Peter Göhner

Abstract

In the development of automated systems in the field of industrial automation, engineers often have to work on many tasks under time pressure, including simulations. In order to support engineers in these complex simulation tasks, a framework is presented which coordinates and calculates simulations based on structured knowledge in a parallelized, decentralized way. Different approaches for a problem are simulated automatically and compared with each other. Therefore, complex problems, meaning large-scale ones that often consist of coupled problem parts, are decomposed into partial problems. Their approaches are subsequently processed separately each using the most suitable software tool. Cooperating software agents are utilized to achieve a flexible coordination of decentralized simulations. These autonomous software units communicate with each other to control the parallelized activities during a simulation project. The presented concept is evaluated based on the application fields of control design and multiphysics simulation. Hence, multi-agent systems (MAS) were generated prototypically using the developed framework. As an addition to the framework for parallel simulation, a concept for supplementing the MAS with a case-based reasoning component is presented. Using the case-based reasoning addition, the performance of the simulations was further improved. Due to the varying computation time of the different approaches, analyzed in parallel, results are often available earlier. The MAS is also capable of improving the quality of the results because of the automatic analysis and comparison of different approaches.

Abstract

In the development of automated systems in the field of industrial automation, engineers often have to work on many tasks under time pressure, including simulations. In order to support engineers in these complex simulation tasks, a framework is presented which coordinates and calculates simulations based on structured knowledge in a parallelized, decentralized way. Different approaches for a problem are simulated automatically and compared with each other. Therefore, complex problems, meaning large-scale ones that often consist of coupled problem parts, are decomposed into partial problems. Their approaches are subsequently processed separately each using the most suitable software tool. Cooperating software agents are utilized to achieve a flexible coordination of decentralized simulations. These autonomous software units communicate with each other to control the parallelized activities during a simulation project. The presented concept is evaluated based on the application fields of control design and multiphysics simulation. Hence, multi-agent systems (MAS) were generated prototypically using the developed framework. As an addition to the framework for parallel simulation, a concept for supplementing the MAS with a case-based reasoning component is presented. Using the case-based reasoning addition, the performance of the simulations was further improved. Due to the varying computation time of the different approaches, analyzed in parallel, results are often available earlier. The MAS is also capable of improving the quality of the results because of the automatic analysis and comparison of different approaches.

Abstract

This paper presents an intelligent approach to support engineers with performing computational simulation of new developments and prototypes. With multiple interacting physical effects and large three dimensional models the choice of the right solution strategy is crucial for a correct solution and an acceptable calculation time. The presented multi-agent system can solve these simulation tasks using distributed heterogeneous computation resources with the objective to reduce the calculation time. An important factor for the criterion time is the choice of the linear solver. Here a case-based reasoning concept is introduced to improve the decisions in the multi-agent system. Allowing each agent to solve its problem part by using appropriate solution methods, a decentralized architecture with autonomous software agents is provided.

Abstract

This paper presents an intelligent approach to support engineers with performing computational simulation of new developments and prototypes. With multiple interacting physical effects and large three dimensional models the choice of the right solution strategy is crucial for a correct solution and an acceptable calculation time. The presented multi-agent system can solve these simulation tasks using distributed heterogeneous computation resources with the objective to reduce the calculation time. An important factor for the criterion time is the choice of the linear solver. Here a case-based reasoning concept is introduced to improve the decisions in the multi-agent system. Allowing each agent to solve its problem part by using appropriate solution methods, a decentralized architecture with autonomous software agents is provided.

Abstract

Um Ingenieure bei Simulationsaufgaben zu unterstützen, wird ein Framework vorgestellt, das Simulationen basierend auf strukturiertem Wissen parallel und dezentral berechnet. Zur flexiblen Koordination der dezentralen Simulationen werden Softwareagenten eingesetzt. Evaluiert wird das vorgestellte System anhand des Anwendungsgebiets des Regelungsentwurfs.

Abstract

Um Ingenieure bei Simulationsaufgaben zu unterstützen, wird ein Framework vorgestellt, das Simulationen basierend auf strukturiertem Wissen parallel und dezentral berechnet. Zur flexiblen Koordination der dezentralen Simulationen werden Softwareagenten eingesetzt. Evaluiert wird das vorgestellte System anhand des Anwendungsgebiets des Regelungsentwurfs.

