=Paper=
{{Paper
|id=Vol-2074/article_2
|storemode=property
|title=Representing Processes of Human Robot Collaboration
|pdfUrl=https://ceur-ws.org/Vol-2074/article_2.pdf
|volume=Vol-2074
|authors=Georg Weichhart
}}
==Representing Processes of Human Robot Collaboration==
https://ceur-ws.org/Vol-2074/article_2.pdf
Representing Processes of Human Robot
Collaboration
Georg Weichhart
1
PROFACTOR GmbH Georg.Weichhart@profactor.at
2
Pro2Future GmbH Georg.Weichhart@pro2future.at
Abstract S-BPM supports the representation of processes using two
levels: the individual subject behaviour level and the subject interaction
level. These two levels are helpful when it becomes necessary to spe-
cify the individual subject’s behaviour in di↵erent levels of details. We
take a system-of-systems point of view and take a S-BPM specific look
on interoperability. We use human-robot collaboration as a motivation
and use-case to understand the interoperability requirements of adapt-
ive system-of-systems. However, every type of human robot collaboration
has di↵erent requirements not only for subject behaviour but also for the
interaction level. We present the challenges and advantages of using S-
BPM in this setting.
Keywords: Business Process Modelling, Subject-oriented Business Process Mod-
elling, Human Robot Collaboration
1 Introduction
Increased competition is pushing enterprises to become sustainable in economic,
environmental and social dimensions. To reach this goal, enterprises must be-
come true smart adaptive systems for being able to react rapidly and flexibly to
changing environments. This involves the human system of enterprises as well
as the technical. Networked Mobile devices, social networks and edge devices
produce great amounts of data. Smart decisions are required to make use of
that large amount of information. Next generation information systems need to
support the S3 -Enterprise — Sensing, Smart and Sustainable Enterprise which
is a system of system where human and artificial systems collaborate [1].
Human Robot collaboration is one area which shows the high potential of
the S3 Enterprise. Sensors are required for understanding the user’s position
and activities. The robot is controlled by smart algorithms. For becoming sus-
tainable the collaboration needs to be adaptive, reacting to changing products,
production processes and customer demands. Since the human and the artificial
system are independent and loosely coupled, some coordination of the activit-
ies is required. Both systems need an understanding what the counterparts are
doing [2]. In the following we take a look at S-BPM and its (dis-)advantages to
support interoperability in production-system-of-systems.
The paper is organised as follows. First Enterprise interoperability is presen-
ted. The work described here supports modelling and use of systems which
are loosely coupled. We take a look on S-BPM supporting interoperability in
production-system-of-systems. As a motivation and specific use case, we use
human-robot-collaboration to show di↵erent levels of interaction in production-
system-of-systems.
2 Enterprise Interoperability
Interoperability in general and interoperability on process level specifically is
required to have support formation of a system-of-systems. In the following we
argue about di↵erent levels of interoperability that need to be addressed in
system-of-systems to maintain a loose coupling.
“Taking a system-of-systems (SoS) perspective [3], the production system
includes all socio, economic and technical systems that are needed to make the
production (in the general sense) work. . . . Following [4] we distinguish a system
from a system-of-systems by the aspect that a system has a certain purpose
to fulfil. In a system-of-systems the purpose remains assigned to each of the
systems, whereas elements of a system are an inherent part of the system –
they lose their autonomy for the purpose of the system, systems in a system-
of-systems, however, remain independent and may leave their super system as
autonomous system.” [2, p. 2]
In human robot collaboration, using a system-of-systems perspective, one
system is of human and the other of artificial kind. Di↵erent degrees of integra-
tion and interoperability of these systems is possible from working independently
to dedicated and task specific enhancement of the workers cognitive or physical
capabilities [5,6].
2.1 Degree of Coupling
An integrated system works seamlessly with other integrated systems. However,
when taking a system-of-systems (SoS) perspective [3], the system that needs to
be addressed, includes socio, economic and technical systems. Enterprise Integra-
tion and Interoperability (EI&I) has been developed in the overlapping domains
of business information systems and enterprise information systems, production
research, business process management, computer science and organisational sci-
ence.
