myJoghurt des AIS ist Teil des White-Papers des japanischen Wirtschaftsministerium zur Industrie 4.0.

Industrie 4.0 requires intelligent self-aware adaptive machines and plants that know their abilities. In this paper, we propose different qualitative and quantitative measures to evaluate reconfiguration abilities of automated production systems in the context of Industrie 4.0. This paper presents first measures to quantify different reconfiguration abilities of automated production systems, using different adaptive strategies focusing on fault compensation. For an application example, a lab size plant, the measures will be explained and calculated.

The increasing demand for adaptive and flexible machines and plants raises the need for components and systems that can be dynamically reconfigured. Therefore, production facilities are especially needed to allow for connecting or disconnecting machine modules at runtime to allow for flexible production orders and varying product types. Many highly sophisticated approaches e.g. multi-agent systems and service-oriented architectures support reconfiguration at the application layer, but the communication link between the components’ hardware has not yet been appropriately considered. However, the deterministic behavior of a field-bus is required to perform such a system reconfiguration of plants without violating the maximum cycle time of control applications. Considering these constraints, two different approaches are presented and discussed in this paper – a single-master and a multi-master approach. Based on an extension of the standard EtherCAT state machine, it is shown how flexibility can increase by reconfiguration of the field-bus communication. An evaluation of the reconfiguration time illustrates the impact to the control application.

The operation of industrial automated production systems (aPS) usually requires human operators that observe and, if necessary, intervene to keep aPS in steady operation. Inside the distributed control system (DCS) of an aPS, notifications are generated by an alarm management system (AMS) and visualized, informing operators about critical aPS situations, e.g. faults of a device. Since a huge number of notifications are usually configured inside the AMS, operators nowadays often face the problem of receiving more notifications than they can physically address. This paper proposes an approach, which allows automatic identification of alarm floods by using criteria-based search strategies. In order to address the problem statement, four hypotheses are stated. To evaluate the proposed algorithm regarding its ability to identify causally dependent notifications, historical notification logs of real industrial aPS are analyzed. For this purpose, notification logs of eight existing industrial aPS as well as the assessment of industrial experts are taken into account.

This paper comprises a SysML-based approach to support the model-driven engineering (MDE) of Manufacturing Automation Software Projects (MASP). The Systems Modeling Language (SysML) is adapted to define the SysML-AT (SysML for automation), a specialized language profile that covers (non-)functional requirements, corresponding software applications and properties of proprietary hardware components. Furthermore, SysML-AT supports an automated software generation for run-time environments conforming to IEC 61131-3. A prototypical tool support was realized for adapted SysML Parametric Diagrams (PD) inside an industrial automation software development tool. Coupling the model editor and online data from the provided run-time environment enables direct debugging inside the model. The approach was evaluated by several case studies and additional usability experiments. With the latter, the suitability of the MDE approach for future users was proven.

Due to fierce competition, short product lifecycles and fluctuating markets, there is an increasing demand for flexible and fault tolerant systems in automated manufacturing. Multi-Agent System (MAS) can help meeting these demands by enabling fast reconfigurations and smart fault handling and compensation. A previously developed MAS, distributed on real time and non-real time capable platforms, can increase these benefits by combining the advantages of both, real time and nonreal time implementations of MAS when involved in controlling (a part of) a manufacturing plant. Even though different communication concepts have been developed and are provided within this MAS architecture, connections to other industrial IT systems such as Enterprise Resource Planning (ERP) or third party MAS implementations have not been included. To enable maximizing the system’s flexibility, a complete immersion of the MAS into the industrial IT environment needs to be provided. This paper proposes communication concepts, a running example and evaluation of the concepts for this problem.

Todays increasing volatility of market demands and customer requirements are forcing industrial enterprises to realize and ensure an increased flexibility of production systems. Since current automation concepts and architectures for production systems do not provide the required flexibility sufficiently, new approaches have to be developed. This paper proposes an approach that implements the quickly evolving concept of Cyber-Physical Systems (CPS) for the special case of production systems by means of software agents. A joined demonstrator of such Cyber-Physical Production System (CPPS) is described and used for the evaluation of the proposed multi-agent approach.

Häufig wird Industrie 4.0 und CPS (Cyber-Physical Systems) bzw. CPPS (Cyber- Physical Production Systems) in Zusammenhang mit Automotive oder dem klassischen Maschinen- und Anlagenbau und somit dem Bereich der Fertigungstechnik in Verbindung gebracht. Doch auch in der Prozessindustrie führt Industrie 4.0 zu neuen Strategien, z.B. in der Flexibilisierung der Produktion oder der Wartungsunterstützung etc.

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“).

Die erheblich gesteigerte vertikale und horizontale Integration von Cyber-Physical- