(90a) Real Time Plant Support with Focus on Enterprise Manufacturing Intelligence (EMI)

Dow, being one of the largest and long
standing startups (118 years old), accrued immense chemical production process
data. However, most of these data are underutilized and simply archived in
databases.  In order to extract the most
significant and immediate value from that data, process design knowledge and
operational experience can be used to summarize and aggregate plant data to
expose the most relevant information in the right context. The goal of
Enterprise Manufacturing Intelligence (EMI) is to make these high value
relevant data available in real time to all levels of production management
(Operations to Plant and Business Management).

Establishing new control
and monitoring protocols previously unattainable due to the manner in which
data systems were designed and data was stored prior to the age of “Big Data”.

Furthermore, with such
abundant availability of data, multivariate approaches such as chemometrics and
machine learning methods can be complimentary to existing process knowledge by
identifying new relationships previously “unknown”.  The EMI system is able to incorporate these
additional process insights to further increase the breadth and performance of
the monitoring framework.

Finally, to tie data
trends with known and documented science to bring faster context has
significantly improved the capabilities of data analytics. These improvements
transcended the traditional paradigm of univariate control charting and alarm
limits, and progresses towards the mastery of multivariate real-time data
monitoring that is aligned to the various needs at all levels of the production
facility.  A robust Enterprise system and
a growth strategy are the enablers of this transformation. These aspects outlined above will reinvigorate
an operational focus and create a systematic memory that is robust against significant
turnover in personnel and the loss of plant knowledge such turnover brings. At
Dow, we want the data to start working for us, rather than us having to work to
get the data.