Digital Twin in Industrial Application – Requirements to a Comprehensive Data Model
As mentioned above, data can appear in dif-
ferent protocols. Another aspect of connec-
tivity parameters therefore relates to the
definition of these protocols and the formats
to be interpreted in the IIoT system.
suppliers may not work with the same soft-
ware.
Therefore, one initial requirement for main-
taining digital twin model data is the ability
to consolidate partial models from different
parts of the supply chain into a single model
that is associated with the final asset.
M AINTAINING A D IGITAL T WIN D ATA
M ODEL
Maintenance and extensions
The major challenge associated with all the
references and meta-descriptions men-
tioned in Section 4 relates to how to gener-
ate them and keep them up to date. The fol-
lowing requirements apply to the mainte-
nance process:
While the tasks described above are already
complex, the main challenge actually arises
during operation over the lifecycle of the as-
set. Maintenance and refurbishment can
substantively change the way an asset be-
haves, and new or replacement components
will be installed in it—including from suppli-
ers that were not part of the original OEM
supply chain. Third party maintenance pro-
viders may modify assets without reference
to the OEM if they possess corresponding
service-level agreements with the operating
company.
Consolidation
As we have seen in the use cases (Section 3),
a digital twin may relate to a product con-
taining components that originate from mul-
tiple sources. Industrial products typically
consist of a number of third party compo-
nents assembled in deep supply chains with
tier-1, tier-2 or other suppliers. To make it
possible to create a digital twin of a final
product, these sources have to be connected
and consolidated into a common model to
reflect the complete, fully updated as-deliv-
ered-state.
This leads to the obligation on the part of the
owner or operator of the asset to keep the
digital twin up-to-date so that it describes
the asset's as-maintained-state.
A second requirement for digital twin mod-
els therefore refers to the possibility of
maintaining and extending them—even if
the operator is not part of the manufacturing
supply chain. This also includes the friction-
less handover of the digital twin data from
the manufacturing process to the operating
process owner.
Hence, the concerns and challenges involved
in keeping the digital twin up to date also ap-
ply to the OEMs in the supply chain. The
OEM will require up-to-date twin descrip-
tions of all the components in a way that per-
mits the (automated) compiling of partial
models from the different suppliers in the
supply chain (or a number of pre-consoli-
dated models from the tier-1 suppliers). It is
clear that models have to be interoperable
across system boundaries since OEMs and
Granularity
The task of consolidating and maintaining a
digital twin’s data during operation raises
the question of the level of detail the partial
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November 2019