Abstract

Um Ingenieure bei Simulationsaufgaben zu unterstützen, wird ein Framework vorgestellt, das Simulationen basierend auf strukturiertem Wissen parallel und dezentral berechnet. Zur flexiblen Koordination der dezentralen Simulationen werden Softwareagenten eingesetzt. Evaluiert wird das vorgestellte System anhand des Anwendungsgebiets des Regelungsentwurfs.

Abstract

Based on autonomous software agents capable of calculating individual numerical field problems, a distributed method for solving transient field problems is presented. The software agents are running on distributed resources connected via a network and represent a dynamic calculation environment. Communication and data exchange between multiple agents enables their collaboration and allows decisions based on distributed overall knowledge. As unique characteristics, no central unit influences the solution process at any time. The presented simulation example and its evaluated calculation process proves the method to benefit from redundant resources.

Abstract

Based on autonomous software agents capable of calculating individual numerical field problems, a distributed method for solving transient field problems is presented. The software agents are running on distributed resources connected via a network and represent a dynamic calculation environment. Communication and data exchange between multiple agents enables their collaboration and allows decisions based on distributed overall knowledge. As unique characteristics, no central unit influences the solution process at any time. The presented simulation example and its evaluated calculation process proves the method to benefit from redundant resources.

Abstract

Based on autonomous software agents capable of calculating individual numerical field problems, a distributed method for solving transient field problems is presented. The software agents are running on distributed resources connected via a network and represent a dynamic calculation environment. Communication and data exchange between multiple agents enables their collaboration and allows decisions based on distributed overall knowledge. As unique characteristics, no central unit influences the solution process at any time. The presented simulation example and its evaluated calculation process proves the method to benefit from redundant resources.

Abstract

Zur Ermittlung des Systemverhaltens werden beim Engineering in Kombination mit der modellgestützten Entwicklung häufig Simulationen eingesetzt. Dieser Beitrag stellt einen agentenkoordinierten Ansatz für die parallele Simulation von multiphysikalischen Problemstellungen auf heterogenen Rechenressourcen vor. Durch die unterschiedlichen eingesetzten Simulationsmethoden steigt hierbei die Zuverlässigkeit beim Erreichen der Ergebnisse.

Abstract

Zur Ermittlung des Systemverhaltens werden beim Engineering in Kombination mit der modellgestützten Entwicklung häufig Simulationen eingesetzt. Dieser Beitrag stellt einen agentenkoordinierten Ansatz für die parallele Simulation von multiphysikalischen Problemstellungen auf heterogenen Rechenressourcen vor. Durch die unterschiedlichen eingesetzten Simulationsmethoden steigt hierbei die Zuverlässigkeit beim Erreichen der Ergebnisse.

Abstract

A novel approach is presented applying capabilities of software agent-based programming to numerical field computations. Distributed and autonomous calculation resources are used in analogy to a machine-to-machine system application for setting up and solving coupled simulations respecting the individual machine capabilities. Within the presented system, the involved machines interact cooperatively and comparatively. No central unit takes any influence to the solution process. Redundant resources do automatically and proactively add variance to the solution process by modifying their partial tasks based on negotiations between the involved resources. In that way, different numerical methods, solution strategies, and solver configurations are automatically evaluated as examples of the variety within coupled simulations. Partial results are dynamically integrated into an overall solver sequence, demonstrated on the coupled electric field computation of a patch antenna array. A quick provision of results is shown contemplating changes at calculation resource and vague user decisions for a nonlinear and bidirectionally coupled simulation of a 3-D multiphysics problem.

Abstract

A novel approach is presented applying capabilities of software agent-based programming to numerical field computations. Distributed and autonomous calculation resources are used in analogy to a machine-to-machine system application for setting up and solving coupled simulations respecting the individual machine capabilities. Within the presented system, the involved machines interact cooperatively and comparatively. No central unit takes any influence to the solution process. Redundant resources do automatically and proactively add variance to the solution process by modifying their partial tasks based on negotiations between the involved resources. In that way, different numerical methods, solution strategies, and solver configurations are automatically evaluated as examples of the variety within coupled simulations. Partial results are dynamically integrated into an overall solver sequence, demonstrated on the coupled electric field computation of a patch antenna array. A quick provision of results is shown contemplating changes at calculation resource and vague user decisions for a nonlinear and bidirectionally coupled simulation of a 3-D multiphysics problem.