Current EI&I research is following a system-of-systems approach [7,8]. Based
on this basic conceptualisation, EI&I research discusses a continuum of di↵erent
qualities of integration [9]. Full integration describes systems where elements
share the same model. Tight coupling has both advantages and disadvantages.
A main advantage of sharing the same model, is that work on interfaces is
simple. The evolution of a model is done at the same time with all elements
of the integrated system. A major disadvantage of an integrated system is that
tight coupling of elements requires any modification (and model evolution) to
happen in all (related) elements at the same time. If one part requires some
change, all other elements must be adapted to meet this change as well. Loose
integration also has its advantages and disadvantages.
“[I]ntegration is generally considered to go beyond mere interoperability to
involve some degree of functional dependence” [10, p. 731]. This dependence
implies less flexibility and less resilience since it combines the involved systems
in order to form a single whole [11]. The integrated systems additionally lose their
individual purpose, in order to contribute to the purpose of the super-system.
Loose integration, also referred to as unified interoperability, is an approach
to support inter-operation of system-of-systems, where all systems share a com-
mon meta-model [12]. That meta-model allows information exchange at least
on an abstract level. The common meta-model is mapped by every system to
its own meta-model, and no assumptions may be made by other systems on the
private meta-models. That preserves the autonomy of the systems. So in order for
systems that join a system under this paradigm, a system maps and copies its in-
ternal data structures and information to the shared meta-model. The receiving
system then maps and copies the received information to its own internal struc-
ture. The advantage this is that all systems are clearly separated. Each system
may be changed without that change influencing other systems. Due to the layer
of abstraction, the change is not observable (per se). However, the meta-model
determines (and possibly limits) the interaction capabilities between the sys-
tems. And still some situations require the common meta-model to be changed,
which then requires the systems to adapt their own models and interfaces.
A third, even more loose coupled approach to interoperability exists. Feder-
ated interoperability describes systems of systems, where systems are capable
of negotiating interfaces and information-structures at runtime. Only a minimal
set of requirements is needed a-priori. This approach is sometimes called late-
binding and requires a semantic unification space where concepts that are used
by two or more systems can be mapped [9].
For example, domain ontologies, are used for semantic unification [13]. A
more recent example of this approach has been developed by [14].
2.2 Semiotic Level of Interoperability
Orthogonal to the degree of coupling are the levels of concern where interoper-
ability barriers (may) occur [8].
Barriers of enterprise interoperability are discussed on business / organisa-
tional level, semantic / conceptual level, and technical / data level.
On business level interoperability issues stop tow or more enterprise systems
doing business in general. Examples include incompatibilities in legal practice
and country dependent laws. On the same level, when processes are not com-
patible supplier - customer relationships are deadlocked, where both enterprises
wait for the other to perform an activity.
On semantic / conceptual level, models used in IT are incompatible. For
example di↵erent granularity of models stop enterprises from calling others’ API
to transmit data. Also conceptual barriers like di↵erent levels of granularity
of exchanged information objects occur (Person objects modelled with a name
property vs. objects modelled with a given-name and family-name).
At the technical level, enterprise interoperability barriers include among oth-
ers, syntactic message formats, service interaction protocols and technical secur-
ity aspects.
The European Interoperability Framework (EIF) [15,2], as one example,
brings together these above discussed levels as illustrated in Figure 1. Here se-
miotic levels are mapped to the EIF.
Figure 1. Semiotic Levels of Interoperability mapped to the European Interoperability
Framework (EIF)
Organisational semiotics, allows to discuss in more detail the relationship
between the model, its use and the addressed reality [16]. In this approach, the
levels are separated by norms that are used on that level.
social values of information / impact of signs influencing social behaviour
pragmatic information is used to get things done
semantic meaning of information is made and maintained in the organisation
syntactic data and sign structures and (semi) formal languages
empiric signs are organized into predictable patterns (alphabet);
physical hardware and physical media for signs; economic properties at the
material level
In addition to the structural requirements, EI&I is not a one-shot approach.
