Chemical Engineering August 2021 - 27

and asset data. Using this self-service,
advanced-analytics solution
supports improving an organization's
key performance indicators
(KPIs), while also reducing costs.
Classic model-based analytics require
data-science expertise and
can often be time consuming. Enabling
more users to access advanced
analytics decreases " timeto-insight. "
This democratization
of analytics supports people with
a deep understanding of the process
to improve the performance
of the plant. The platform analyzes
both time-series data and contextual
data. Users can find relevant
data, identify trends and create
actionable information to solve
production issues. They can also
troubleshoot problems and monitor
processes and assets in real-time
to make better decisions, faster. -
TrendMiner US, Houston
www.trendminer.com
Smart predictive analytics for
heat-transfer-fl uid maintenance
Fluid Genius is a new predictive
analytics tool for heat-transfer-fluid
(HTF) life expectancy that uses
AI
algorithms built around HTF
sample analysis data. The tool is
designed to provide recommendations
for extending fluid life and
maintaining HTF systems. Fluid
Genius generates a fluid condition
score, a unique measure of
the overall fluid condition, as well
as notifications about fluid trends
and customized recommendations
for proactive maintenance
actions. These could include system
venting, inert-gas blanket
system installation and inspection,
fluid replacement, the implementation
of side-stream filtration
and alerts
for possible contamination.
- Eastman Chemical Co.,
Kingsport, Tenn.
www.eastman.com
Cloud-based APM merges
modeling and analytics
The Forge Asset Performance
Management (APM) platform goes
beyond traditional machine monitoring
and data gathering by merging
machine modeling with modern
cloud analytics.
Digital twins
developed in this platform predict
machinery availability, drill to the
root cause of inefficient machine
operation and bring order to reliability
and maintenance planning.
Forge APM deploys rapidly through
a variety of standard asset libraries
and tools to integrate data sources
quickly. To achieve peak asset performance
and maximize machinery
uptime, Forge APM supports
greater enterprise asset manageFLOW
OPTIMIZATION
SECOND TO NONE
ment, even where pre-existing
monitoring systems are already installed.
- Honeywell International
Inc., Charlotte, N.C.
www.honeywell.com
Explainable machine learning
for manufacturing optimization
This company's software platform
aims to make manufacturing
more efficient through explainable
machine learning. With this easyto-use
software, factory personnel
can optimize production and
address root causes of quality issues,
with no data-science experience
required. Once deployed,
models offer real-time optimization
suggestions that constantly
learn from the
latest
production
data. Visual dashboards allow results
to be shared with operations
teams, so models can be scaled
to other plants within weeks. A
highlight of this solution is the ability
to virtually replicate multi-stage
batch processes in the software.
With this functionality, users can
model complex interactions between
stages of batch processes
with a high degree of accuracy,
providing key data for decision-making.
- Fero Labs,
New York, N.Y.
www.ferolabs.com
■
Mary Page Bailey
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Chemical Engineering August 2021

Table of Contents for the Digital Edition of Chemical Engineering August 2021