IDM ¦ Technology/IT
for participating production companies.
After identifying all physical components
of the production line with
direct product-contact, the relevant
valves, pumps, controllers, and sensors
in these parts are determined. Figure 2
illustrates how stakeholders share data
via MindSphere for specific use cases.
Figure 3 schematically illustrates interconnections
of individual digital twins,
company-wide or with a specific view
to pudding production in a dairy.
What other possibilities
does the DTM offer?
Data from management, administration,
and planning services, e.g. personnel
Figure 3: Connection of individual digital twins within the considered value chain.
24 · May 2020 ¦ international-dairy.com
and resource planning, can also be synchronized
with data from digital twins or
made accessible for subsequent analysis
purposes 4, 5. New cross-connections
and patterns can be recognized by using
methods of artificial intelligence or
machine learning. By networking with
these higher architectural levels and
such new evaluation possibilities, estimates
of product quality or machine service
lifetime can be made in real time.
A particular advantage is the predictive
analysis of future events. For example,
anomalies in devices or machines can be
forecasted and counteracted in order to
avoid undesired defects, minimize downtimes
and reduce production losses. Due
to their data density and structure, these
systems are able to generate their own
expert knowledge and thus can detect
anomalies independently. This high degree
of networking beyond a company's
own production boundaries enables
evaluation across the entire value chain.
DTM and data integrity
Within the DTM system, data security,
accountability, and transparency are
ensured. If data leaves the DTM system,
additional security is required. Therefore,
the International Data Space (IDS)
developed by the Fraunhofer Gesellschaft
6 was utilized, namely for communication
with the Digital Food Passport.
The Digital Food Passport is an
app, which provides selected food safety
data to consumers and authorities.
The IDS is a virtual data space leveraging
existing standards and technologies
to facilitate secure and standardized
data exchange and data linkage in a
trusted business ecosystem. It thereby
provides a basis for facilitating innovative
cross-company business processes,
while at the same time guaranteeing
data sovereignty for data owners.
Conclusion and outlook
The integration of digital twins always
requires a detailed analysis of the existing
production process with production
plans, SCADA plans and other information
from the ERP system. For existing
plants, it may be necessary to integrate
new measuring points into the process.
However, the depth of data collection
is not limited. Basic data, such
as temperatures, times, conductance
values, filling levels, etc. should always
be integrated. More detailed representations
of individual data correlations
are possible at any time, but even more
macroscopic observations can provide
important information, e.g. on process
efficiency. Here, it makes sense to create
a so-called Big Picture for existing
production processes. This Big Picture
reflects the physical production process
and also maps data streams, production
responsibilities, and stakeholders.
The amount of data is also helping to
execute root cause analyses for the
identification of problematic deviations
in the production process. This contributes
to the prediction of problematic
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