Regression and Advanced Process Control
Regression analysis can uncover information where you thought none existed.
- Three-day course
- Taught at your facilities
- Option to combine it with projects
- Use statistical software (such as MinitabTM) to run regressions
and analyze non-stationary processes
- For technical and senior supervisory staff in the process industries
- Analyse data from your on-line data collection systems
- Find trends and relationships between process parameters
Regression and advanced process control. Course Agenda
Module 1: Regression
Regression in process improvement
Relationships between outputs and inputs
Do the data fit the model? Residual plots.
Regression with more than one input
Analysis of covariance
Interpretation of regression analyses
Logistic regression for pass/fail data
Module 2: Introduction to advanced statistical process control techniques.
The Cusum chart
EWMA charts
Adjustment charts
Module 3: Understanding Dynamic Processes
Properties of dynamic processes
Properties of time series from industrial processes
Stationary models
Non-stationary models
Tools for understanding stationary and non-stationary processes
Some pointers on autocorrelation.
Fitting ARIMA models
Implications for process control
Module 4: Multivariate tools
Fundamentals of multivariate analysis
Principal components analysis
Applications in the process industries.
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