Get More Out Of Your Data With Process Understanding
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- 22/04/2021 - 11:00 am - 12:00 pm CDT
- Every process engineer knows that good data is precious commodity. It is therefore critical to make good (optimal) use of data obtained during the early stages of process development. In this context, the engineer faces a key challenge, i.e., ensuring that data collected at one scale (the lab, for instance) is can be used appropriately at another scale (kilo-scale, for instance). The challenge lies in the fact that equipment shapes and configurations differ from scale to scale – so that without a proper accounting of the “scale-dependent” aspects, data use and re-use cannot be done meaningfully. Accounting for scale dependence, therefore, is a key step towards getting more out of process data.
In this webinar, we show how, using a systematic approach based on process understanding, the scale dependence of process data can be appropriately dealt with. With this approach engineers are able to extract maximal benefits from process data with very minimal efforts. The process understanding based approach will be demonstrated using examples – from the pharma and biopharma industry sectors.
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Get More Out Of Your Data With Process Understanding
22/4/202111:00am CDT1 hourEvery process engineer knows that good data is precious commodity. It is therefore critical to make good (optimal) use of data obtained during the early stages of process development. In this context, the engineer faces a key challenge, i.e., ensuring that data collected at one scale (the lab, for instance) is can be used appropriately at another scale (kilo-scale, for instance). The challenge lies in the fact that equipment shapes and configurations differ from scale to scale - so that without a proper accounting of the "scale-dependent" aspects, data use and re-use cannot be done meaningfully. Accounting for scale dependence, therefore, is a key step towards getting more out of process data.
In this webinar, we show how, using a systematic approach based on process understanding, the scale dependence of process data can be appropriately dealt with. With this approach engineers are able to extract maximal benefits from process data with very minimal efforts. The process understanding based approach will be demonstrated using examples - from the pharma and biopharma industry sectors.