To provide the student with statistical tools for designing experiments, evaluating processes and predicting responses. This module will also provide the student with quality tools for supporting quality functions within a manufacturing organisation.
Single-factor Experiments
Principles of experimental design: randomisation, replication, blocking. Hypotheses, models and assumptions. One-way Analysis of Variance, by hand and using software.
Two-factor experiments
Main effects and interaction effects. Design and analysis of two-factor experiments. Interpreting ANOVA tables and interaction plots.
Multi-factor experiments
Fractional factorial experiments. Curvature. Aliasing. Effects plots. Crossed and nested designs. Fixed and random factors. Power and sample size.
Regression and Association
Prediction intervals and confidence intervals in regression.Hypotheses testing in regression. Curvilinear and multiple regression. Selection of variables. Categorical data analysis: contingency tables.
Process Capability and SPC
Process capability analysis: statistics for assessing centrality, normality, stability, capability and performance. Process control: construction of SPC charts for variables and attributes. Corrective, preventive and remedial action.
Quality Management Standards
Management motivation for registration to QMS. Documentation control. Medical Device QMS, Pharma GMP.
Supplier Quality Management
Material traceability. Certificate of Compliance. Vendor auditing, approval and rating.
Quality Audits
Developing an audit plan and schedule. Audit checklists and execution. Auditing reports and corrective actions.
Product Reliability
Product life cycle, MTBF, Failure rate analysis, reliability evaluation.
Quality Awards & Quality Gurus
EIQA, Malcolm Baldridge Quality Award, EFQM Excellence Award, Self-assessment - process and concept. Deming and other Quality Gurus
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Other Assessment(s) | 30 |
| Formal Examination | 70 |