Enterprise integration and interoperability is a continuous process in a dynamic
environment. Having interoperability achieved, this state is easily lost due to
changing properties in the external environment or simple things like software
updates [17]. Already in moderately complex systems, it is not possible to predict
all impacts of a single change in one system on other systems. When missing
the continuous need for adaptation has lead enterprise application integration
(EAI) approaches to produce monolithic software systems [12].
Overall Enterprise Integration and Interoperability is a multi dimensional
system-of-systems research approach which facilitates flexibility and adaptabil-
ity while still having a system for a specific purpose. EI&I is a model-driven
approach, discussing not only the technical issues for exchanging raw data, but
also the semantics of the models (and meta-models) and the pragmatic aspects
in terms of what is triggered in organisations through the information exchange.
With respect to the system-of-systems approach interoperability on technical
level, is a pre-requirement for systems to interact. Interoperability on semantic
level is required to support a common understanding. However, only interop-
erability on process level assures that on organisational level tasks are enacted
without disturbance.
2.3 S-BPM for Enterprise Interoperability
Before going into more details how to support processes involving humans and
robots, we take a look at S-BPMN. S-BPM has been chosen, as it has a formal
basis [18] which for example BPMN misses [19].
S-BPM as an approach in general, and the available tools for S-BPM sup-
port interoperability. The following Table 1 shows this support for enterprise
interoperability by the S-BPM framework itself [20], by existing tools, and by
research prototypes [21,22,23,20,24]. The results presented in the table are de-
scribed in more detail in [25]. It shows that potential of the S-BPM ecosystem
on supporting the enterprise in generating loosely coupled integration. This is
mainly due to the two layers of inter-subject business object exchange and intra
subject control flow.
This table shows interoperability on several levels. However, for human robot
collaboration one (among other) interoperability gab exists between the human
and artificial system.
S-BPM has also been used in the manufacturing industry, connecting the
business process layer with the production process layer [33,24,34]. In that re-
search a S-BPM Subject integrated using OPC UA technology the link to hard-
ware and a production process which involves humans (as usual with S-BPM).
Three types of subjects have been identified in SO-Pc-Pro:
(i) Service Subject
(ii) Human Subject
(iii) Coordination Subject
The Service Subject represents a certain functionality required in the pro-
duction system. This includes for example the robots and sensors. However,
the subject behaviour is pre-specified. This works fine for pre-defined functions,
where Business Objects may be used to parametrise the machine.
The Human Subject represents the operator or worker. A user interface needs
to be provided to communicate with the worker.
Table 1. S-BPM Support for Interoperability in the Problem Space [25]
Barriers
Conceptual Technological Organizational
Concerns
3 2
Business smart4sense2act [21] Framework [20]
S-BPM Design Tools2
[20]
Process Framework (Ana- Framework Framework
lysis, Model- (IT-, Organization (All Activities)1 [20]
1 1
ing,Validation) Implementation) [20] Metasonic Touch2
S-BPM Design and S-BPM Design and [26], Comprehand3
1 1
Execution Tools [20] Execution Tools [20] [27,28,29],
S-BPM Design Tool1 ,
jCPEX!1 [30,22],
Ad-hoc Deviations1
[31]
Service Framework S-BPM Execution Framework
(Validation)2 Tool1 [20] (Monitoring)2
2
Metasonic Touch KPI Management
[26], Comprehand3 Tool2 [32]
[27,28,29]
Data S-BPM Execution
Tool as Enterprise
Bus1 [24]
1 . . . integrated; 2 . . . unified; 3 . . . federated;
“The main task of Coordination Subjects is to coordinate the interaction
of the subjects in the production environment to achieve a certain goal. How
this goal can be reached is basically defined by a set messages sent to di↵er-
ent subjects. These messages then again trigger the execution of concrete task
implementations. The coordination subject’s responsibility is to sequence these
messages based on a defined flow sequence, current state of the system and the
execution results.” [24, p. 3653]
In our approach this is the responsibility of the production process subject,
which takes care of the controlling the interaction between production systems.
