Institute of Automation and Information Systems
Engineering and operation of intelligent, reconfigurable, distributed cyber-physical production systems
n In 2015, the Institute of Automation and Information Systems (AIS) focused on analyzing, establishing and improving novel methods, appro- aches and tools to address the challenges that result from the increasing demand to produce customer-specific, individual products in the machine and plant manufacturing domain.
Therein, innovative approaches for Industry 4.0-capable systems have been and are being developed to improve
both the engineering and the operation of cyber-physical production systems. Among others, technologies and methods applied at AIS are agent-based and service-oriented approaches as well as modeling approaches – both semi-formal and formal – to provide novel concepts
for designing and operating intelligent, reconfigurable, distributed cyber-physical production systems. Especially methods and technologies from the computer science domain are used and adapted to address the challenges in automation and in the machine and plant manufacturing domain. Moreover, taking the interaction with humans and machines into account,
the methods and approaches developed
at AIS are analyzed and evaluated in real- world scenarios and together with experts from industry.
Research focus of the Institute of Automation and
Information Systems
Prof. Dr.-Ing.
Birgit Vogel-Heuser
Contact
www.ais.mw.tum.de
Phone +49.89.289.16400
Intelligent, Reconfigurable, Distributed
Cyber-Physical Production Systems
Open research demonstrator „myJoghurt“ (Starterkit available from http://i40d.ais.mw.tum.de)
The ever-increasing complexity and dimensions of automated production systems in industrial automation require
a high degree of flexibility and intelligence
in and among system components. Hence, one aspect being addressed by AIS is to explore the advantages of such intelligent, reconfigurable and distributed systems contrary to their disadvantages, e.g. the extended need for communica- tion.
Therefore, at AIS, notations, methods
and tools are developed for the design of agent-oriented automation software for machines and production plants in both the manufacturing and process automa- tion domain. By that, the design, imple- mentation and operation of distributed, intelligent cyber-physical production sys- tems can be simplified, comprehensibility can be increased and, thus, acceptance
in industry can be enhanced. In 2015, two
novel research projects (namely aComA and iSikon) were established that address the need for flexibility and reconfigurability in the logistics domain. Moreover, the joint demonstrator ‘myJoghurt’ was extended together with three further German insti- tutes – thereby enlarging the demonstrator towards eight participants. Furthermore, since 2015, ‘myJoghurt’ is contained in
the ‘Landkarte Industrie 4.0’*, which has
been initiated by the ‘Plattform Industrie
4.0’ initiative. Besides others, together with international robot companies, the same architecture and platform was applied for a collaborative production. Using simple scenarios, the coupling of
locally distributed production systems in an automatic and dynamic manner can be demonstrated using ‘myJoghurt’.
Projects
n BayFor Project – Automatische Codegenerierung für modulare Anlagen (aComA)
n BMBF Project – Sichere, dynamische
Vernetzung in Operationssaal und Klinik
(OR.NET)
n DFG Project – Gesteigerte Flexibilität in heterogen aufgebauten Material- flusssystemen auf Basis intelligenter Softwareagenten in selbstkonfigurieren- der Fördertechnik (iSikon)
Model-based Engineering of Variant-rich
Interdisciplinary Manufacturing Systems
Extended Pick and Place Unit (xPPU) – demonstrator for safety, modes of operation and commu- nication technologies
Besides improving the operation of Industrie 4.0-capable systems, one major area of interest for AIS is the engineering
of automated production systems. Therein, AIS investigates concepts and methods towards the model-based development
of such systems – both in the (discrete)
manufacturing engineering domain and in the (continuous) process engineering domain. A special focus is put on the interdisciplinary character of the design of industrial automation systems as well as on increasing the transparency and handling the complexity throughout the workflow of automation systems design and operation.
* http://www.plattform-i40.de/I40/Navigation/DE/
In-der-Praxis/Karte/karte.html, retrieved 2015/12/11.
