Chemical Engineering October 2019 - 40

Cover Story
Advanced Analytics:
Accelerating Insights
for Engineers
Michael Risse
Seeq Corporation
E
IN BRIEF
IMPROVED SOLUTIONS
FOR ANALYZING DATA
A TAXONOMY FOR
ANALYTICS
APPLICATIONS
THE ANALYTICS
ADVANTAGE
very day,
the chemical
process
industries
Data rich...
Information poor
(CPI) produce data
at an unprecedented
rate, including
historian-based
process data, and
business and manufacturing
system
contextual data.
Plants can generate
terabytes of sensor
data per day, and
companies can generate
scores of terabytes of data per day.
With the rise of sensors and other equipment
connected via the industrial internet
of things (IIoT), these data volumes are expanding
exponentially.
And, the problem of too much data and too
little insight will only accelerate as IIoT takes
hold. IIoT forecasts correlate to the amount
of data generated, and the International Data
Corporation (IDC) is expecting worldwide
spending on IoT to reach $745 billion this
year, led by the manufacturing sectors [1].
That represents a massive increase in sensor
data. Despite the hype around " smart " sensors,
the data will go to waste absent robust
analytics to enable insights.
Data in process historians,
manufacturing & IT systems
In fact, " data rich, information poor "
(DRIP), threatens to drown organizations in
a sea of underutilized data (Figure 1), driving
a search for new solutions. For the last 30
years, spreadsheets were the analysis tool
of choice in process manufacturing, but this
general-purpose tool is no longer sufficient
40
Manual analysis in
spreadsheets
Part 2
The surge in data volumes within the chemical process industries has made it difficult for
engineers to find the insights they need to improve processes. Advanced analytics applications
enable engineers and others to harness the data for improved operations
Long time to insight
Inflexible static reports
FIGURE 1. Many CPI plants and facilities are data rich, but information poor, driving the need
for new advanced analytics solutions
for complex analysis of the expanding volumes
of time-series data.
At all levels of the manufacturing enterprise,
from operators to engineers to field staff to
quality control, and up to the executives, everyone
needs useful insights for daily decision-making.
And they need self-service access
to data without the need for assistance
from information technology (IT) experts and
data scientists. Fortunately, a solution is at
hand in the form of advanced analytics.
Improved solutions for analyzing data
A new class of analytics applications leverages
new technologies, including big data
and machine learning (ML) innovations, to
accelerate engineers' time to insights. Advanced
analytics applications cover the crucial
" last mile " between data and insights,
enabling employees in many different roles to
do their own analysis and share their findings
in the moment, without the required intervention
of a data scientist or other IT expert.
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OCTOBER 2019

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Chemical Engineering October 2019

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