From a global perspective in the SO-Pc-Pro approach, the user’s workflow
and activities are represented as internal behaviour in this approach.
With respect to the machine workflow, either some of the activities are refined
to trigger OPC UA connected devices, or a subject is created that has the desired
(internal) behaviour to connect the low-level machine control to the S-BPM
process. The conceptual and organisational control flow of the former is from the
user perspective. There is a single thread of control. From the interoperability
considerations above, the work in SO-Pc-Pro [24] is an integrated approach.
S-BPM allows (to some extend) to support the coordination of activities
in a system-of-systems involving human and artificial systems. It has a formal
basis which supports activities for artificial systems and it is human readable
supporting the human system. In the following we take a look at human-robot
collaboration specific aspects.
3 Interoperability in Robotic System-of-Systems
So far we have argued that the manufacturing enterprise is a system-of-systems
and support for interoperability (in contrast to integration) is required. This is
particularly true on the process level.
In the following, Human-Robot collaboration serves as motivation and ex-
ample to show the advantages and disadvantages of using S-BPM as interoper-
ability support for system-of-systems involving humans and machines.
With respect to manufacturing, one of the most flexible production system
are robots in general and human-robot collaboration more specifically in the
context of this research paper. It therefore makes sense from a workflow and
process perspective to take a closer look on interoperable and adaptive produc-
tion systems-of-systems with special attention to robotics.
Figure 2 brings together three important aspects for adaptive production
system-of-systems:
(a) the production system in fig. 2 is modelled as a system-of-systems, and sys-
tems are process-oriented (i.e. for a certain step a specific process instance
is implemented)
(b) while the production system-of-systems exhibits the desired modularity and
flexibility an overarching process is needed to coordinate the (independent)
sub-processes of the systems.
(c) S-BPM can be used to model systems and their internal processes. Interac-
tion of systems takes place through messages containing business objects.
Figure 2. Production System-of-Systems from an abstract S-BPM point of view
In the following we present di↵erent degrees of human robot collaboration.
The di↵erence is in the synchronization and coordination needs of the collabor-
ation of human and robotic systems. First we present these collaboration scen-
arios, then we discuss technologies for implementation.
3.1 Human Robot Collaboration Types
Human robot interaction can be understood in di↵erent degrees of physical coup-
ling. It is the interaction and the concept used to synchronise activities that
specifies the degree [35]:
(i) A simple binary input (e.g. start / stop) from the worker to control the robot
is a simple interaction. Point of synchronisation is through the interaction
of the worker with the control switches in this simple case.
(ii) Human Robot coexistence is a situation where both operate in close prox-
imity but have no shared or synchronised tasks or work pieces. Here hardly
synchronisation is necessary. Both must only make sure to not interfere with
the others’ work, e.g. collision avoidance is required.
(iii) Human Robot assistance is the situation, where the robot serves the worker
without any active part or reasoning, simply obeying the commands of the
user. Here the synchronisation between human and robot takes place through
the command information transmission.
(iv) Human robot cooperation describes a situation where the operator and the
robot work on the same workpiece. Here the synchronisation takes place
through the work piece. Both need to be aware where the other one works
on the piece and does not take any steps that interfere with the other’s work.
This requires an understanding of both about the others current and planed
tasks.
(v) The most intense interaction occurs when humans and robots share the
same task. This situation is called Human Robot Collaboration. The syn-
chronisation requirements here are not limited to the workpiece, but need to
synchronise the activities. The timing and location of the worksteps are of
importance. Also the upcoming activities of the collaborator. Both (the hu-
man and the robot) need a detailed understanding of the activities including
their timing.
