1. Driving your process monitoring programme with data analytics
11:45-12:00 Course registration
12:00-13:00 Lunch
13:00-15:00 Industry 4.0 and analytics; Analytical strategies – trending and modeling; Which methods for which data
15:00-15:20 Tea/coffee
15:20-17:30 Multivariate analysis and machine learning and AI; Process monitoring program – what, how and when; Manufacturing Intelligence
“Across industries one of the main challenges in the manufacturing processes is to monitor and control variation. Successful variation control ensures predictable production and accompanying business benefits. Recently there have been major developments in sensor technology allowing an increasing number of inline and online measurements. Together with improvements in IT infrastructure and technology, the sensor development contributes to rapid growth in the data available for any process. The big data challenge requires suitable timely analytics to enable each factory to make the most of the opportunities the new paradigm is offering. A common label for this challenge is Industry 4.0.
Analytics is a key component within Industry 4.0. Relevant actionable results are required, and these results must be available for the control system in a timely manner. Multivariate methods are well established and proven useful within process monitoring. Lately there have also been a number of applications where machine learning and AI have been considered. The choice of method depends on the type of data available and the purpose of the analytics.
In this training the challenges and opportunities for monitoring and control within the big data paradigm are reviewed. The focus is on analytics and integration within the manufacturing process. The underlying question which we are trying to answer is how to create and apply manufacturing intelligence.”
This course will be facilitated by Geir Rune Flaten, CAMO Analytics.
2. Screening and optimisation design options for DoE
11.45-12.00 Course Registration
12.00-13.00 Lunch
13.00- 15.00 Theory: Introduction to Design of Experiments (DoE). Introduction to designs including: Full & Fractional Factorial (classical), Plackett-Burman, Response Surface, Mixture and Definite Screening Designs. The theory behind some of the most commonly applied designs from a design and analysis perspective will be explored with practical examples. Advantages and disadvantages of the designs with a particular focus on Definitive Screening Designs will be discussed. Course delegates will share their knowledge and any industrial case studies with the rest of the learning cohort.
15.00-15.20 Tea/Coffee
15.20-17.30 Application: Setting up and analysing designs within software. Course delegates will practice using the designs within a statistical software package. The session will close with a summary discussion and action planning.
This course will be facilitated by Matt Linsley, Newcastle University.
3. Advanced spectral preprocessing without equations
Advanced Spectral Preprocessing without Equations takes up where our Chemometrics without Equations course leaves off. It is assumed that participants will have a working knowledge of Principal Components Analysis (PCA) and regression with Partial Least Squares (PLS). The concentrates on improving chemometric models via advanced preprocessing methods.
The critical difference between inadequate and successful chemometric models is often data preprocessing, i.e. what is done to the data before using PCA, PLS etc. The goal of preprocessing is to remove variation not related to the problem of interest so that the variation of interest is more evident and can be more easily modeled. The course focuses on advanced preprocessing methods, including baselining, normalization, smoothing and derivatives, Extended Multiplicative Scatter Correction (EMSC) and Generalized Least Squares (GLS), for improving models. The effect of preprocessing on robustness of the final models is also considered.
11:45-12:00 Course registration
12:00-13:00 Lunch
13:00-15:00 Review of PCA/PLS, centering, normalization, and baselining methods and specialized scaling
15:00-15:20 Tea/coffee
15:20-17:30 Filtering and derivatives, GLS, EMSC
The course will be facilitated by Barry M. Wise, President of Eigenvector Research and creator of PLS_Toolbox chemometric software.
4. An introduction to process control for scientists, chemists and pharmacists
The course will provide an overview of closed loop process control for scientists and engineers that have no background in process control and automation. Sufficient knowledge will be provided to allow delegates to appreciate the scope of process control techniques and the challenges that need to be considered when implementing process control strategies within a PAT and QbD environment. The topics will include classical feedback control with process examples; feedforward and inferential control; multi-loop control; analytical feedback control; and will finish with a brief overview of more advanced control systems now being applied. Industrial case studies will be used.
11:45-12:00 Course registration
12:00-13:00 Lunch
13:00-15:00 The Building Blocks of Process Control: An Introduction to Feedback Control, Proportional Control (P); Proportional + Integral Control (PI), Proportional + Integral + Derivative Control (PID) Control
15:00-15:20 Tea/coffee
15:20-18:00 Multi-loop Control Systems: Cascade Control; Ratio Control; Feedforward Control; Model Based Predictive Control; Inferential Measurement & Software Sensors
This course will be facilitated by Prof Julian Morris, CPACT's Technical Director.
The courses will be open to conference delegates as an additional option at a reduced rate of £150, or may be attended on a ‘course only’ basis at a cost of £300.
Please register via the on-line shop: https://onlineshop.strath.ac.u...