Statistical Quality Control

Subject description

Statistical quality control and business sciences: a historical perspective.

Modern quality management approaches:

  • system
  • model
  • qualitative
  • quantitative

Levels of analysis in statistical quality control:

  • process
  • products and services
  • workplace
  • department
  • organisation

Data sources for statistical quality control.
Sampling for statistical quality control.

Tools and methods of statistical quality control:

  • basic typologies
  • selection and practical application of qualitative tools and methods
  • selection and practical application of quantitative tools and methods (control charts etc.)
  • statistical quality control in real time

Special approaches to quality management in manufacturing and services (education, retailing etc.).

Statistical quality control in haealth care (indicators, classifications, statistical methods, graphical displays).

Statistical quality control and statistical consulting,

Other relevant topics.

The subject is taught in programs

Objectives and competences

The goal of the course is to introduce students to statistical quality control (SQC) emphasising those aspects which are relevant for SQC's practical implementation. Special emphasis is given the comparison of similarities and differences in quality management of manufacturing and services (health services, educational services, retailing … ).

Teaching and learning methods

  • Lectures.
  • Seminars.
  • Tutorials.
  • Project work.
  • Presentations.

Expected study results

In-depth knowledge of theoretical and practical aspects of SQC.

Understanding of the link between SQC and business analysis / business planning.

Skills acquisition:

  • secondary data search, evaluation and use in SQC processes;
  • primary data collection, evaluation and use in SQC processes;
  • use of statistical software packages in quality management processes;
  • data/results of analysis visualisation and dissemination in quality management processes.

Basic sources and literature

  • Coleman, Shirley (ur.), Greenfield, Tony (ur.), Stewardson, Dave (ur.), Montgomery, Douglas C. (ur.). Statistical Practice in Business and Industry, (Statistics in Practice). Chichester: John Wiley & Sons, 2008.
  • Ruggeri, Fabrizio (ur.), Kenett, Ron S. (ur.), Faltin, Frederick W. (ur.). Encyclopedia of statistics in quality and realiability. Chichester: Wiley, 2007 ali kasnejše izdaje/or later editions.
  • Beauregard, Michael R., Mikulak, Raymond J., Olson, Barbara A. (1992): A Practical Guide to Statistical Quality Improvement. Opening up the Statistical Toolbox. New York: Van Nostrand Reinhold.
  • Wheeler D.J. (2000). Understanding Variation (2nd ed.). Knoxville, TX: SPC Press.
  • Nelson P.R., Wludyka P.S., Copeland K.A.F. (2005): The Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions. Philadelphia, PA: SIAM.
  • Winkel P., Zhang N.F. (2007): Statistical Development of Quality in Medicine. Chichester: John Wiley.
  • von Eye A., Mun E.Y. (2005): Analyzing Rater Agreement: Manifest Variable Methods. Mahwah, NJ: Lawrence Erlbaum.
  • Jacobs R., Smith P.C., Street A. (2006): Measuring Efficiency in Health Care: Analytic Techniques and Health Policy. New York: Cambridge University Press.

Stay up to date

University of Ljubljana, Faculty of Electrical Engineering Tržaška cesta 25, 1000 Ljubljana

E: T:  01 4768 411