Abstract

Based on autonomous software agents, capable of calculating individual numerical field problems, a distributed method for solving transient field problems is presented. The software agents are running on distributed resources connected via network and represent a dynamic calculation environment. Communication and data exchange between multiple agents enables their collaboration and allows decisions based on distributed overall knowledge. As unique characteristics, no central unit influences the solution process at any time. A presented simulation and its evaluated calculation process proves the method to benefit from redundant resources and outline its flexibility for non-permanent resources.

Abstract

This paper presents the latest development towards a software agent–based numerical framework for interdisciplinary coupled problems. The software agent framework is capable to incorporate multiple physical effects and combine multiple numerical methods through the usage of a neutral abstraction layer. The principles of software agent–based programming and the application in a numerical example are discussed. This paper focuses on dielectric heating and different methods for solving the time harmonic Maxwell equation. By reusing state of the art finite element method (FEM) and boundary element method (BEM) software tools and managing the interface between the different tools, this approach solves complicated and realistic three-dimensional problems. The functionality and efficiency of the framework are demonstrated on the dielectric heating inside a human head due to electromagnetic waves. A proper iterative coupling formulation for FEM and BEM is derived and numerically validated. The FEM-BEM coupling separates from existing approaches, because it takes advantage of new developments in the FEM, namely, the perfect handling of infinite domains through perfectly matched layers. Moreover, the simplicity and flexibility of the coupling method allow implementation in existing numerical codes.

Abstract

This paper presents the latest development towards a software agent–based numerical framework for interdisciplinary coupled problems. The software agent framework is capable to incorporate multiple physical effects and combine multiple numerical methods through the usage of a neutral abstraction layer. The principles of software agent–based programming and the application in a numerical example are discussed. This paper focuses on dielectric heating and different methods for solving the time harmonic Maxwell equation. By reusing state of the art finite element method (FEM) and boundary element method (BEM) software tools and managing the interface between the different tools, this approach solves complicated and realistic three-dimensional problems. The functionality and efficiency of the framework are demonstrated on the dielectric heating inside a human head due to electromagnetic waves. A proper iterative coupling formulation for FEM and BEM is derived and numerically validated. The FEM-BEM coupling separates from existing approaches, because it takes advantage of new developments in the FEM, namely, the perfect handling of infinite domains through perfectly matched layers. Moreover, the simplicity and flexibility of the coupling method allow implementation in existing numerical codes.

Abstract

Das hier vorgestellte Konzept zeigt eine Möglichkeit, Verfahren in der Entwicklung von automatisierten Systemen intelligent zu parallelisieren. Dies wird an den Beispielen der multiphysikalischen Simulation und des Regelungsentwurfs gezeigt. Oft sind viele verschiedene alternative Lösungsverfahren für eine Problemstellung bekannt. Zu entscheiden, welches das beste ist, ist zu Beginn eines Projekts meist nicht möglich. Die Zeit, diese Verfahren sequenziell zu untersuchen, hat ein Ingenieur durch die immer kürzeren Entwicklungszyklen, die nötig sind, um sich auf dem Markt zu behaupten, nicht. Das hier vorgestellte Agentensystem unterstützt den Ingenieur, indem es verschiedene Alternativen zur Lösung der jeweiligen Problemstellung untersucht, vergleicht und dem Nutzer die besten Lösungen präsentiert. Durch den Einsatz von Agenten, die miteinander kooperieren, können neben der Bewältigung von Abhängigkeiten auch Synergieeffekte zwischen den alternativen Lösungsmethoden erzielt werden.

