Statistical quality control.

lstat2310  2021-2022  Louvain-la-Neuve

Statistical quality control.
4.00 credits
15.0 h + 5.0 h
Q1
Teacher(s)
Language
French
Main themes
- Statistical tools for quality insurance - Principles and classes of Shewhart control charts - CUSUM and EWMA control charts - Control charts for autocorrelated and multivariate data - Capability analysis - Decomposition of sources of variability. Gauge analysis. - Reception sampling
Learning outcomes

At the end of this learning unit, the student is able to :

1 At the end of this course, the students will have gain knowledge and a critical view of the statistical tools usefull in the setup of quality insurance policy, in process control and daily follow up of analytical devices. They will be able to apply these tools to industrial data sets.
 
Content
The themes discussed in this course are :
  • Statistical tools for quality insurance
  • Principles and classes of Shewhart control charts
  • CUSUM and EWMA control charts
  • Control charts for autocorrelated, multivariate and short run data
  • Capability analysis
  • Reception sampling
Teaching methods
Lectures (15h)
  • Methods presentation on the basis of real-life situations.
  • Formal but intuitive discussion of theoretical concepts and formulae for most methods.
  • Interpretation of software outputs.
  • Interactive lectures: students are encouraged to participate during the course.
 Computer labs (5h)
  • Case studies on JMP, methodological exercises, and JMP Output interpretation. 
Evaluation methods
The evaluation is based on a project, a written exam and an oral exam.  
Other information
Prerequisite : First course in statistical inference
Online resources
See the Moodle site: https://moodleucl.uclouvain.be/course/view.php?id=9935
Bibliography
 D. C. Montgomery, Statistical Quality Control. New York: Wiley.
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Statistics: General

Advanced Master in Nanotechnologies

Master [120] in Statistics: Biostatistics

Master [120] in Biomedical Engineering

Approfondissement en statistique et sciences des données

Minor in Statistics, Actuarial Sciences and Data Sciences

Certificat d'université : Statistique et sciences des données (15/30 crédits)

Master [120] in Mathematical Engineering