Presenting my PhD thesis project at the MODEL2023 doctoral symposium (best doctoral symposium submission award)

1. Christian Doppler Laboratory for Model-Integrated Smart Production
Institute of Business Informatics – Software Engineering
Johannes Kepler University Linz
Altenberger Straße 69, Science Park 3
4040 Linz
Christian Doppler Laboratory for Model-Integrated Smart Production
CDL-MINT
A Model-Driven Platform for Engineering Holistic Digital Twins
Daniel Lehner

2. From Basic to Holistic Digital Twins
2
Digital
Twin (DT)

3. From Basic to Holistic Digital Twins
• Basic DT definition: Kritzinger [1]
• Existing DT platforms (Azure, AWS, …) support development of basic DTs
• How can we provide more functionality?
• Holistic DT: Basic DT + augment PT with additional functionality
3
[1] Kritzinger et al. "Digital Twin in manufacturing: A categorical literature review and classification." IFAC-PapersOnline 51.11 (2018): 1016-1022.
Simulation Platform
DT Platform
Automation Platform
communicates
communicates
communicates
Services
SC-based
Planner
AI-based
Planner
Time-based
Monitor
Event-based
Monitor
Simulation
Physical
Twin (PT)
Digital
Twin (DT)
communicates

4. Methodological Approach: Design Science [1]
4
[1] Wieringa, R. J. (2014). Design science methodology for information systems and software engineering. Springer.
(1) Problem investigation:
What are problems when engineering holistic DTs?
(2) Research Method
Use Cases
(4) Available Treatments
What are capabilities of current DT platforms?
What are existing MDE approaches for Digital Twins?
(5) Digital Twin Platforms
Method: Structured Review
(5) MDE4DT Approaches
Method: Systematic Mapping Study
(7) Requirements satifsfaction
Missing capabilities
• Reuse design time information
• Simulation support
• DT architecture integration support
(10) Validation
Comparing requirements satisfaction + required effort of
- New treatment
- Available treatments
(9) Prototype design and implementation
Contribution 1: Papers at ETFA 2021 and ECMFA 2022
Contribution 2: Paper at CASE and planned for T-ASE
Contribution 3: Paper planned for ECMFA 2024
(11) Research Method:
• Case Study
• Comparison Study
(8) New Treatment
DT++ Platform

5. Methodological Approach: Design Science [1]
5
[1] Wieringa, R. J. (2014). Design science methodology for information systems and software engineering. Springer.
(1) Problem investigation:
What are problems when engineering holistic DTs?
(2) Research Method
Use Cases
(4) Available Treatments
What are capabilities of current DT platforms?
What are existing MDE approaches for Digital Twins?
(5) Digital Twin Platforms
Method: Structured Review
(5) MDE4DT Approaches
Method: Systematic Mapping Study
(7) Requirements satifsfaction
Missing capabilities
• Reuse design time information
• Simulation support
• DT architecture integration support
(10) Validation
Comparing requirements satisfaction + required effort of
- New treatment
- Available treatments
(9) Prototype design and implementation
Contribution 1: Papers at ETFA 2021 and ECMFA 2022
Contribution 2: Paper at CASE and planned for T-ASE
Contribution 3: Paper planned for ECMFA 2024
(11) Research Method:
• Case Study
• Comparison Study
(8) New Treatment
DT++ Platform

6. Methodological Approach: Design Science [1]
6
[1] Wieringa, R. J. (2014). Design science methodology for information systems and software engineering. Springer.
(1) Problem investigation:
What are problems when engineering holistic DTs?
(2) Research Method
Use Cases
(4) Available Treatments
What are capabilities of current DT platforms?
What are existing MDE approaches for Digital Twins?
(5) Digital Twin Platforms
Method: Structured Review
(5) MDE4DT Approaches
Method: Systematic Mapping Study
(7) Requirements satifsfaction
Missing capabilities
• Reuse design time information
• Simulation support
• DT architecture integration support
(10) Validation
Comparing requirements satisfaction + required effort of
- New treatment
- Available treatments
(9) Prototype design and implementation
Contribution 1: Papers at ETFA 2021 and ECMFA 2022
Contribution 2: Paper at CASE and planned for T-ASE
Contribution 3: Paper planned for ECMFA 2024
(11) Research Method:
• Case Study
• Comparison Study
(8) New Treatment
DT++ Platform

