This module introduces a systems engineering approach to design of experiments, data analysis and modelling, towards product and process improvement and optimisation. Students will learn about the Taguchi method for robust engineering design which is a system engineering approach for Quality by Design for process and product development.

15 months long | Credits: 5

This module introduces a systems engineering approach to design of experiments, data analysis and modelling, towards product and process improvement and optimisation. Students will learn about the Taguchi method for robust engineering design which is a system engineering approach for Quality by Design for process and product development. They will explore a range of statistical models and tools and learn how to apply them in a range of problem based learning scenarios using surveys, product and process developmental data. Topics and approaches to be covered include : • ANoVA, DoE with orthogonal arrays, optimisation and minimisation of variability with Signal-to-Noise ratio • Model-based analysis and response surface methodology • Unconfounded experimental designs • Multi-response approaches (PCA and Factor Analysis) Students will also consider affective product design and kansei engineering approaches in the context of real life practice problems.
(Language of instruction: English)

Learning Outcomes
  1. Plan experiments and data collection strategies to determine which factors are more influential on a particular system of interest
  2. Apply a Taguchi approach to identify optimum combination of options of the most influential design factors to minimise non-conformity costs
  3. Fit mathematical models to data using least square regression, determining confidence intervals and error region of model predictions
  4. Use experimental designs without confounding and polynomial models to estimate points of optimum
  5. Apply a factor analysis to extract high-level responses (Principal Components) from a large number of individual responses
  6. Draw quality charts, design tables and Pareto charts.
Assessments

This module's usual assessment procedures, outlined below, may be affected by COVID-19 countermeasures. Current students should check Blackboard for up-to-date assessment information.

  • Continuous Assessment (100%)
Module Director
Lecturers / Tutors
Reading List
  1. "Design of Experiments Using The Taguchi Approach" by Ranjit K. Roy
    ISBN: 0-471-36101-1.
    Publisher: John Wiley & Sons
  2. "Design and Analysis of Experiments" by Douglas Montgomery
    ISBN: 978-0-470-398.
    Publisher: John Wiley & Sons
The above information outlines module ME5108: "Data Analysis for Process and Product Development" and is valid from 2020 onwards.
Note: Module offerings and details may be subject to change.

They will explore a range of statistical models and tools and learn how to apply them in a range of problem based learning scenarios using surveys, product and process developmental data. Topics and approaches to be covered include : • ANoVA, DoE with orthogonal arrays, optimisation and minimisation of variability with Signal-to-Noise ratio • Model-based analysis and response surface methodology • Unconfounded experimental designs • Multi-response approaches (PCA and Factor Analysis) Students will also consider affective product design and kansei engineering approaches in the context of real life practice problems.

On successful completion of this module the learner will be able to:

Plan experiments and data collection strategies to determine which factors are more influential on a particular system of interest

Apply a Taguchi approach to identify optimum combination of options of the most influential design factors to minimise non-conformity costs

Fit mathematical models to data using least square regression, determining confidence intervals and error region of model predictions

Use experimental designs without confounding and polynomial models to estimate points of optimum

Apply a factor analysis to extract high-level responses (Principal Components) from a large number of individual responses

Draw quality charts, design tables and Pareto charts.

Funding for a limited number of places is available under the Modular Skills Provision. Details are available at www.nuigalway.ie/cpd

Contact Information

aisling.monahan@nuigalway.ie

https://www.nuigalway.ie/adult-learning/courses/business-&-management/

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