Advanced Course on Quality Management and Engineering
1
2022-2023
03006511
Technology and Environmental Engineering
Portuguese
English
Face-to-face
SEMESTRIAL
6.0
Elective
3rd Cycle Studies
Recommended Prerequisites
Applied Statistics; Quality Systems Engineering
Teaching Methods
Since this discipline aims to provide students with effective knowledge on advanced Quality methods, teaching is divided evenly between exposure classes and field/tutorial classes. Thus, both teacher and students are (equally) active in the process of acquiring knowledge, which also aims to develop autonomous learners.
Learning Outcomes
The objectives of this course are focused on achieving a higher level of proficiency in relevant areas of quality systems and methodologies, including:
- Learn about alternative methodologies and initiatives in the fields of quality management, its improvement and development of new products (e.g., Lean Six Sigma, TOC, Axiomatic Design, Design for Six Sigma). What distinguishes them and which complementariness is present? .
- Measure. Characterization and analysis of measurement systems (MSA, Gauge R&R).
- Analyze. Advanced data analysis (multivariate analysis, clustering techniques, classification).
- Improving. Application of advanced methods of design of experiments (optimal design of experiments; Split-plot designs).
- Control. Advanced process monitoring (multivariate continuous and batch processes).
Work Placement(s)
NoSyllabus
Critical analysis of different methodologies of quality, and its scope (eg lean six-sigma, TOC, etc.).
Measurement systems analysis (MSA) and its repeatability / reproducibility. Analysis of measurement uncertainty and its propagation. Bootstrap methods. Monte Carlo simulation.
Advanced methods for data analysis: linear regression using projection methods, classification methods (parametric and non-parametric classifiers) and cluster analysis.
Optimal design of experiments. Split-plot designs. Supersaturated experimental designs.
Multivariate control charts (continuous and batch processes).
Head Lecturer(s)
Marco Paulo Seabra dos Reis
Assessment Methods
Assessment
Oral presentations, class attendance, small project defences : 40.0%
Project: 60.0%
Bibliography
Vining, G., Kowalski, S.M. “Statistical Methods for Engineers”, 2ªed. (Thomson/Brooks/Cole, ed), 2006.
Montgomery, D. C., “Introduction to Statistical Quality Control”, 5º ed., Wiley, 2005.
Jobson, J. D., Applied Multivariate Data Analysis. Springer-Verlag: New York, 1992; Vol. 2: Categorical and Multivariate Methods.
Martens, H.; Naes, T., Multivariate Calibration. Wiley: Chichester, 1989.
Atkinson, A.C.; Donev, A.N. “Optimum Experimental Designs”. Oxford Science Publications. Oxford Statistical Science Series, vol. 8. Oxford: Clarendon Press, 1992
Fedorov, V.V.; Hackl, P.; Model-Oriented Design of Experiments. Lecture Notes in Statistics. Vol. 125. Springer, 1997.