Figure 3 shows the the simplest form of interaction (i), the worker starts or
stops the robot. Due to the simplicity of the interaction no subject behaviour
diagram is shown.
Figure 3. Scenario i: Start / Stop Robot by worker
Figure 4 shows the coexistence scenario (ii) where human and robot share the
same workspace but no direct interaction is required. Here a monitoring subject
triggers messages in order to warn about collisions. Often that is implemented
in the robot itself. However, its possible to have that component as a separate
module implementing the required functionality.
Figure 5 shows the assistance scenario (Iii) where human has full control over
the robot.
In figure 6 both agents share the same workpiece (scenario iv & v). In the
cooperation scenario (iv) the task lists need to be communicated to be able to
Figure 4. Scenario ii: Coexistence - collision avoidance by monitoring
understand if there is a conflict. A possible conflict would be that both occupy the
same area on the workpiece. In advanced settings some planing algorithm might
dynamically assign tasks to either party. In another scenario worker chooses a
task which is communicated to the robot to then react. As mentioned above
(v) in the truly collaborative scenario not only the workpiece is shared but also
tasks. While the basic interaction will look similar to the cooperative scenario
(iv), the level of detail is much higher. Not only the area on the workpiece, on
which tasks take place but also the timing of the tasks needs to be synchronized.
Hence, the interaction is time-sensitive. This time-sensitive synchronisation of
tasks is only implicitly possible in S-BPM.
3.2 Technologies for Interoperable System-of-Systems
For integration on data and technical level, the OPC UA Standard has been
used to integrate PLCs (Programmable Logic Controller) in Business Processes
[24,33]. In this approach, information and process models are mapped manually
to the OPC UA information model. Through a publish subscribe protocol the
PLC receives / pushes information from / to the Business process. This explicit
mapping also solves the problem of di↵erent information granularities required
for information understandable by human and robot.
With respect to the types of human robot interaction, this approach could
be used for binary interaction and co-existing interaction (scenario i, ii).
For the assistance scenario (iii) some other approaches exist, that allow to
reprogram robots by workers on the fly [36,35]. However, in these approaches
a process representation does not exist. It is assumed, that workers and ro-
bots are executing a simple sequence of tasks. Focus of that work is on the
developments for dynamic reprogramming robots by workers. Hence, advanced
workflows where for example parallel executed activities which need some syn-
chronization can not be dealt with.
Figure 5. Scenario iii: Assistance - worker in command
Figure 6. Scenario iv / v: Cooperation - synchronization of tasks / Collaboration -
synchronization of tasks and their timing
In some other research technologies for planning and assigning tasks auto-
matically to humans or robots is analysed [37]. Here also a elaborated process
point of view is missing, to support more complex assignment and coordina-
tion of activities of di↵erent agents. This allows simple cooperation (scenario iv)
based on simple task lists.
Missing is support for manual design and automated planning of advanced
process structures where parts are executed by human and artificial agents.
3.3 Next Steps
S-BPM as basis for human robot collaboration (scenario v) allows to support
loose coupling through the two layer approach. Multiple aspects need to be
further developed to reach this vision.
On the Subject Behaviour Layer the semantics of the di↵erent model elements
can be determined through an abstract state machine based formal model [20,18].
The formal underpinning allows to specify precisely the model building blocks
and control flows. Unfortunately on Subject Interaction Layer the business ob-
jects are formalised as messages only. For the envisioned support, more detailed
meta-models and semantics support in order to increase the interoperability of
subjects executing di↵erent process segments is required. More specifically, an
ontology describing in detail the activities, work-pieces and tools in detail is
needed for supporting a shared understanding between multiple agents enacting
these subjects.
Another aspect for future research, is to enable automatic re-planing of pro-
cesses and complex tasks using that ontology to support the detailed specification
of robotic arm movements, articulate potential collision situation, specification
of human tasks an the required resources, tools.