7. Simulation Platform
DT Platform
Automation Platform
represents
represents
communicates
Problems in Engineering Holistic DTs
communicates communicates
7
Problem 1:
Redundant
specification
Problem 2: Manual
effort for connecting
services + simulations
Problem 3: Manual
effort for creating
architectures
Services
SC-based
Planner
AI-based
Planner
Time-based
Monitor
Event-based
Monitor
Simulation
Physical
Twin
Digital
Twin (DT)
DT Model
{twinType robot{
Attr posX, …
method gripItem(…)
…
Simulation Model
Engineering Model
Robot
posX: int
…
gripItem(…)
represents
communicates
Idle Moving
…
…

8. 8
Solution: DT++ Platform

9. DT++ Platform
Automation
Platform
reuses
represents
represents
communicates
DT Workflow Model
uses
Architecture of the DT++ Platform
communicates
Engineering
Model
Robot
posX: int
…
gripItem(…)
communicates
9
Contribution 1:
Reuse design
time information
Contribution 2:
Automate integration
PT + Simulation => DT
Contribution 3:
Automate integration
DT + services => DT
architectures
DT Mega-Model
DT Model Monitor Config Model
Simulation Endpoint Config
PT Endpoint Config
Services
Monitoring Template Planning Template
…
SC-based
Planner
AI-based
Planner
Time-based
Monitor
Event-based
Monitor
Simulation
Physical
Twin
Twin
Manager

10. Contribution 1: Reuse by Transformation
10
Engineering Model Digital Twin Model Digital Twin
transformation
UML
AutomationML
Azure DTDL
Eclipse Vortolang
AWS TwinMaker-MM
Azure DT Service
Eclipse Ditto
AWS TwinMaker
Pfeiffer, J., Lehner, D., Wortmann, A., & Wimmer, M. (2022). Modeling capabilities of digital twin platforms-old wine in new
bottles?. J. Object Technol, 21(3), 3.
{
„twinTypes“: [{
„name“: „Robot“
„attributes“: [ … ],
„methods“: [ … ],
„relations“: [ … ]
],
twins: [
{„name“: „robot1“, „type“: „Robot“},
{„name“: „robot2“, „type“: „Robot“},
{„name“: „robot3“, „type“: „Robot“},
]
}
Robot
posX: int
…
gripItem(…)
robot3
robot2
robot1
configuration
robot1: Robot
robot2: Robot robot3: Robot
conformsTo
conformsTo
conformsTo

11. Contribution 1: Solution Approach
11
Pfeiffer, J., Lehner, D., Wortmann, A., & Wimmer, M. (2022). Modeling capabilities of digital twin platforms-old wine in new
bottles?. J. Object Technol, 21(3), 3.
Profile DTUML
«Stereotype»
DTProperty
Boolean isTimeSeries
String unit
String type
«Stereotype»
AWS_Property
Boolean isExternalId
Boolean isStoredLocally
List<String> allowedValues
String quantity
«Stereotype»
VortoLang_Property
Boolean isFault
String constraintRule
«Stereotype»
DTDL_Property
«Metaclass»
Property
Class type
Int lower
Int upper
Boolean readOnly
Property redefinedProperty
Value defaultValue
rule class2interface {
from
cl: UML!Class
to
interf: DTDL!Interface ()
do{
interf.displayName <- cl.name;
if(cl.ownedComment.notEmpty()){
interf.comment <- cl.ownedComment.first().body;
}
interf.contents <- Set{};
-- Create Commands
for(op in cl.ownedOperation) {
interf.contents <- interf.contents->including(thisModule.newCommand(op));
}
-- Create Components
-- …
-- Create Properties, Telemetries, Relationships and Components
-- …
}
}
}
UML profile for missing concepts ATL transformation for reuse

