MSE Master of Science in Engineering

The Swiss engineering master's degree

Jedes Modul umfasst 3 ECTS. Sie wählen insgesamt 10 Module/30 ECTS in den folgenden Modulkategorien:

  • ​​​​12-15 ECTS in Technisch-wissenschaftlichen Modulen (TSM)
    TSM-Module vermitteln Ihnen profilspezifische Fachkompetenz und ergänzen die dezentralen Vertiefungsmodule.
  • 9-12 ECTS in Erweiterten theoretischen Grundlagen (FTP)
    FTP-Module behandeln theoretische Grundlagen wie die höhere Mathematik, Physik, Informationstheorie, Chemie usw. Sie erweitern Ihre abstrakte, wissenschaftliche Tiefe und tragen dazu bei, den für die Innovation wichtigen Bogen zwischen Abstraktion und Anwendung spannen zu können.
  • 6-9 ECTS in Kontextmodulen (CM)
    CM-Module vermitteln Ihnen Zusatzkompetenzen aus Bereichen wie Technologiemanagement, Betriebswirtschaft, Kommunikation, Projektmanagement, Patentrecht, Vertragsrecht usw.

In der Modulbeschreibung (siehe: Herunterladen der vollständigen Modulbeschreibung) finden Sie die kompletten Sprachangaben je Modul, unterteilt in die folgenden Kategorien:

  • Unterricht
  • Dokumentation
  • Prüfung
Quality Control (TSM_QCheck)

Introduction:

  • Introduction to Quality Control
  • Statistics refresher: Probability distributions, sampling distributions, inference
  • Overview of the most commonly used problem-solving tools: histogram, plots, Pareto chart 

Problem-solving methodology:

  • Quality management approaches: QRQC, A3, 8D, DMAIC, etc.
  • Statistical analysis: t-tests, confidence intervals

Introduction to Statistical Process Control :

  • Customer and supplier risk 
  • Acceptable Quality Level 
  • Acceptance Sampling plans
  • Control charts: variable, attribute, multivariate
  • Analysis of Variance (ANOVA)
  • Process and Measurement System Capabilities
  • Gage repeatability and reproducibility, GR&R studies 

Design of experiments:

  • Process optimization with designed experiments
  • Factorial and fractional experimental designs
  • Surface response methodology

Eintrittskompetenzen

Prior to joining the module, the students should be familiar with the basics of statistics (variance, standard deviation, probability density). The student should also understand the concepts of measurement uncertainty, repeatability and reproducibility.

Knowledge of design/mechanical drawing reading/tolerancing

Lernziele

 

At the end of the module, the students should

 

  • Understand the quality management approach
  • Understand the functioning and apply the principles of statistical process control
  • Be able to estimate the capability of a measuring device for the quality control
  • Be able to make a conformity decision
  • Be able to evaluate the resulting customer/supplier risks
  • Be able to set up a sampling plan for a given Acceptable Quality Level
  • Know the most commonly used SPC methods and understand their main limitations.
  • Understand the different methods for problem solving
  • Be able to setup and analyze a designed experiment for process improvement.
  • Understand the main quality wordings.

Modulinhalt

 

  • Introduction to quality management: 10%
  • Problem solving methodology: 20%
  • Introduction to Statistical Process Control: 20%
  • Incoming quality control: 10%
  • Metrologic performance and measurement capability: 10%
  • Design of Experiments: 20%
  • Examples and case studies: 10% 

 

Lehr- und Lernmethoden

 

  • Lectures
  • Exercises
  • Case studies
  • Self-study of SPC methodologies


Bibliografie

D. Montgomery, "Introduction to Statistical Quality Control", 8th ed., Wiley & Sons (2020)
D. Montgomery, "Design and Analysis of Experiments", 10th ed., Wiley & Sons (2019)
Quality Trainer, qualitytrainer.minitab.com, Minitab
E.L. Cano, J.M. Moguerza and A. Redchuk. "Six Sigma with R. Statistical Engineering for Process Improvement", UseR ! series. Springer, (2012)

M. Pillet, « Six Sigma: Comment l'appliquer » , Ed. Eyrolles (2013)

Vollständige Modulbeschreibung herunterladen

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