Working groups

 

 

Model based engineering

Responsible: Prof. Cesare Fantuzzi (cesare.fantuzzi(at)unimore.it)

Manufacturing systems are becoming more and more complex, and modern industrial automation applications exhibit the same symptoms of “excessive complexity” that brought about the software crisis in the 1970s and 1980s; at the same time, the role of software is getting more prominent, both as design tool (computer-aided engineering (CAE) tools) and as stand-in for preexisting technology. For example, in high-performance manufacturing machinery, mechanical cams, and other motion transmission devices are often replaced with software-coupled servomotors, in order to increase flexibility and reconfigurability of the production system. This technological innovation can be managed with a Model Based Engineering (MBE) Approach to machine design.

MBE focuses on creating and exploiting domain models as means of information management to tackle complexity in machine design, also supporting model execution in computer simulation experiments for an early evaluation of engineering design. The aim of this sub-WG is to foster joint discussion and research on these topics.

 

 

Semantic technologies in control engineering

Responsible: Aljosha Köcher (aljosha.koecher@hsu-hh.de)

In various use-cases in industry and research, a common concept for semantic modeling is needed in order to implement these use-cases. This especially holds for heterogeneous, distributed systems, such as Cyber-Physical Production Systems (CPPS), but similarly in other domains. These distributed systems have to deal with individual sub-systems which stem from different suppliers but have to exchange information to implement the overall system function. Not only the communication means have to be agreed upon, but further the content of the exchanged information must be understood correctly by all components, which requires that the information is based on a semantic description.

This holds for all phases of the life cycle of an automated system: The first use-case for semantic modeling can be found in the early life-cycle phase of a system, i.e. the engineering of the system. The engineering of automated systems usually relies on several engineers who are working on different tasks that have to be accomplished through the engineering phase. Especially for complex systems, model-based engineering as well as the systematic reuse of components can provide relevant efficiency increases. However, the information created in the engineering phase has to use a common semantic, not only for avoiding inefficiencies or faults throughout the engineering process, but also to support the cooperation between engineering teams.

Concerning the modeling of skills for the purpose of reconfiguration of manufacturing systems, there has been remarkable research effort on information modeling already in order to model skills for reconfiguration and orchestration purposes.

Concerning the orchestration of manufacturing services by means of service oriented architectures (SOA), semantic modeling of services is necessary in order to provide a common understanding of the post- and preconditions of a service, and semantic descriptions of manufacturing services have been proposed in order to provide information for an agent based orchestration system. Furthermore, semantic descriptions of manufacturing systems can be used to schedule the resources, e.g. workers and machines, of a factory.

Furthermore, semantic modeling of systems is becoming relevant for diagnosis and maintenance systems as well: semantic descriptions about the condition of systems are required to provide a common information model for the diagnosis of distributed manufacturing systems, i.e. semantic descriptions of the systems that are monitored and the maintenance knowledge.

Desipte these needs, there are still many open research questions regarding the creation and use of semantic enrichment of information in the design, implementation, operation and optimization of automated systems. The aim of this sub-WG is to foster joint discussion and research on these topics.

 

 

Industrial agents

Responsible: Prof. Birgit Vogel-Heuser (vogel-heuser(at)ais.mw.tum.de)

The focus of the TC 3.1 working group “Industrial agents“ lies on the investigation of agent-based applications in the industrial automation domain such as logistics, automation production systems or energy and smart grids. Based on a multi-agent system, the intense interconnectedness in between computers or embedded systems in these domains as well as partly within operational and business applications over the Internet should be improved. Therefore, members of universities or industry investigate and adapt novel approaches, applications and methods for multi-agent systems in industrial automation systems. Additionally, various technologies in further fields, e.g. Machine Learning, are identified and their potentials for applications within the domain of industrial automation are analyzed. In the field of “Energy and Smart Grids”, challenges of agent-based coordination and control of energy supply systems of the future are examined. Thus, the control and introduction of renewable energy systems will be improved.

The results of our work are both integrated within the remaining working groups “Semantic technologies in control engineering” and “Model based engineering” of the TC 3.1 as well as within joint publications. Therefore the members are working on a roadmap of possible applications of agents as well as their potentials in the industrial automation domain. In this context, first implementations of a decentralized multi-agent system, such as the agent-based networks for cyber–physical production systems (CPPS)– listed as one of Germany’s official Industrie 4.0 use case – could be developed and commissioned in the past. The development and application of further use cases in different domains is maintained and expanded in the future. To improve the application, the members defines standards for the development of multi-agent systems within the various application areas of industrial automation as well as application potentials. The working group thus provides a platform for exchanging research results, ideas and experiences of researchers and appliers interested.

 

 

Software Analysis of IEC 61131-3 control code and Recommendations for Actions

Responsible: Eva-Maria Neumann (eva-maria.neumann@tum.de)

The TC 3.1 working group “Analysis and optimization of industrial IEC 61131-3-compliant control software” focuses on developing methods and strategies to tackle current and future challenges in the field of control software development that were identified and confirmed by international experts and industrial practitioners. Specifically, the working group addresses the following core topics and research questions:

  • Procedure for Static Code Analysis
    • Which methods can be used to analyze the current status of control software across companies to identify potentials for improvement?
    • Which factors in the software must be taken into account and how can other distinct features of control software be considered, such as the implemented functionality and the controlled hardware?
  • Control Software Architecture
    • How are typical automation functions such as error handling or operating mode changes implemented in the architecture and which software structures are particularly suitable for this purpose?
    • How can the software architecture be optimized by concrete recommendations for action?
  • Assessment of modularity and reuse using quality indicators
    • How can quality characteristics of software according to ISO 25010 be measured by objective quality indicators?
    • Which reuse strategies of software exist and which of them are suitable for which boundary conditions?
  • Conduction of international questionnaire studies
    • What are the current challenges in the modularization of mechatronic systems, especially regarding control software?
    • How can maturity in modularization be made internationally comparable?

The working group aims to address researchers (young and senior) with a focus on software engineering and industrial practitioners from engineering in machine and plant manufacturing and further IEC 61131-3 domains (e.g., trains or construction machinery).