12. DT++ Platform
Automation
Platform
reuses
represents
represents
communicates
DT Workflow Model
uses
Architecture of the DT++ Platform
communicates
Engineering
Model
Robot
posX: int
…
gripItem(…)
communicates
12
Contribution 1:
Reuse design
time information
Contribution 2:
Automate integration
PT + Simulation => DT
Contribution 3:
Automate integration
DT + services => DT
architectures
DT Mega-Model
DT Model Monitor Config Model
Simulation Endpoint Config
PT Endpoint Config
Services
Monitoring Template Planning Template
…
SC-based
Planner
AI-based
Planner
Time-based
Monitor
Event-based
Monitor
Simulation
Physical
Twin
Twin
Manager

13. Contribution 2.1: Endpoints
13
Lehner, D., Gil, S., Mikkelsen, P., Larsen, P. & Wimmer, M. (2023). An Architectural Extension for Digital Twin Platforms to Leverage Behavioral Models, Proc.
of CASE.
<<abstract>>
Endpoint
Physical
Twin
Simulation
getAttributeValue(...): Object
executeOperation(...): void

14. DT Mega-Model
Contribution 2.2: TwinManager
14
Lehner, D., Gil, S., Mikkelsen, P., Larsen, P. & Wimmer, M. (2023). An Architectural Extension for Digital Twin Platforms to Leverage Behavioral Models, Proc.
of CASE.
Services Monitoring Template Planning Template
…
SC-based
Planner
AI-based
Planner
Time-based
Monitor
Event-based
Monitor
TwinManager
create/read/updateEndpoint(…)
executeOperation(List<Endpoint>, Time, …)
…
<<abstract>>
Endpoint
Physical
Twin
getAttributeValue(...): Object
executeOperation(...): void
communicates
communicates
Simulation
uses

15. Endpoint Config Model
WeBotEndpoint wbEndpoint implementing Robot at 137.654.1
gripAt(x, y, z) at /grip
data: current_x:curX, current_y:curY, current_z:curZ
Endpoint Config Model
ROSEndpoint rosEndpoint implementing Robot at 137.654.2
gripAt(x, y, z) at /grip
data: x:curX, y:curY, z:curZ
Service Config Model
Service Monitor at 127.0.0.1
in: monitorForDeviation(actual, simulation, curX), out: Deviation: bool
implements
implements
DT Mega-Model
twin niryoRobot: Robot
twins: actual at rosEndpoint, simulation at wbEndpoint
services: Monitor checkPosX
DT Model
Type Robot
int curX, curY, curZ
int targetX, targetY, targetZ
int torque
moveGripperTo(x, y, z)
gripAt(x, y, z)
placeAt(x, y, z)
uses
Contribution 2.3: DT Mega-Model
15

16. DT++ Platform
Automation
Platform
reuses
represents
represents
communicates
DT Workflow Model
uses
Architecture of the DT++ Platform
communicates
Engineering
Model
Robot
posX: int
…
gripItem(…)
communicates
16
Contribution 1:
Reuse design
time information
Contribution 2:
Automate integration
PT + Simulation => DT
Contribution 3:
Automate integration
DT + services => DT
architectures
DT Mega-Model
DT Model Monitor Config Model
Simulation Endpoint Config
PT Endpoint Config
Services
Monitoring Template Planning Template
…
SC-based
Planner
AI-based
Planner
Time-based
Monitor
Event-based
Monitor
Simulation
Physical
Twin
Twin
Manager

17. Contribution 3.1: DT Module Templates
17
Monitoring Template
Monitor
Monitor Config
Language
Event-based Monitor Module
Event-based
Monitor
Event
Monitoring
Language
LC
SC
LC
SC
Idea 1: Wrap software and language components into common DT modules
• Use MDE techniques to automate integration of different components
Idea 2: Provide templates of DT modules for reusability
• Integration is lifted on the reference architecture level

18. Contribution 3.2: DT Workflow Language
• Extends structural information of DT Mega-Model
• Describes interactions between serivces and DTs
18
DT Workflow Language
monitorForDeviation (actual, simulation, param):
every 10 seconds:
def = actual.getAttributeValue(param) –
simulation.getAttributeValue(param)
response def <= 1
Endpoint Model
Endpoint Model
Service Config Model
DT Mega-Model
DT Model
uses