Abstract

Das hier vorgestellte Konzept zeigt eine Möglichkeit, Verfahren in der Entwicklung von automatisierten Systemen intelligent zu parallelisieren. Dies wird an den Beispielen der multiphysikalischen Simulation und des Regelungsentwurfs gezeigt. Oft sind viele verschiedene alternative Lösungsverfahren für eine Problemstellung bekannt. Zu entscheiden, welches das beste ist, ist zu Beginn eines Projekts meist nicht möglich. Die Zeit, diese Verfahren sequenziell zu untersuchen, hat ein Ingenieur durch die immer kürzeren Entwicklungszyklen, die nötig sind, um sich auf dem Markt zu behaupten, nicht. Das hier vorgestellte Agentensystem unterstützt den Ingenieur, indem es verschiedene Alternativen zur Lösung der jeweiligen Problemstellung untersucht, vergleicht und dem Nutzer die besten Lösungen präsentiert. Durch den Einsatz von Agenten, die miteinander kooperieren, können neben der Bewältigung von Abhängigkeiten auch Synergieeffekte zwischen den alternativen Lösungsmethoden erzielt werden.

Abstract

A novel approach is presented applying capabilities of software agent based programming to numerical field computations. Distributed and autonomous calculation resources are used in analogy to a machine to machine system application for setting up and solve coupled simulations respecting the individual machine capabilities. Within the presented system the involved machines interact cooperatively and comparatively. Redundant resources do automatically and proactively add variance to the solution process by modifying their partial tasks based on negotiations between the involved resources. In that way different numerical methods, solution strategies and solver configurations are automatically evaluated as examples of the variety of coupled simulations and dynamically integrated into an overall solver sequence shown for the coupled electric field computation of a patch antenna array. A quick provision of results contemplating changes at calculation resource and vague user decisions is shown for a nonlinear and bi-directionally coupled simulation of a 3d multiphysics problem.

Abstract

A novel approach is presented applying capabilities of software agent based programming to numerical field computations. Distributed and autonomous calculation resources are used in analogy to a machine to machine system application for setting up and solve coupled simulations respecting the individual machine capabilities. Within the presented system the involved machines interact cooperatively and comparatively. Redundant resources do automatically and proactively add variance to the solution process by modifying their partial tasks based on negotiations between the involved resources. In that way different numerical methods, solution strategies and solver configurations are automatically evaluated as examples of the variety of coupled simulations and dynamically integrated into an overall solver sequence shown for the coupled electric field computation of a patch antenna array. A quick provision of results contemplating changes at calculation resource and vague user decisions is shown for a nonlinear and bi-directionally coupled simulation of a 3d multiphysics problem.

Abstract

A novel approach is presented using software agents for an iterative and distributed solution of multiphysics problems. Total convergence is reached by combining individual functionalities of different agents within a multi agent system. Single physics agents cooperatively solve the problem based on specialized, commercial or in-house code. The autonomy of each agent grants a problem dependent solving behaviour without the requirement of a predefined solver sequence. As numerical example, a coupled 3D electromagnetic wave propagation and heat transfer problem inside a waveguide is considered. The required three software agents are described in detail. The created framework solves multiphysics simulations coupled by field values or values exchanged on discrete ports. Here we focus at weak unidirectional and bidirectional field coupled multiphysics problems.

Abstract

A novel approach is presented using software agents for an iterative and distributed solution of multiphysics problems. Total convergence is reached by combining individual functionalities of different agents within a multi agent system. Single physics agents cooperatively solve the problem based on specialized, commercial or in-house code. The autonomy of each agent grants a problem dependent solving behaviour without the requirement of a predefined solver sequence. As numerical example, a coupled 3D electromagnetic wave propagation and heat transfer problem inside a waveguide is considered. The required three software agents are described in detail. The created framework solves multiphysics simulations coupled by field values or values exchanged on discrete ports. Here we focus at weak unidirectional and bidirectional field coupled multiphysics problems.

Abstract

In this paper a framework for large scale coupled simulation raising from Maxwell’s equations is presented.

Abstract

In this paper a framework for large scale coupled simulation raising from Maxwell’s equations is presented.

