Module Overview

Quality & Reliability 2

This subject focuses the student on developing knowledge, know-how, skill and competence in more advanced approaches to Quality & Reliability Engineering. It equips students with the capability to design, select, apply and interpret a variety of statistical techniques for process analysis and testing, undertaking engineering experiments, six-sigma problem solving and reliability analysis. It introduces students to predictive modelling in the context of process optimisation.

Module Code

QURL 4111

ECTS Credits

5

*Curricular information is subject to change

1. Process Characterization and Experimental Design: Descriptive Statistics & Graphical Presentation of same, Correlation and Simple Linear Regression, Hypothesis tests applied to Engineering Experiments, ANOVA Analysis, 1FAAT, Full Factorial experiments, Fractional Factorial/Taguchi Orthogonal Arrays, Graphical Analysis of factors, Prediction equations. Practical experiment. The application of Gage R&R Analysis to Measurement Systems, Use of Minitab software

2. Six Sigma Quality: Analysis, Improvement and Control Stages in DMAIC, Cause and Effect Matrices, Control Plans. Six Sigma case studies

3. Reliability Engineering: Reliability Test Planning and Testing, HASS, HALT, FRACAS, Accelerated Life Tests,  Sample Size Determination, Test Environments, Environmental Stress Screening: Definition, Types of Stress Screening, Case Histories, Implementing An ESS Program, Weibull Analysis & Probability Plotting, Case Study On Reliability Engineering in Design

4. Quality Assurance Models/Philosophies: The TQM journey, Effective practical quality principles outlined by Juran, Deming and other Quality gurus.  TQM case studies

5. Quality Management: Strategic Quality Management, Organization for Quality, Developing a continuous improvement culture, Competitive benchmarking, World-Class methodologies for change management, Balanced Scorecard

6. Validation Overview

7. Introduction to Predictive Modelling: Classification & Regression Technique (CART) & Random Forest

  Approaches to Process Optimisation

Lectures, In-Class Tutorials  using Minitab software and manual exercises, Videos, Case Studies, Team Project Work

Module Content & Assessment
Assessment Breakdown %
Formal Examination75