The third aspect for further research is a common S-BPM meta-model and
and information model (e.g. upper ontology) forming a basis for federated in-
teroperability where robot and human negotiate over task distributions on an
ad-hoc basis. Federated interoperability also requires a shared meta-model sup-
porting the understanding of systems that may assume several subject “roles”.
The shared subject information contains (implicitly) interaction protocols, as
subjects only interact with specific other subjects with well defined interaction
(send / receive states and business objects exchanged).
This description needs to be shared through some infrastructure services,
allowing agents to identify other agents and subjects. This directory service is a
basic support for federated interoperability, where agents interact with a priory
unknown other agents.
4 Conclusions
We have argued, that production is a system-of-systems. The systems have an
individual purpose and a certain degree of autonomy. To keep this autonomy a
coordination approach is needed that allows to maintain autonomy.
S-BPM, due to its two level approach of separating the subject-interaction
from the individual system behaviour would allow to support process interoper-
ability.
We have used human-robot collaboration as a motivation and use-case to
understand the interoperability requirements of adaptive production system-of-
systems.
Advanced types of human-robot collaboration requires more information on
available other systems, their capabilities, detailed understanding of the others’
tasks and activities. Semantic interoperability needs to be established for ex-
ample using a common high level ontology describing business objects, tasks,
processes and services that allow agents to discover that information.
To be able to have the robotic system execute a process, also automated
planing needs to take place. As stated above, that in turn impacts planing
and scheduling of the overall collaborative processes. Additionally planing and
scheduling needs to be able to assign a certain task to a specific agent at runtime.
For highly interactive scenarios, the following is also missing but not discussed
in detail:
– time sensitive synchronization of tasks where human and robots have to
execute their specific tasks concurrently
– time constraints in general are missing, e.g. to stop activities after some time.
– dynamic assignment of specific subjects that implement a certain subject
interaction protocol
Acknowledgement
The research described in this paper has been partially funded by the European
Union and the state of Upper Austria within the strategic economic and research
program “Innovative Upper Austria 2020” and the projects ”Smart Factory Lab”
and ”DigiManu”.
References
1. Weichhart, G., Molina, A., Chen, D., Whitman, L., Vernadat, F.: Challenges
and current developments for sensing, smart and sustainable enterprise systems.
Computers in Industry 79 (2016) 34–46
2. Weichhart, G., Stary, C., Vernadat, F.: Enterprise modelling for interoperable and
knowledge-based enterprises. International Journal of Production Research (2018)
accepted for publication.
3. Gorod, A., White, B.E., Ireland, V., Gandhi, S.J., Sauser, B., eds.: Case Studies in
System of Systems, Enterprise Systems, and Complex Systems Engineering. CRC
Press, Taylor & Francis Group (2014)
4. Boardman, J., Sauser, B.: System of systems - the meaning of of. In: System of
Systems Engineering, 2006 IEEE/SMC International Conference on, IEEE (2006)
6 pp.–
5. Romero, D., Bernus, P., Noran, O., Stahre, J., Fast-Berglund, Å.: The operator 4.0:
Human cyber-physical systems & adaptive automation towards human-automation
symbiosis work systems. In Nääs, I., Vendrametto, O., Mendes Reis, J., Gonçalves,
R.F., Silva, M.T., von Cieminski, G., Kiritsis, D., eds.: Advances in Production
Management Systems. Initiatives for a Sustainable World, Cham, Springer Inter-
national Publishing (2016) 677–686
6. Romero, D., Stahre, J., Wuest, T., Noran, O., Bernus, P., Fast-Berglund, Å.,
Gorecky, D.: Towards an operator 4.0 typology: a human-centric perspective on
the fourth industrial revolution technologies. In: International Conference on Com-
puters and Industrial Engineering (CIE46) Proceedings. (2016)
7. Naudet, Y., Latour, T., Guédria, W., Chen, D.: Towards a systemic formalisation
of interoperability. Computers in Industry 61 (2010) 176–185
8. Ducq, Y., Chen, D., Doumeingts, G.: A contribution of system theory to sustain-
able enterprise interoperability science base. Computers in Industry 63(8) (2012)
844 – 857 Special Issue on Sustainable Interoperability: The Future of Internet
Based Industrial Enterprises.