Abstract

The increasing cost pressure on Intra-Logistics systems due to the global competition in Intra-Logistics systems motivates planners to decrease planning durations in order to stay cost efficient. Conversely, the rough planning of Intra-Logistics systems is a time consuming, complex task, whose progress is primarily driven by the experience of the planning team. Consequently, the planning is opaque. In order to reduce the planning duration and to systemize the planning this paper presents a rule-based concept for an agent-based assistance system to support the planner during the rough planning of Intra-Logistics systems. The assistance system provides an overview of possible solutions regarding to specified requirements by generating and evaluating all possible solution alternatives.

Abstract

Aufgrund von vielen Freiheitsgraden bei der Entwicklung von automatisierten Systemen ergibt sich eine hohe Anzahl möglicher Entwicklungsvarianten. Da die Entwicklung ein zeitaufwendiger, iterativer Prozess ist, die Entwicklungszeiten aber aufgrund des Kostendrucks sinken müssen, kann der Ingenieur nur eine sehr begrenzte Anzahl dieser Entwicklungsvarianten berücksichtigen und entwickeln. Die Erstellung der betrachteten Entwicklungsvarianten ist daher heute stark vom Wissen und von den Erfahrungen des Ingenieurs abhängig. Dies führt bereits zu Beginn der Entwicklung zu einer Einschränkung der zu entwickelnden Varianten, ohne dass diese für andere Personen zwingend nachvollziehbar ist. In diesem Beitrag wird ein Konzept für ein agentenbasiertes Assistenzsystem vorgestellt, mit dessen Hilfe der Ingenieur alle Varianten bei der Entwicklung berücksichtigen kann. Die Grundlage für dieses Konzept bilden Komponenten, die als intelligente Planungsobjekte modelliert werden. Ein automatisiertes System wird hierbei als ein Zusammenschluss aus unterschiedlichen Komponenten wie Motor, Kabine etc. betrachtet, die unterschiedliche Funktionen wie beispielsweise Fördern erfüllen. Der Zusammenschluss aus den Komponenten erfüllt die geforderte Gesamtfunktionalität.

Abstract

Aufgrund von vielen Freiheitsgraden bei der Entwicklung von automatisierten Systemen ergibt sich eine hohe Anzahl möglicher Entwicklungsvarianten. Da die Entwicklung ein zeitaufwendiger, iterativer Prozess ist, die Entwicklungszeiten aber aufgrund des Kostendrucks sinken müssen, kann der Ingenieur nur eine sehr begrenzte Anzahl dieser Entwicklungsvarianten berücksichtigen und entwickeln. Die Erstellung der betrachteten Entwicklungsvarianten ist daher heute stark vom Wissen und von den Erfahrungen des Ingenieurs abhängig. Dies führt bereits zu Beginn der Entwicklung zu einer Einschränkung der zu entwickelnden Varianten, ohne dass diese für andere Personen zwingend nachvollziehbar ist. In diesem Beitrag wird ein Konzept für ein agentenbasiertes Assistenzsystem vorgestellt, mit dessen Hilfe der Ingenieur alle Varianten bei der Entwicklung berücksichtigen kann. Die Grundlage für dieses Konzept bilden Komponenten, die als intelligente Planungsobjekte modelliert werden. Ein automatisiertes System wird hierbei als ein Zusammenschluss aus unterschiedlichen Komponenten wie Motor, Kabine etc. betrachtet, die unterschiedliche Funktionen wie beispielsweise Fördern erfüllen. Der Zusammenschluss aus den Komponenten erfüllt die geforderte Gesamtfunktionalität.

Abstract

This paper puts forward a novel concept of a Remote Problem Management System that allows an industrial automation system continuing to work with available functions during the appearance of a problem. The concept of the Remote Problem Management System consists of passive and active management to handle problems. The passive management aims at handling known problems by means of receiving the Fault-ID from a Fault-Diagnosis System, accessing the producers’ knowledge base and getting available functions. On the contrary, the active management attains to handle unknown problems via processing diagnosis results, analyzing the sphere of the influence, confirming available functions and storing these information in the producers’ knowledge base with the help of this system, the producer is able to manage the problems in his sold machines remotely and the user can use his machine with available functions before the machine is repaired.

