Efficient Plant Jan./Feb. 2024 - 9

feature | data management
manufacturing teams
streamlining communication and handoff
s between shiſt s
optimizing resource utilization and
effi ciency
maximizing quality
minimizing waste.
While specifi c objectives will vary by
industry and project, they should be defi ned
in as much detail as practical. Th e best way
to know if objectives are being met is to
quantify the results using KPIs such as:
Lower the response/solution time when
certain production problems arise by a given
percentage.
Increase productivity by a given
percentage.
Reduce scrap by a given percentage.
Identify and eliminate wasteful air leaks.
To support these objectives, identify a
digital platform capable of:
performing real-time data collection from
a variety of sources
incorporating common and custom lean
production and energy-effi ciency analytics
delivering clear operational and informational/performance
visibility using HMI and
SCADA soſt ware, with convenient and secure
access for local and remote/cloud users
integrating with Power BI dashboards and
other IT resources to provide enterprise-wide
perspectives.
A complete solution must address the
entire journey of data from the plant fl oor
to the cloud, providing value as manufacturers
meet their objectives, and then prove
results with KPI metrics.
DATA INTO ACTION
Emerson's factory in Lodz, Poland, which
manufactures Asco valves, is just one of
many sites where the company has implemented
their own solutions to improve their
product manufacturing. Much like any other
manufacturing enterprise, the organization
wanted to collect and record data from
JAN/FEB 2024
Convenient access to quality data is necessary so users can fully evaluate their operations. In this
case, OEE can be examined over the past month, past year, and by shift. Courtesy Emerson
operating assets, visualize real-time and
analyzed conditions, and determine overall
equipment eff ectiveness (OEE), along with
other KPIs associated with effi ciency and
performance. Th e solution would need to
connect with a variety of machines and it
had to be scalable so they could start in a
few operational areas, then expand to all
operating assets and be able to grow as new
machines were put into service.
Th e factory produces pneumatic automation
and monitoring components, and
the internal IIoT solutions team had several
goals to help the facility gain insights and
improve operation:
Calculate OEE and measure downtime to
understand production capacities and drive
effi ciency.
Track product test results and analyze
them to determine good-versus-scrap output.
Monitor and evaluate energy and air
consumption.
Enable extended reporting so staff could
investigate other areas of interest.
Based on the needs and requirements,
the team implemented Emerson Movicon.
NExT HMI/SCADA soſt ware for real-time
data collection and visualization, combined
with the Pro.Lean module to provide the
desired analytics and reporting capabilities.
Th e HMI/SCADA soſt ware includes
provisions to communicate with almost
any type of operational asset, storing the
data in a historian and logging it to an SQL
database for more extensive evaluation. Th e
cloud-based architecture for energy- and
air-consumption monitoring uses timeseries
databases to eff ectively manage the
otherwise overwhelming data using carefully
applied compression techniques.
In this case, live data streams into the
database and is maintained at full accuracy-typically
a sample rate from 100 msec.
to 5 sec.-for 30 days. Th e database can
compress this data at a 1:25 factor. Aſt er 30
days, the data undergoes further compression
to around a 1-hr. sample rate (by
keeping minimum, maximum, and mean),
yielding an additional compression factor of
1:1,200. Th e resultant overall data reduction
is about 1:30,000, which makes it practical
to store many years of data.
While some users might think about
creating their own analytics from scratch,
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Efficient Plant Jan./Feb. 2024

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