Tech Briefs Magazine - April 2021 - 32

Communications
Building Big Data from Little Data
Edge computing, focused applications, and open connectivity let designers start with little
data on their digital transformation journey.
Emerson Machine Automation, St. Louis, Missouri

anufacturing facilities generate massive amounts of operational data
from their automated production equipment, condition monitoring devices, and
other sensors and systems. As companies
are becoming more aware of the potential
marooned in these assets, they are asking
how Industrial Internet of Things (IIoT)
initiatives can help tap into this information and create useful insights. But many
attempts to tackle this via enterprise-wide
mega-projects fail to meet expectations
because of the sheer size and complexity.
Perhaps a better approach is to begin with
" little " data at the source to build up to
big data using edge computing, focused
applications, and open connectivity.
Digital transformation is never a oneand-done task. But taking on a project that
is too big can quickly derail the efforts. Just
connecting the many different data producers can be hard, yet effectively transmitting, processing, and storing that data
- on premise or in the cloud - is an
equally massive undertaking. Therefore,
the most successful projects start from the
bottom up employing machine-level data
instead of from the top down at the enterprise level (Figure 1).
Focusing the field of view on specific
challenges and assets can deliver immediate returns compared with gathering all
possible data and trying to discover possibilities without a clear problem statement. Plant personnel can prioritize
insights that address everyday operational
issues and select the most relevant data
from existing or even new sensing points.
But that uncovers a new challenge: the
data of interest is usually not actively
being stored in the control system.
For instance, when experiencing excessive downtime with a new machine, not
collecting data means the operator cannot
find the root cause. Every action taken is
reactive to observations after the failure
occurs. Applying a little-data project, the
user can gather data from the control system along with new air pressure and vibration sensors. By collecting and analyzing
data in real time within the context of the

BIG DATA

LITTLE DATA

Figure 1. Complex big data projects can be daunting. Starting with little data is a practical approach to embarking on the digital transformation journey and delivering immediate value.

Figure 2. Edge controllers, like Emerson's PACSystems RX3i CPL410, are key for easily bridging OTsourced little data with IT-centric communications and processing capabilities.

machine, the operators can quickly find
the root cause and address the issues, leading to improved uptime.
Production data sources are generally
part of the operational technology (OT)
domain, which includes programmable
logic controllers (PLCs), motion devices,
and many types of sensors and instru-

www.techbriefs.com

Cov

ToC

ments. But communicating, storing, and
processing massive amounts of data
requires information technology (IT)
capabilities.
The key to bridging OT and IT- and
enabling personnel formerly on both
sides of this divide to work collaboratively - is found in a new generation of
Tech Briefs, April 2021

http://www.techbriefs.com http://www.abpi.net/ntbpdfclicks/l.php?202104TBNAV

Tech Briefs Magazine - April 2021

Table of Contents for the Digital Edition of Tech Briefs Magazine - April 2021