Digital Twin in Industrial Application – Requirements to a Comprehensive Data Model
requires sophisticated condition monitoring
and maintenance control.
The manufacturer offers a full range of ser-
vices from the design and manufacturing of
the equipment through to its installation,
maintenance and system overhauls. In most
cases, tasks are divided, with the manufac-
turer and customer working together to
commission the system while standard-
maintenance and small extensions are per-
formed by the customer, and more exten-
sive or complex modifications are under-
taken by the manufacturer.
As these vehicles are provided by different
suppliers, there is no common fleet-wide
monitoring logic or even any common moni-
toring mechanism, and the logistics supplier
has had to implement fleet control on its
own. Of course, weather conditions play a
significant role here. The objective of such a
fleet control system is to monitor the differ-
ent (groups of) vehicles and consolidate the
data for the joint reporting of general readi-
ness information. Furthermore, a predictive
maintenance system based on historical
data from the vehicles' internal control sys-
tems is intended to proactively trigger
measures to prevent malfunctions and
breakdowns. Automated spare parts provi-
sion might be the next logical step.
At this point, a potential conflict arises when
the customer makes changes to the system
without informing the manufacturer and
then subsequently requests a modification
or complains about a system failure. The first
challenge then facing the manufacturer is to
identify the up-to-date as-maintained state
of the system in order to have a reliable
baseline for any further activity.
This case gives rise to the following IIoT re-
quirements:
The key abilities required of an IIoT system in
this context are to:
Consolidate key measures of system
behavior from different suppliers/as-
sets
Consider environmental influences
Define limit values for parameters
and related measures
Provide spare parts orders
Case 3: Maintenance and modification
of assets
The third case involves a manufacturer of
large-scale plant systems for handling food
products. Based on customer requirements,
the manufacturer combines a number of
modules and functional units to create an in-
tegrated system (configure-to-order). This
system is then interlinked with the custom-
er's production environment.
Track control parameters (pressure,
speed, etc.)
Describe the as-maintained-state in
terms of the components and assem-
bly situation
Integrate a description of third party
components (modifications by cus-
tomer)
Describe the interaction with other
surrounding production assets
Case 4: Monitoring of overall systems
and predictive maintenance
The fourth case relates to train operation.
Since trains are operated for many hours
every day, often in tough environments, the
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