9. Petrie, C.J., ed.: Enterprise Integration Modeling. The MIT Press, Cambridge,
MA (1992)
10. Panetto, H.: Towards a classification framework for interoperability of enterprise
applications. International Journal of Computer Integrated Manufacturing 20(8)
(December 2007) 727–740
11. Dassisti, M., Jardim-Goncalves, R., Molina, A., Noran, O., Panetto, H.,
Zdravković, M.M.: Sustainability and interoperability: Two facets of the same
gold medal. In Demey, Y.T., Panetto, H., eds.: On the Move to Meaningful In-
ternet Systems: OTM 2013 Workshops. Volume 8186. Springer, Berlin Heidelberg
(2013) 250–261
12. Vernadat, F.B.: Interoperable enterprise systems: Principles, concepts, and meth-
ods. Annual Reviews in Control 31(1) (2007) 137 – 145
13. Fox, M.S., Gruninger, M.J.: Enterprise modeling. AI Magazine 19(3) (1998) 109–
121
14. Tu, Z., Zacharewicz, G., Chen, D.: A federated approach to develop enterprise
interoperability. Journal of Intelligent Manufacturing 27(1) (2014) 11–31
15. Vernadat, F.B.: Technical, semantic and organizational issues of enterprise inter-
operability and networking. Annual Reviews in Control 34(1) (2010) 139 – 144
16. Stamper, R., Liu, K., Hafkamp, M., Ades, Y.: Understanding the roles of signs
and norms in organizations - a semiotic approach to information systems design.
Behaviour & Information Technology 19(1) (2000) 15–27
17. Bénaben, F., Mu, W., Boissel-Dallier, N., Barthe-Delanoe, A.M., Zribi, S., Pingaud,
H.: Supporting interoperability of collaborative networks through engineering of
a service-based mediation information system (mise 2.0). Enterprise Information
Systems 9(5-6) (2015) 556–582
18. Lerchner, H., Stary, C.: An open s-bpm runtime environment based on abstract
state machines. In Proper, H.A., Ralyté, J., Marchand-Maillet, S., Lin, K., eds.:
2014 IEEE 16th Conference on Business Informatics. (2014) 54–61
19. Wohed, P., van der Aalst, W.M., Dumas, M., ter Hofstede, A.H., Russell, N.: On
the suitability of bpmn for business process modelling. In Dustdar, S., Fiadeiro,
J.L., Sheth, A., eds.: Proceedings 4th International Conference on Business Process
Management. Volume 4102., Springer (2006) 161–176
20. Fleischmann, A., Schmidt, W., Stary, C., Obermeier, S., Börger, E.: Subject-
Oriented Business Process Management. Springer, Berlin Heidelberg (2012)
21. Bastarz, F., Halek, P.: smart4sense2act: A smart concept for systemic performance
management. In Schmidt, W., ed.: S-BPM ONE - Learning by Doing - Doing by
Learning. Volume 213 of Communications in Computer and Information Science.
Springer Berlin Heidelberg (2011) 109–114
22. Meyer, N., Feiner, T., Radmayr, M., Blei, D., Fleischmann, A.: Dynamic catenation
and execution of cross organisational business processes - the jcpex! approach.
In Fleischmann, A., Schmidt, W., Singer, R., Seese, D., eds.: Subject-Oriented
Business Process Management. Volume 138 of Communications in Computer and
Information Science. Springer, Berlin Heidelberg (2011) 84–105
23. Rothschädl, T.: Ad-hoc adaption of subject-oriented business processes at runtime
to support organizational learning. In Stary, C., ed.: S-BPM ONE - Scientific Re-
search. Volume 104 of Lecture Notes in Business Information Processing. Springer
Berlin Heidelberg (2012) 22–32
24. Neubauer, M., Krenn, F., Majoe, D., Stary, C.: Subject-orientation as design
language for integration across organisational control layers. International Journal