As one major success in 2015 – not only for AIS as coordinator, but also for the entire research team – the DFG approved the extension of the Collaborative Research Center (CRC) 768 for a third funding period of four years. Moreover, AIS was able to establish further research projects within the second funding period of the Priority Programme (PP) 1593. In addition, concepts for the integration
of energy aspects with the modeling of
the operating performance (behavior) of production systems and automotive systems are explored (cf. research project ProMES). Therefore, different modeling languages are investigated and adapted for these different classes of mechatronic systems and corresponding editors and tool environments have been developed. For the coupling and synchronization of heterogeneous models, model transfor- mations as well as formal methods for consistency checking have been investi- gated and successfully applied. Concern- ing the transfer of research results into industrial applications, a major outcome
of this field of research is the successful
realization of approaches for model-ba- sed automation software development, code generation, and model-based debugging (e.g. within the completed projects ZuMaTra and MoBaTest) as well
as software testing inside a development environment for automation software that is widely used in industry. As one core aspect of industrial automation software, a working group ‘Modularity, Variant
and Version Management in Industrial Automation’ was established together with companies in the packaging, wood processing and automotive domain. Our core demonstrator – the Pick and Place Unit – was extended in 2015 to address further, industry-relevant aspects such as safety, modes of operation and novel communication technologies.
Projects
n BMBF Project – Automatisches Gene- rieren von Fertigungsmanagementsys- temen (für die Lebensmittelindustrie) (AutoMES)
n DFG Project – Regression Verification in a User-Centered Software Develop- ment Process for Evolving Automated Production Systems (SPP 1593, project IMPROVE APS)
n DFG Project – Domain-spanning Main-
tainability Estimation (SPP 1593, project
DoMain)
n DFG Project – Self-Maintenance of Mechatronic Modules (SFB 768, subpro- ject A6)
n DFG Project – Diagnosis and Resolution
of Inconsistencies in Heterogeneous
Models (SFB 768, subproject D1)
n DFG Project – Decision making support in innovation processes under con- sideration of the technical disciplines (SFB 768, subproject T3)
n EU Project – Innovative Modelling
Approaches for Production Systems to
Raise Validatable Efficiency (IMPROVE)
Human-Machine Interaction as well as Data
Integration and Processing to Support Humans
This field of research addresses the
design and evaluation of human-machine- interfaces (HMI) for operators as well as engineering support systems. The rese- arch field concerns supporting the opera- ting personnel in training, commissioning, process monitoring, process optimizing, and diagnosis by means of appropriate visualization methods of process and message data during the operation phase of technical plants. The current trend in industry is to replace the classical 2D visualization systems in control rooms
for process monitoring and operation by
new visualization technologies such as 3D visualization as well as augmented reality and their visualization on mobile devices. Today’s challenges cover the extraction of beneficial information from the rising flood of process data to e.g. detect faults. This information is collected by data aggrega- tion and data analysis from many different data sources. Fault characteristics are not only characteristics indicating a fault, but also symptoms that indicate causal impact of a fault within a system. Based on this analysis the system can provide recom-
mendations to the operator on how he has to intervene in the process. AIS, therefore, not only investigates scalable integration concepts for aggregating and analyzing big industrial data sets (cf. project SIDAP), but also visualization and navigation concepts (cf. SFB 768 D2) to support stakeholders in the industrial automation domain.
Projects
n BMWi Project – Skalierbares Integra- tionskonzept zur Datenaggregation,
-analyse, -aufbereitung von großen
Datenmengen in der Prozessindustrie
(SIDAP)
n DFG Project – Interactive Visualization and Navigation in Heterogeneous Models (SFB 768, subproject D2)
n KME Project – Prozesszustandsbasier-
tes Monitoring von Produktionsanlagen durch MES (ProMES)
Exemplary challenges of hetero- geneous models
Research Focus
n Model-based engineering
n Quality management
n Distributed, intelligent control systems
n Software agents, service-oriented architectures
n Machine learning
n Cyber-physical production systems
n Information processing
n Human factors
Competence
n Improvement of the engineering during the whole life cycle of products and production lines for hybrid processes using and adapting methods from com- puter science, e.g. pattern recognition and software engineering.
n In charge of the smart production
scenario of the cyber physical systems road-map in close cooperation with market-leading companies.
