relevant activities/work units and even the work centers were identified following
ISA-88. Organic supply chains have strong linkages and communication between
the process participants and the majority of the steps are manual. Moreover, the data
is complex, and the processes involve various communicating partners. Therefore,
detailed UML models are used in the OSC project and structured according to
ISA-88 hierarchies.
7.3 Shared Digital Twins
The Fraunhofer cluster of excellence “Cluster of Cognitive Internet Technologies
(CCIT)” [85] studies cognitive technologies for the industrial internet. Researchers
from multiple disciplines are developing key technologies for various levels along
the value chain, from sensors and intelligent learning methods for data processing up
to cloud technologies. Its Forschungszentrum Data Spaces (FDS) focuses on concepts and technologies for sovereign industrial data exchange based on the IDS. An
integral aspect of the FDS is the cross-institutional cooperation between numerous
Fraunhofer Institutes collaborating on projects. One of these projects relates to the
integration of IDS Connectors and AAS and, accordingly, with the combination of
the information models and the security concepts of both approaches. It aims to
develop a shared DT based on the current and future standards for interoperability
and data sovereignty.
RIOTANA
® (Realtime IoT Analytics) is a domain-independent IoT architecture
and DT that processes raw sensor data into key process indicators (KPIs) in realtime, developed by Fraunhofer ISST [86]. It consists of sensor modules attached to
arbitrary assets (e.g., forklifts), which transmit their data via Message Queuing
Telemetry Transport (MQTT) to a backend, which can combine the sensor values
and calculate KPIs. The combination of a proprietary DT such as RIOTANA
® with
IDS and AAS leads to a shared DT complying with the corresponding standards. The
data can be accessed by multiple participants in the ecosystem, while the data owner
retains full control over the data. The owner can define who can access and use the
data and for what purposes the data can be used. By using IDS, its usage control
mechanisms can be applied.
Figure 14 shows the architecture of the combination: on the right panel, as sample
assets, three forklifts f1–f3 are shown with attached RIOTANA
® sensor modules,
which transmit their values to the RIOTANA
® DT. The latter is now an IDS data app
in a service container and used to implement the standard AAS-REST-API, which
also is an IDS data app acting as the AAS wrapper for RIOTANA
® . In this case
study, there is a composite forklift fleet asset with co-managed forklift assets.
The combination of AAS and IDS results in an architecture that requires the
mapping of the data models and security concepts: IDS messages contain
AAS-compliant data with references to IDS resources. The AAS-ABAC security
concept is combined with IDS contracts, which protect those resources. The
submodels of the AAS are protected by both mechanisms and may be subject to
158
R. Werner et al.
ISA-88. Organic supply chains have strong linkages and communication between
the process participants and the majority of the steps are manual. Moreover, the data
is complex, and the processes involve various communicating partners. Therefore,
detailed UML models are used in the OSC project and structured according to
ISA-88 hierarchies.
7.3 Shared Digital Twins
The Fraunhofer cluster of excellence “Cluster of Cognitive Internet Technologies
(CCIT)” [85] studies cognitive technologies for the industrial internet. Researchers
from multiple disciplines are developing key technologies for various levels along
the value chain, from sensors and intelligent learning methods for data processing up
to cloud technologies. Its Forschungszentrum Data Spaces (FDS) focuses on concepts and technologies for sovereign industrial data exchange based on the IDS. An
integral aspect of the FDS is the cross-institutional cooperation between numerous
Fraunhofer Institutes collaborating on projects. One of these projects relates to the
integration of IDS Connectors and AAS and, accordingly, with the combination of
the information models and the security concepts of both approaches. It aims to
develop a shared DT based on the current and future standards for interoperability
and data sovereignty.
RIOTANA
® (Realtime IoT Analytics) is a domain-independent IoT architecture
and DT that processes raw sensor data into key process indicators (KPIs) in realtime, developed by Fraunhofer ISST [86]. It consists of sensor modules attached to
arbitrary assets (e.g., forklifts), which transmit their data via Message Queuing
Telemetry Transport (MQTT) to a backend, which can combine the sensor values
and calculate KPIs. The combination of a proprietary DT such as RIOTANA
® with
IDS and AAS leads to a shared DT complying with the corresponding standards. The
data can be accessed by multiple participants in the ecosystem, while the data owner
retains full control over the data. The owner can define who can access and use the
data and for what purposes the data can be used. By using IDS, its usage control
mechanisms can be applied.
Figure 14 shows the architecture of the combination: on the right panel, as sample
assets, three forklifts f1–f3 are shown with attached RIOTANA
® sensor modules,
which transmit their values to the RIOTANA
® DT. The latter is now an IDS data app
in a service container and used to implement the standard AAS-REST-API, which
also is an IDS data app acting as the AAS wrapper for RIOTANA
® . In this case
study, there is a composite forklift fleet asset with co-managed forklift assets.
The combination of AAS and IDS results in an architecture that requires the
mapping of the data models and security concepts: IDS messages contain
AAS-compliant data with references to IDS resources. The AAS-ABAC security
concept is combined with IDS contracts, which protect those resources. The
submodels of the AAS are protected by both mechanisms and may be subject to
158
R. Werner et al.