Advanced Techniques for Quality D
- Applying certain specific statistical techniques to short production runs.
- Applying specific control charts to detect small and moderate shifts in the process’ parameters.
- Applying multivariate statistical techniques to control the p quality characteristics.
- Applying specific statistical techniques to the SPC with autocorrelation.
- Applying the adequate methodology to a case study, involving the implementation of control charts.
Ana Sofia Leonardo Vilela de Matos, José Fernando Gomes Requeijo
Weekly - Available soon
Total - 80
-Doty, L. A. (1997). SPC for Short Run Manufacturing
-Guimarães, R. C. e Cabral, J. A. S. (1997). Estatística, McGraw – Hill, Lisboa
-Hawkins, D. M. e Olwell, D. H. (1998). Cumulative Sum Charts and Charting for Quality Improvement, Springer – Verlag, New York
-Montgomery, D. C. (2001). Introduction to Statistical Quality Control, 4th Edition, John Wiley & Sons, New York
-Pereira, Z. L. e Requeijo, J. G. (2012). Qualidade: Planeamento e Controlo Estatístico de Processos, 2ª Edição, FFCT-UNL, Lisboa
-Quesenberry, C. P. (1997). SPC Methods for Quality Improvement, John Wiley & Sons, New York
-Ryan, T. P. (2000). Statistical Methods for Quality Improvement, 2nd edition, Wiley, New York.
-Wheeler, D. J. (1991). Short Run SPC, S.P.C. Press, Knoxville, Tennessee
-Wheeler, D. J. (1995). Advanced Topics in Statistical Process Control, S.P.C. Press, Knoxville, Tennessee
- Expositive theoretical lectures, with systematic appeal to students’ participation.
- Problem-solving and lab sessions with high participation of students.
- Supervision of the students’ work, out of the classroom, related to weekly homework and lab work, in order to motivate them to find the solution most appropriate for solving a specific problem.
- Admission to final exam - the final exam is restricted to students who had made the practical work (one case study), that is presented and discussed at the end of the semester; these practical work is carried out in groups of 3 to 5 students and the minimum classification is 10 points (out of 20).
- The above requirements are valid for the following two school year, if necessary.
- Approval and final classification in the course takes into consideration the following components: (1) one practical work, (2) two assessment tests.
- For approval at UC, the minimum score in the second test is 7 points (out of 20).
- For aproval at UC, the tests average score must be at least 10 points (out of 20).
- The final classification is obtained from the classifications of the three components, with the same weight.
1.Short Run Statistical Process Control
-Z and W charts for variables
-Estimation of the process parameters
-Q charts for variables
-Z and Q charts for attributes
-CUSUM charts for the mean and process dispersion
-Graphs and tables for determining "h"
-CUSUM – FIR chart
3. EWMA Charts
- EWMA charts for the mean and process dispersion
-Graphs and tables for determining the "Lambda" and "K"
-EWMA charts for joint control of the mean and process dispersion
4.Multivariate Statistical Process Control
-Multivariate charts for the mean vector
-Multivariate charts for the covariance matrix
-Interpretation of the multivariate charts
-Multivariate process capability
5.Statistical Process Control with autocorrelated data
-Autocorrelated Function and Parcial Atocorrelated Function
-Charts for residuals/forecast errors
Programs where the course is taught: