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| Program start date | Application deadline |
| 2026-01-16 | - |
Program Overview
Process Optimisation in the Pharmaceutical Industry (PE6016)
Module Goal
To enable students to use simple tools to apply the Taguchi method and other optimisation approaches used in Quality by Design and 6-sigma for process improvement and optimisation.
Module Content
Optimisation in pharmaceutical manufacturing: Quality by Design (QbD), its origin in the Taguchi method and the minimisation of variability and non-conformity losses. The systems engineering approach. One-way Analysis of Variance (including application in surveys and clinical trials). Factorial ANoVAs, concept of interactive effects and confoundings. Design of Experiments applied to process assessment and analysis of robustness. Taguchi methods with orthogonal arrays. ANOVA, marginal means addition, and use of signal-to-noise ratio to minimise variability. Model fitting and the role of modelling and Response Surface Analysis in unconfounding effects
Additional Teaching Mode Information
- 1 x 4hr(s) lectures
- 1 x 8hr(s) tutorials
- 1 x 12hr(s) problem-based learning
Course Fact File
| Code | PE6016 |
|---|---|
| Duration | 12 weeks |
| Teaching Mode | Part-Time |
| NFQ Level | Level 9 |
| Fees | €1,000 |
| Closing Date | 04/01/2026 |
| Venue | Blended delivery |
| Credits | 5 |
| Start Date | 16/01/2026 |
Continuous Assessment
- 100 marks
- Assignment - Individual assignment to carry out a survey to gather data, using ANOVA tools to extract conclusions - 50 marks
- In-class test - computer-based - 50 marks
Why Choose
On successful completion of this module, students should be able to:
- Apply a systems engineering approach to data analytics
- Apply a quantitative approach to process assessment and optimisation providing predictive functional relations based on Analysis of Variance and Taguchi approach
- Discuss the implications of the main limitations of the Taguchi method arising from confoundings
- Choose appropriate DoE, demonstrating understanding of the compromises, advantages and limitations of the different options
- Fit mathematical models to data, obtain response surfaces and draw Pareto charts
Requirements
The micro-credential offers graduates working in the pharmaceutical/biopharmaceutical industry as well as students and professionals with basic engineering backgrounds/experience the opportunity to further develop their skill set and employability across a wider range of roles in the industry through enhanced continuing professional development.