of Production Research 55 (2017) 3644–3656
25. Weichhart, G., Wachholder, D.: On the interoperability contributions of s-bpm.
In Nanopoulos, A., Schmidt, W., eds.: S-BPM ONE - Scientific Research. Volume
170 of LNBIP - Lecture Notes in Business Information Processing. Springer Inter-
national Publishing (2014) 3–19
26. Kannengiesser, U., Oppl, S.: Business processes to touch: Engaging domain experts
in process modelling. In Daniel, F., Zugal, S., eds.: BPM Demo Session 2015.
Volume 1418 of CEUR Workshop Proceedings., CEUR-WS.org (2015) 40–44
27. Oppl, S.: Subject-oriented elicitation of distributed business process knowledge. In
Schmidt, W., ed.: International Conference on Subject-Oriented Business Process
Management. Volume 213 of Communications in Computer and Information Sci-
ence., Springer-Verlag Berlin Heidelberg, Springer-Verlag Berlin Heidelberg (2011)
16–33
28. Oppl, S., Stary, C.: Facilitating shared understanding of work situations using
a tangible tabletop interface. Behaviour & Information Technology 33(6) (2014)
619–635 Published online: 02 Oct 2013.
29. Oppl, S.: Articulation of subject-oriented business process models. In: Proceedings
of the 7th International Conference on Subject-Oriented Business Process Manage-
ment. S-BPM ONE ’15, New York, NY, USA, ACM, ACM (2015) 2:1–2:11
30. Meyer, N., Radmayr, M., Heininger, R., Rothschädl, T., Fleischmann, A.: Platform
for managing and routing cross-organizational business processes on a network
router. In Schmidt, W., ed.: S-BPM ONE - Learning by Doing - Doing by Learning.
Volume 213 of Communications in Computer and Information Science (CCIS).
Springer, Berlin Heidelberg (2011) 175–189
31. Heininger, R.: Requirements for business process management systems supporting
business process agility. In Oppl, S., Fleischmann, A., eds.: S-BPM ONE - Edu-
cation and Industrial Developments. Volume 284 of Communications in Computer
and Information Science. Springer, Berlin Heidelberg (2012) 168–180
32. Weichhart, G., Feiner, T., Stary, C.: Implementing organisational interoperability
– the sudden approach. Computers in Industry 61(2) (2010) 152 – 160
33. Neubauer, M., Stary, C., eds.: S-BPM in the Production Industry. Springer Inter-
national Publishing, Switzerland (2017)
34. Weichhart, G., Stary, C.: Interoperable process design in production systems.
In Debruyne, C., Panetto, H., Weichhart, G., Bollen, P., Ciuciu, I., Vidal, M.E.,
Meersman, R., eds.: On the Move to Meaningful Internet Systems: OTM 2017
Workshops. Number 10697 in Lecture Notes in Computer Science. Springer Inter-
national, Cham, Switzerland (2018) 26–35
35. Pichler, A., Akkaladevi, S.C., Ikeda, M., Hofmann, M., Plasch, M., Wögerer, C.,
Fritz, G.: Towards shared autonomy for robotic tasks in manufacturing. Procedia
Manufacturing 11 (2017) 72–82
36. Matthaiakis, S.A., Dimoulas, K., Athanasatos, A., Mparis, K., Dimitrakopoulos,
G., Gkournelos, C., Papavasileiou, A., Fousekis, N., Papanastasiou, S., Michalos,
G., Angione, G., Makris, S.: Flexible programming tool enabling synergy between
human and robot. Procedia Manufacturing 11 (2017) 431 – 440 27th International
Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-
30 June 2017, Modena, Italy.
37. Müller, R., Vette, M., Mailahn, O.: Process-oriented task assignment for assembly
processes with human-robot interaction. Procedia CIRP 44 (2016) 210 – 215 6th
CIRP Conference on Assembly Technologies and Systems (CATS).