19. 19
Evaluation: DT++ vs. existing DT platforms

20. Evaluation Plan: Case Study [1] (1/2)
Research Questions
▪ RQ1: Reuse of engineering models in DT++ Platform? (Contribution 1)
▪ RQ2: Effort of service connection in DT++ Platform? (Contribution 2)
▪ RQ3: Effort of architecture integration using DT++ Platform? (Contribution 3)
Considered Cases
20
Runeson, P., & Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering, 14,
131-164.
Air Quality
Measurement
Stack Balancing Incubator Temperature
Managmeent
Smart Room
1
7
3
Stack
1
Stack
2
Stack
3

21. Initial Evaluation Results
21
RQ1 (Reuse potential) [1]
▪ Some adaptations required to existing languages
▪ Transformation reduces effort for setup + evolution by 50 %
RQ2 (Effort of service connection) [2]
▪ Effort for connecting services to different endpoints reduced by > 50 %
▪ Effort for switching the underlying DT of a service reduced by ~40 %
RQ3 (Effort of architecture integration)
▪ Increased scalability for integrating similar
services into a high number of different architectures
▪ Higher initial effort than baseline approaches
[1] Lehner, D., Sint, S., Vierhauser, M., Narzt, W., & Wimmer, M. (2021, September). AML4DT: a model-driven framework for developing and maintaining digital twins with
AutomationML. In 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1-8). IEEE.
[2] Pfeiffer, J., Lehner, D., Wortmann, A., & Wimmer, M. (2022). Modeling capabilities of digital twin platforms-old wine in new bottles?. J. Object Technol, 21(3), 3.
Effort 50 %
Effort 40-50 %
Initial Effort
Scalability

22. Current State + Ongoing Work
Problem Investigation + Existing Solutions
▪ DT Airquality Exemplar (MODDIT‘21)
▪ Reactive Planning using DTs (ISOLA‘22)
▪ Investigation of existing platforms (IEEE Software‘22)
▪ Systematic Mapping Study submitted to SOSYM
Solution + Validation
▪ Design of reuse mechanism (ETFA’21 and ECMFA‘22)
▪ Design of TwinManager (CASE‘23)
Ongoing Work
▪ Publication of Integration Method + DT Workflow Language (RQ3)
▪ Extension of existing evaluations to further use cases for generalizability
22

23. Conclusion + Potential Societal Impact
23
[1] Heithoff, M., Hellwig, A., Michael, J., & Rumpe, B. (2023). Digital twins for sustainable software systems. In Proc. of GREENS
Problems in Engineering holistic DTs
1. Redundancy
2. High effort for integrating components
Contributions of the DT++ Platform
1. Reuse
2. Automation
Potential impact on society
• Increased DT adoption enables innvoation
• Sustainable product development [1]
• Optimized use of human workforce

24. CDL-MINT
https://cdl-mint.se.jku.at/
Christian Doppler Laboratory for Model-Integrated Smart Production
CDL-MINT
Thank You!
Comments? Questions? Feedback?
Daniel Lehner
daniel.lehner@jku.at
http://github.com/derlehner

25. Evaluation Plan: Case Study [1] (2/2)
Metrics
25
Runeson, P., & Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering, 14,
131-164.
Endpoint Model
WeBotEndpoint wbEndpoint implementing Robot at 137.654.1
gripAt(x, y, z) at /grip
data: current_x:curX, current_y:curY, current_z:curZ
1
2
3
Lines of Code
Twin Manager
Monitoring Template
# Operation Calls getAttributeValue(…)
TOD
O
metri
k für
jede
RQ

26. Conclusion + Potential Societal Impact
▪ Engineering holistic DTs is cumbersome and error-prone
▪ DT++ platform helps reduce this effort by
▪ Reusing existing design time information
▪ Automating the integration of PT and simulations into a holistic DT
▪ Automating the integration of DTs and services into DT architectures
26
TODO: Impact on Society
- Hoher Aufwand = weniger
Innovation möglich
- Weniger DTs = Potenziale bzgl.
Digitalisierung und CO2-
Messung weniger nutzbar
TODO: Too much text:
vllt Gegenüberstellung
Current State + DT++ mit
Problems + Contrubionts
darunter?
TODO: hier Referenz von
Keynote Judith reingeben