Abstract

This paper puts forward a novel concept of a Remote Problem Management System that allows an industrial automation system continuing to work with available functions during the appearance of a problem. The concept of the Remote Problem Management System consists of passive and active management to handle problems. The passive management aims at handling known problems by means of receiving the Fault-ID from a Fault-Diagnosis System, accessing the producers’ knowledge base and getting available functions. On the contrary, the active management attains to handle unknown problems via processing diagnosis results, analyzing the sphere of the influence, confirming available functions and storing these information in the producers’ knowledge base with the help of this system, the producer is able to manage the problems in his sold machines remotely and the user can use his machine with available functions before the machine is repaired.

Abstract

In industrial automation systems, when a problem occurs at run-time and no technician is available instantly, it can result in the stopping of the whole industrial automation system. Often, the occurred problem addresses only few system functions. Theoretically, other functions can be performed. However, in most of the cases, none of the system functions can be used. In order to prevent the stop of the whole system and guarantee the performance of still available functions, this paper proposes an intelligent multi-agent based problem management system. This system receives the diagnosis results from the industrial automation system by means of a local communication agent. Problems are discussed in two cases, i.e. known problems and unknown problems. For known problems, the intelligent multi-agent based problem management system directly accesses the database to get the available functions and sends this information to industrial automation systems. For unknown problems, it analyzes the effect of problems as well as the scope of them in order to identify available functions with the help of different agents. Thus, these information about available functions are stored into the database and are sent to industrial automation systems. Consequently, the industrial automation system can continue to work with the available functions. Hence, the intelligent multi-agent based problem management system can enhance the availability of industrial automation systems through ensuring available functions and preventing long system break-down.

Abstract

This paper puts forward a novel concept of a Remote Problem Management System that allows an industrial automation system continuing to work with available functions during the appearance of a problem. The concept of the Remote Problem Management System consists of passive and active management to handle problems. The passive management aims at handling known problems by means of receiving the Fault-ID from a Fault-Diagnosis System, accessing the producers’ knowledge base and getting available functions. On the contrary, the active management attains to handle unknown problems via processing diagnosis results, analyzing the sphere of the influence, confirming available functions and storing these information in the producers’ knowledge base with the help of this system, the producer is able to manage the problems in his sold machines remotely and the user can use his machine with available functions before the machine is repaired.

Abstract

In industrial automation systems, when a problem occurs at run-time and no technician is available instantly, it can result in the stopping of the whole industrial automation system. Often, the occurred problem addresses only few system functions. Theoretically, other functions can be performed. However, in most of the cases, none of the system functions can be used. In order to prevent the stop of the whole system and guarantee the performance of still available functions, this paper proposes an intelligent multi-agent based problem management system. This system receives the diagnosis results from the industrial automation system by means of a local communication agent. Problems are discussed in two cases, i.e. known problems and unknown problems. For known problems, the intelligent multi-agent based problem management system directly accesses the database to get the available functions and sends this information to industrial automation systems. For unknown problems, it analyzes the effect of problems as well as the scope of them in order to identify available functions with the help of different agents. Thus, these information about available functions are stored into the database and are sent to industrial automation systems. Consequently, the industrial automation system can continue to work with the available functions. Hence, the intelligent multi-agent based problem management system can enhance the availability of industrial automation systems through ensuring available functions and preventing long system break-down.

Abstract

In industrial automation systems, when a problem occurs at run-time and no technician is available instantly, it can result in the stopping of the whole industrial automation system. Often, the occurred problem addresses only few system functions. Theoretically, other functions can be performed. However, in most of the cases, none of the system functions can be used. In order to prevent the stop of the whole system and guarantee the performance of still available functions, this paper proposes an intelligent multi-agent based problem management system. This system receives the diagnosis results from the industrial automation system by means of a local communication agent. Problems are discussed in two cases, i.e. known problems and unknown problems. For known problems, the intelligent multi-agent based problem management system directly accesses the database to get the available functions and sends this information to industrial automation systems. For unknown problems, it analyzes the effect of problems as well as the scope of them in order to identify available functions with the help of different agents. Thus, these information about available functions are stored into the database and are sent to industrial automation systems. Consequently, the industrial automation system can continue to work with the available functions. Hence, the intelligent multi-agent based problem management system can enhance the availability of industrial automation systems through ensuring available functions and preventing long system break-down.

