-S/01

Mutuating
Course unit code Course unit name Teacher in charge Degree course code
SCP4063665 STATISTICAL QUALITY CONTROL GUIDO MASAROTTO SC2094

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines SECS-S/01 Statistics 9.0

Course unit organization
Period Second semester
Year 3rd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Laboratory 4.5 32 80.5 No turn
Lecture 4.5 32 80.5 No turn

Calendar
Start of activities 02/03/2020
End of activities 12/06/2020
Show course schedule 2019/20 Reg.2014 course timetable

Syllabus
Prerequisites: None
Target skills and knowledge: This course aims to present the main tools of statistical process control (SPC) and their use in several frameworks. At the end of the course, students will be able to establish the stability over time of the distribution of one and more quality characteristics. Then, they will be able to analyze the capability to produce units satisfying given specification limits.
Examination methods: Written examination. Multiple choice questions concerning the statistical analysis of real data. Reports and analysis are performed in the lab using the R software.
Assessment criteria: The evaluation of the preparation of students will be based on the understanding of the handled topics, the acquisition of concepts and skills to apply them.
Course unit contents: 1) Techniques for univariate statistical process control (products and services)
a) Sampling plans.
b) Elements of acceptance sampling;
c) Commom and special causes of variation.
2) Univariate parametric control charts.
a) Shewhart, CUSUM and EWMA control charts for variables and attributes;
b) Performance measures and optimal design of control charts(ARL, curve CO, FAP, exact and approximate computations);
c) Known and unknown process parameters (Phase I and Phase II methods);
d) Characterization of random and nonrandom patterns
3) Capability analysis.
a) Capability measures (estimation in the univariate case);
b) Six-sigma and Lean Quality Systems;
c) Capability versus Statistical Process Control.
4) Techninques for quality improvement.
a) Pareto's analysis, Failure Mode and Effective Analysis (FMEA) methods;
b) Inroduction to DOE and nested ANOVA to identify significative source of variation.
Planned learning activities and teaching methods: Lectures.

Labs are the core of the course. Case studies are analyzed using the R language. Practical problems are discussed doing an accurate exploratory data analysis and applying the main tools of the statistical process control.
Additional notes about suggested reading: Slides of the lectures and written comments to the case studies, discussed during labs, will be available on the website.
Textbooks (and optional supplementary readings)
  • Montgomery D. C., Controllo statistico della qualità 2/ed.. --: McGraw-Hill., 2006. ISBN: 9788838662447 Cerca nel catalogo
  • Qiu, Peihua., Introduction to statistical process control. --: CRC Press, 2013. Cerca nel catalogo