Infrastructure
n Complex hybrid plant lab model which operates with market leading automa- tion devices
n 48 modular production plants for
C-programming in basic lectures
n Neutralization plant – test bed for the
process engineering domain
n Pick and Place Unit – demonstrator for evolution in industrial plant automation
n Extended Pick and Place Unit –
demonstrator for safety, modes of operation and novel communication technologies
Courses
n Basics of Modern Information
Technology I+II
n Modeling and Simulation
n Industrial Automation 1+2
n Development of Distributed Intelligent
Embedded Mechatronic Systems
n Industrial Software Engineering 1+2
n Semantic Technologies in Industrial
Automation
n Manufacturing Execution Systems in
Producing Industries
n Practical Course Automation
n Practical Course Development of Distributed Intelligent Embedded Mechatronic Systems
n Practical Course Industrial Software
Engineering
n Practical Course Simulation Technology
Management
Prof. Dr.-Ing. Birgit Vogel-Heuser, Director
Associate Lecturer
Dr.-Ing. Heiko Meyer
Secretariat Michaela Franke Irene Goros
Steering Committee
Dr.-Ing. Dorothea Pantförder
Dr.-Ing. Daniel Schütz
Jens Folmer
Research Associates
Thomas Aicher Ulrich Bührer Franziska Fassl Stefan Feldmann
Konstantin Kernschmidt
Christoph Legat Felix Mayer Daniel Regulin
Sebastian Rehberger
Susanne Rösch Thomas Simon Sebastian Ulewicz Benedikt Weißenberger
Laboratory and Technical Staff
Christian Gmeinwieser
Thomas Mikschl Andor Nagy Johannes Werner
Apprentices
Julian Schachermeier
Tom Kaden
Doctoral Theses finished in 2015
Dr.-Ing. Daniel Schütz
Dr.-Ing. Dominik Stengel
Dr.-Ing. Martin Obermeier
Publications 2015
Journal Articles
n Fay, A.; Vogel-Heuser, B.; Frank, T.; Eckert, K.;
Hadlich, T.; Diedrich, C.: Enhancing a model-based engineering approach for distributed manufacturing automation systems with characteristics and design patterns. In: Journal of Systems and Software
(JSS), vol. 101, 2015, pp. 221-235.
n Obermeier, M.; Braun, S.; Vogel-Heuser, B.: A Model-Driven Approach on Object-Oriented PLC Programming for Manufacturing Systems with Regard to Usability. In: IEEE Transactions on Industrial Informatics (TII), vol. 11, no. 3, 2015, pp. 790-800.
n Rösch, S.; Ulewicz, S.; Provost, J.; Vogel-Heuser,
B.: Review of Model-Based Testing Approaches in Production Automation and Adjacent Domains – Current Challenges and Research Gaps. In: Journal of Software Engineering and Applications, vol. 8,
no. 9, 2015, pp. 499-519.
n Vogel-Heuser, B.; Fay, A.; Schäfer, I.; Tichy, M.: Evolution of software in automated production systems – Challenges and Research Directions. In: Journal of Systems and Software (JSS), vol. 110,
2015, pp. 54-84.
n Vogel-Heuser, B.; Fuchs, J.; Feldmann, S.; Legat, C.: Interdisziplinärer Produktlinienansatz zur Steigerung der Wiederverwendung. In: Automatisie- rungstechnik (at), vol. 63, no. 2, 2015, pp. 99-110.
n Vogel-Heuser, B.; Schütz, D.; Folmer, J.: Cri-
teria-based Alarm Flood Pattern Recognition using Historical Data from Automated Production Systems (aPS). In: Mechatronics, 2015 (in press). Online: http://dx.doi.org/10.1016/j.mechatronics.
2015.02.004.
n Vogel-Heuser, B.; Lee, J.; Leitão P.: Agents enabling cyber-physical production systems. In: Automatisie- rungstechnik (at), vol. 63, no. 10, pp. 777-789.