Abstract

Das Thema Industrie 4.0 verspricht umwälzende Veränderungen in der automatisierten Fertigung, der Produktionsorganisation und den Prozessen in der Industrie. Anhand einer automatisierungstechnischen Verbundanlage im Sinne eines Zusammenschlusses von Teilanlagen der beteiligten Institute werden Potentiale von Industrie 4.0 aufgezeigt und in Bezug auf die Automatisierungstechnologien diskutiert. Anhand des Anlagenverbundes werden insbesondere Aspekte des Managements von Flexibilität sowie die Möglichkeiten des Informationsaustausches aufgrund von Dezentralität und Vernetzung verdeutlicht.

Abstract

Das Thema Industrie 4.0 verspricht umwälzende Veränderungen in der automatisierten Fertigung, der Produktionsorganisation und den Prozessen in der Industrie. Anhand einer automatisierungstechnischen Verbundanlage im Sinne eines Zusammenschlusses von Teilanlagen der beteiligten Institute werden Potentiale von Industrie 4.0 aufgezeigt und in Bezug auf die Automatisierungstechnologien diskutiert. Anhand des Anlagenverbundes werden insbesondere Aspekte des Managements von Flexibilität sowie die Möglichkeiten des Informationsaustausches aufgrund von Dezentralität und Vernetzung verdeutlicht.

Abstract

Das Thema Industrie 4.0 verspricht umwälzende Veränderungen in der automatisierten Fertigung, der Produktionsorganisation und den Prozessen in der Insdustrie. In diesem Beitrag werden am Beispiel einer automotisierungstechnischen Verbundanlage im Sinne eines Zusammenschlusses von Teilanlagen der beteiligten Institute Potenziale von Industrie 4.0 aufgezeigt und in Bezug auf die Automatisierungstechnolgien diskutiert. Anhand des Anlagenverbundes werden vor allem Aspekte des Managements von Flexibiltät sowie die Möglichkeiten des INformationsaustausches aufgrund von Dezentralität und Vernetzung verdeutlicht.

Abstract

Das Thema Industrie 4.0 verspricht umwälzende Veränderungen in der automatisierten Fertigung, der Produktionsorganisation und den Prozessen in der Insdustrie. In diesem Beitrag werden am Beispiel einer automotisierungstechnischen Verbundanlage im Sinne eines Zusammenschlusses von Teilanlagen der beteiligten Institute Potenziale von Industrie 4.0 aufgezeigt und in Bezug auf die Automatisierungstechnolgien diskutiert. Anhand des Anlagenverbundes werden vor allem Aspekte des Managements von Flexibiltät sowie die Möglichkeiten des INformationsaustausches aufgrund von Dezentralität und Vernetzung verdeutlicht.

Abstract

A defective component in an industrial automation system affects only a limited number of sub functions. However, the affected sub functions often lead to break down of the whole system. The goal of this paper is to propose an intelligent agents-based concept for a Problem Management System (IAPMS) to enhance the reliability of industrial automation systems by resolving not only the known problems but also the unknown problems. In this paper, six types of component agents represent all the necessary components of an industrial automation system and a coordination agent type orchestrates the coordination between the component agents. The component agents detect the defective component by using the existing diagnosis system. On one hand, the component agents and the coordination agent could solve the known problems by using the pre-set measures. On the other hand, since no measures for an unknown problem exist, the corresponding component agents negotiate with the coordination agent to keep the unaffected sub functions alive; hence the system can be further used.

Abstract

A defective component in an industrial automation system affects only a limited number of sub functions. However, the affected sub functions often lead to break down of the whole system. The goal of this paper is to propose an intelligent agents-based concept for a Problem Management System (IAPMS) to enhance the reliability of industrial automation systems by resolving not only the known problems but also the unknown problems. In this paper, six types of component agents represent all the necessary components of an industrial automation system and a coordination agent type orchestrates the coordination between the component agents. The component agents detect the defective component by using the existing diagnosis system. On one hand, the component agents and the coordination agent could solve the known problems by using the pre-set measures. On the other hand, since no measures for an unknown problem exist, the corresponding component agents negotiate with the coordination agent to keep the unaffected sub functions alive; hence the system can be further used.

