Today, computational modeling and simulation (M&S) is a key
component of process development in the chemical, pharma and
biotech industries. The popularity and success of modeling
can be largely attributed to its ability to predict with
great accuracy the (3-D) flow, mixing, mass-transfer etc.
fields inside process equipment such as reactors, pumps,
centrifuges, mixers etc. Further, simulation data is
naturally rich in detail from which important process
insights can be extracted. However, despite these
advantages, the full potential of M&S as a “go-to” process
development and scale-up activity remains unfulfilled. This
is because, the process insights extracted from simulation
data is not readily available for easy consumption to the
greater process engineering community within an
organization.
Specifically, analysts do not have a process knowledge
repository solution that enables them to meaningfully store,
curate and distribute process insights to the greater
process engineering community. Simulation data and process
insights/knowledge derived from it largely reside in
presentation decks, cumbersome worksheets etc. which are
hard to maintain and not scalable. This situation is not
optimal and needs to be rectified relatively fast.
In this seminar, we present some key strategies to
successfully address this problem of process knowledge
management. Methods by which simulation data can be
converted into process knowledge are first presented. This
is followed by a description of a workflow that enables
efficient storage and curation of the process knowledge.
Finally, we present methodologies by which the stored
process knowledge can be distributed for easy consumption by
the greater process engineering community within the
organization.
If you are a modeling engineer (CFD, FEA, LBM, etc.) analyst
or the leader of a group of such engineers, this webinar is
a must-attend for you!
Attend this webinar to discover how modeling and simulation
can help you to make better business decisions, faster
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