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Why are some batches better than others? Why do two identical batch reactors produce different batches? Probably because there has never been a way to compare two or more batches, let alone several batches made in each of two reactors. The solution to this long-term problem has come not from complicated mathematics and statistics but from n-dimensional geometry developed by pioneers in their field, PPCL.

The ability to get more from your batch process starts by considering each of the process and quality variables associated with a batch as a ‘dimension’ in an imaginary n-dimensional space and uses a coordinate transformation to draw a new kind of graph in 2-d space. By taking just a simple example we can use 18 variables from a simple process and place each variable on its own axis. The individual values at a single point in time are plotted on their respective axes. Then these values are joined by lines to show that they form a related set, most commonly a set related by a moment in time. This format becomes infinitely more useful when we put many points onto the graph because the lines begin to form patterns that one can learn to recognise.

These patterns provide a wealth of information but once you log per-batch information into the system you can track conditions for individual batches and this provides something never-before seen. Until now it has been difficult to track information through a batch, but using CVE this is easy to delineate. This program not only gives you never-before-seen insights but also enables things such as keeping product quality high and costs down or enabling parametric batch release.

 

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