27. Contribution 3.1: A template-based method for DT architecture integration
27
Digital Twin
Planner DTPlatform
DT Product Line
Planner
DT Platform
Azure
Timed
Statecharts
Basic
Statecharts
AWS IoT
A
DTPlatform: Azure
Planner: Basic Statecharts
Azure
Basic
Statecharts
DTDL
Model
uses
SC
Models
uses
E
Phase 3: Architecture/Product Line Configuration
DT module
DTPlatform.data ->
Planner.data
…
Azure DT
SC Model
Execution Engine
DT service
data cmd
data
Timed
Statecharts
B
Basic
Statecharts
plan
Phase 2: Reference Architecture Definition
Planner
DT Platform
DTPlatform: …
Azure:
Azure.state -> DTPlatform.data
…
Phase 4: DT Architecture Generation
uses uses
generate
state
data
Azure
AWS IoT
D
uses
uses
DT module
wrapper
Connects DT templates
DT module and
template definition
model
Product Line
configuration
Reference architecture
definition model
DTPlatform Planner
DT template
bridge
C
F
G E
A
B B B
Phase 1: Component Definition
DT template
G
E
E
current

28. Holistic Digital Twins (DTs)
Holistic DT: provide functionality based on interactions with PT + simulation
- common functionality: anomaly detection, virtual experimentation, planing, …
Thesis goal
• reduce the effort for engineering holistic DTs
• by employing MDE techniques
• in order to make it easier for academics to adopt DTs
28
Holistic DT
- interactions with PT + simulation
- provide functionality
- anomaly detection
- virtual experimentation
- planning
Physical
Twin
Digital Twin
communicates

29. Evaluation Plan: Case Study [1]
Research Questions
▪ RQ1: Reuse potential (Contribution 1)
▪ RQ2: Effort of service connection (Contribution 2)
▪ RQ3: Effort of architecture integration (Contribution 3)
Cases
▪ Smart Room, incl. Air Quality Measurement
▪ Reactive Planning for Stack Balancing
▪ Incubator DT
Metrics
Count number of…
▪ … High-level operations
▪ … Change operations
▪ … Lines of Code
required to perform predefined scenarios
29
Runeson, P., & Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering, 14,
131-164.

30. Automation
Platform
DT++ Platform
reuses
DT Mega-Model
represents describes
Monitoring Service
represents
DT Model Monitor Config Model
Simulation Endpoint
Configuration
communi
cates
PT Endpoint
Configuration
uses
Twin Manager
Contribution 2.1: Architectural Extensions of existing DT Platforms
Lehner, D., Gil, S., Mikkelsen, P., Larsen, P. & Wimmer, M. (2023). An Architectural Extension for Digital Twin Platforms to Leverage Behavioral Models, Proc.
of CASE.
Digital Twin
Physical
Twin
Simulation
communicates
Robot
posX: int
…
gripItem(…)
Engineering Model
communi
cates
Contribution 2.1: Endpoints
Abstraction of PT + Simulations
Contribution 2.2: TwinManager
Interface to PT + Simulations
Contribution 2.3: DT Mega-Model
Single source of configuration
30

31. Evaluation Plan: Case Study [1]
Research Questions
▪ RQ1: Reuse potential of DT++ Platform compared to existing platforms? (Contribution 1)
▪ RQ2: Effort of service connection in DT++ Platform, compared to existing platforms? (Contribution 2)
▪ RQ3: Effort of architecture integration using DT++ Platform, compared to existing platforms? (Contribution 3)
Cases
▪ Smart Room
▪ Air Quality Measurement
▪ Reactive Planning for Stack Balancing
▪ Heatbed Incubator
Metrics
Count number of…
▪ … High-level operations
▪ … Change operations
▪ … Lines of Code
required to perform predefined scenarios
31
Runeson, P., & Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering, 14,
131-164.