Course Details

Course Code(s):
MS5431
Available:
Part-Time
Intake:
Spring
Course Start Date:
Spring 2025
Duration:
5 Weeks
Award:
University Certificate of Study
Faculty: Science and Engineering
Course Type: Professional/Flexible
Fees: For Information on Fees, see section below.

Contact(s):

Name: SEFLC
Address: Science & Engineering Flexible Learning Centre Email: seflc@ul.ie
Express Interest

Register your interest here for more information or to be notified when applications are open.

Brief Description

Please ensure you enter the Module Code below when applying for this MicroCred. Applications without this cannot be processed.

You may apply for more than one MicroCred under the same application.

Module Description

Module Code

NFQ Level

ECTS Credits

Start Date

 Cost 

Quality Science 

MS5431

9

6

TBC

€1,000

This micro-credential represents a single module within a larger further award (e.g., Certificate, Diploma, Masters). By taking this micro-credential you may be eligible to apply for a credit exemption should you progress to study for a further award.

The programmes associated with this MicroCred are: 

 

This module introduces and applies both basic and advanced quality statistics, appropriate for master black belt level Six Sigma, in the context of Supply Chain Performance Management. Learners will also learn to build on this foundation so that you have the confidence and statistical skills necessary to visualise and interpret data for better decision making.

The overall objectives of the module are:

  • to introduce you to the concept of Quality Science,
  • to give you a foundation in statistical tools and scientific methods for problem solving in the context of Supplier Performance Management.

You will learn to build on this foundation so that you have the confidence and statistical skills necessary to visualise and interpret data for better decision making in the supply chain, specifically Supplier Performance Management.

  • Appreciate the power of data analysis and quality science tools in supporting decision making in the Supply Chain
  • Practise and experiment with key tools from Quality Science in a problem-based learning environment. including:
    • Graphical Methods: Graphs, histograms, location, spread, Boxplots
    • Quantitative Methods: Measures of Centre, Measures of Variation
    • Inferential Statistics: Distribution theories
    • Inferential Statistics: Hypothesis Testing
    • Inferential Statistics: Analysis of Variance
    • Process Capability
    • Statistical Process Control
  • Apply statistical software tools to undertake quantitative analysis of problems in the supply chain
  • Formulate solutions for internal supply chain problems using external sources (benchmarking from best-in-class case studies).
  • Develop transferable skills in scientific decision making for current and future problem scenarios.

On successful completion of this module students will be able to:

  • Critique the current theory, practices, and processes in the application of Quality Science Statistics to Supplier Performance Management,
  • Apply Key Performance Indicators for successful supply chain management,
  • Recognise effective Supplier Performance Management practices,
  • Produce a document which effectively critiques their organisations strategy and application of quality science statistics to Supplier Performance Management.
  • Engage in critical discussion regarding Supplier Performance Management topics with peers from a variety of industry backgrounds,
  • Apply your empirical and professional experience to critically analyse published research and industry white papers.

This module is open to those currently employed, or seeking employment, in a variety of industries such as Manufacturing, Service, Retail, Defence Forces, Health Care Services; Pharmaceutical, Medical Devices, Aviation, Semiconductors etc.

Applicants must have a minimum second-class Level 8 honours degree (QQI NFQ or other internationally recognised equivalent) in a relevant or appropriate subject, or equivalent prior learning that is recognised by the University as meeting this requirement.

Applicants must also satisfy the English Language Requirements of the University.

Entry requirements are established to ensure the learner can engage with the course material and assessments, at a level suitable to their needs, and the academic requirements of the module. By applying to this micro-credential, you are confirming that you have reviewed and understand any such requirements, and that you meet the eligibility criteria for admission.

Successful completion of this module does not automatically qualify you for entry into a further award. All programme applicants must meet the entry requirements listed if applying for a further award.

The fees for this programme are €1,000

Please click here for information on funding and scholarships.