Abstract

A defective component in an industrial automation system affects only a limited number of sub functions. However, the affected sub functions often lead to break down of the whole system. The goal of this paper is to propose an intelligent agents-based concept for a Problem Management System (IAPMS) to enhance the reliability of industrial automation systems by resolving not only the known problems but also the unknown problems. In this paper, six types of component agents represent all the necessary components of an industrial automation system and a coordination agent type orchestrates the coordination between the component agents. The component agents detect the defective component by using the existing diagnosis system. On one hand, the component agents and the coordination agent could solve the known problems by using the pre-set measures. On the other hand, since no measures for an unknown problem exist, the corresponding component agents negotiate with the coordination agent to keep the unaffected sub functions alive; hence the system can be further used.

Abstract

Viele Unternehmen und Institute beschäftigen sich aktuell mit dem Begriff Industrie 4.0 und seiner genauen Auslegung. Daraus resultierend existieren viele verschiedene Vorstellungen darüber, was unter dem Begriff genau zu verstehen ist. Ein Kernthema ist die Auflösung der starren Strukturen und Hierarchien der Ebenen der Automatisierungspyramide in den Unternehmen und über Unternehmensgrenzen hinweg. Realisiert wird dieses durch eine gesteigerte vertikale (über die Ebenen der Automatisierung hinweg) und horizontale (unterschiedliche ITSysteme) Vernetzung (vgl. Beitrag Vogel-Heuser „Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik“).

Abstract

Viele Unternehmen und Institute beschäftigen sich aktuell mit dem Begriff Industrie 4.0 und seiner genauen Auslegung. Daraus resultierend existieren viele verschiedene Vorstellungen darüber, was unter dem Begriff genau zu verstehen ist. Ein Kernthema ist die Auflösung der starren Strukturen und Hierarchien der Ebenen der Automatisierungspyramide in den Unternehmen und über Unternehmensgrenzen hinweg. Realisiert wird dieses durch eine gesteigerte vertikale (über die Ebenen der Automatisierung hinweg) und horizontale (unterschiedliche ITSysteme) Vernetzung (vgl. Beitrag Vogel-Heuser „Herausforderungen und Anforderungen aus Sicht der IT und der Automatisierungstechnik“).

Abstract

Manufacturing automation is an industrial field of application in which agent-based concepts are of a high relevance. Flexibility in engineering, quick and easy adaption and evaluation of the systems are key issues in the domain and can significantly be improved using the paradigm of multi-agent systems. The approach of agent technology is very suitable to conceive assistant systems or control architectures which can be used throughout the engineering and the operation of automated manufacturing systems. This article presents an overview of the research undertaken the past years which has yielded workable concepts for typical use cases of the industry.

Abstract

Manufacturing automation is an industrial field of application in which agent-based concepts are of a high relevance. Flexibility in engineering, quick and easy adaption and evaluation of the systems are key issues in the domain and can significantly be improved using the paradigm of multi-agent systems. The approach of agent technology is very suitable to conceive assistant systems or control architectures which can be used throughout the engineering and the operation of automated manufacturing systems. This article presents an overview of the research undertaken the past years which has yielded workable concepts for typical use cases of the industry.

Abstract

Test case prioritization systems are useful tools to support test managers in planning test runs in regression testing. These systems evaluate information about test cases to find the best order for the test case execution. During a system's life cycle, a lot of test runs are usually performed. To give optimal support and to improve the results from test run to test run, the prioritization systems need to react dynamically to events, which occur during the different phases development, test and operation of the life cycle. They have to consider changes, unexpected faults found during operation, and many other events. This article describes an agent-based approach to improve a test case prioritization system by considering dynamic events for the test plan generation.

Abstract

Test case prioritization systems are useful tools to support test managers in planning test runs in regression testing. These systems evaluate information about test cases to find the best order for the test case execution. During a system's life cycle, a lot of test runs are usually performed. To give optimal support and to improve the results from test run to test run, the prioritization systems need to react dynamically to events, which occur during the different phases development, test and operation of the life cycle. They have to consider changes, unexpected faults found during operation, and many other events. This article describes an agent-based approach to improve a test case prioritization system by considering dynamic events for the test plan generation.