In this webinar we look at the use of designed experiments in industrial settings and show how they can be used to draw conclusions about the robustness of manufacturing processes.
Designed experiments performed in the lab or on pilot equipment often don’t scale up when applied on production lines. This can be because they don’t include information on the noise parameters and so results may not translate accurately to production environments.
Randomised Complete Block Designs can help address these issues by actively using blocks of noise factors to investigate whether experimental results are consistent over a range of conditions.
Blocks can be raw material batches, time, different operators etc and the differences between the results across the blocks can provide information about long- and short-term sources of variation.
In this webinar Nicola Brammer from Solvay presents an example of how this experimental design was used during the start-up of a new production facility where the process parameter tolerances needed to be defined on a limited number of large scale batches before ‘locking in’ those parameters.
The webinar will be presented by Nicola Brammer, Senior Process Engineer, Solvay. It will be hosted by Adam Duckett, Editor of The Chemical Engineer magazine.
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Nicola Brammer works as a senior process engineer and six sigma master blackbelt for Solvay in the UK. Her work includes process improvement and new product/process introduction as well as training other engineers in the use of data for problem solving.
She graduated with a PhD in Chemistry in 1994. Nicola uses JMP for exploratory data analysis, SPC and for the design and analyse of DoE experiments.
This webinar has been prepared by Solvay. Its content has not been reviewed, endorsed or approved by IChemE/The Chemical Engineer.
7th June 2022