Conference Publications
n Abele, L.; Anic, M.; Gutmann, T.; Folmer, J.; Aicher,
T.; Rehberger, S. and Vogel-Heuser, B.: Towards finding the appropriate level of abstraction to
model and verify automated production systems in discrete event simulation. In: 10th IEEE International Conference on Automation Science and Engineer- ing (CASE 2015), Gothenburg, Sweden, 2015,
pp. 1048-1053.
n Beckert, B.; Ulbrich, M.; Vogel-Heuser, B.; Weigl,
A.: Regression Verification for Programmable Logic Controller Software. In: The 17th International Con- ference on Formal Engineering Methods (ICFEM), Paris, France, 2015.
n Bührer, U.; Legat, C.; Vogel-Heuser, B.: Changeabi-
lity of Manufacturing Automation Systems using an Orchestration Engine for Programmable Logic Con- trollers. In: 15th IFAC Symposium on Information Control in Manufacturing (INCOM), Ottawa, 2015, pp. 1573-1579.
n Feldmann, S.; Herzig, S.; Kernschmidt, K.; Wol- fenstetter, T.; Kammerl, D.; Qamar, A.; Lindemann, U.; Krcmar, H.; Paredis, C. and Vogel-Heuser, B.: A Comparison of Inconsistency Management Appro- aches Using a Mechatronic Manufacturing System Design Case Study. In: 10th IEEE International Conference on Automation Science and Engineer- ing (CASE 2015), Gothenburg, Sweden, 2015,
pp. 158-165.
n Feldmann, S.; Herzig, S.; Kernschmidt, K.; Wol- fenstetter, T.; Kammerl, D.; Qamar, A.; Lindemann, U.; Krcmar, H.; Paredis, C. J.J.; Vogel-Heuser, B.: Towards Effective Management of Inconsisten- cies in Model-Based Engineering of Automated Production Systems. In: 15th IFAC Symposium
on Information Control in Manufacturing (INCOM),
Ottawa, 2015, pp. 917-923.
n Feldmann, S.; Legat, C.; Vogel-Heuser, B.: An Analysis of Challenges and State of the Art for Modular Engineering in the Machine and Plant Manufacturing Domain. In: 2nd IFAC Conference
on Embedded Systems, Computational Intelligence
and Telematics in Control, Maribor, 2015, pp. 87-92.
n Feldmann, S.; Legat, C.; Vogel-Heuser, B.: Engineer- ing Support in the Machine and Plant Manufactur- ing Domain through Interdisciplinary Product Lines: An Applicability Analysis. In: 15th IFAC Symposium on Information Control in Manufacturing (INCOM), Ottawa, 2015.
n Fischer, J.; Friedrich, D. and Vogel-Heuser, B.:
Configuration of PLC software for automated warehouses based on reusable components – an industrial case study. In: 20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2015), Luxembourg, 2015,
pp. 1-7.
n Gramß, D.; Vogel-Heuser, B.: Contribution of perso- nal factors for a better understanding of the gender effects of freshmen in mechanical engineering.
In: IEEE International Conference on Industrial
Technology (ICIT), Seville, 2015, pp. 3258-3263.
n Hufnagel, J.; Vogel-Heuser, B.: Data Integration in Manufacturing Industry: Model-Based Integration of Data Distributed from ERP to PLC. In: 13th IEEE International Conference on Industrial Informatics (INDIN), Cambridge, 2015, pp. 275-281.
n Kernschmidt, K.; Preißner, S.; Raasch, C.;
Vogel-Heuser, B.: From selling products to providing user oriented product-service systems – Exploring service orientation in the German machine and plant manufacturing industry. In: 12th IFIP International Conference on Product Lifecycle Management,
2015.
n Mayer, F.; Bührer, U.; Pantförder, D.; Gramß, D.; Vogel-Heuser, B.: Automatic Generation of Inte- grated Process Data Visualizations using Human Knowledge. In: 17th International Conference on Human-Computer Interaction (HCI), Los Angeles, USA, 2015.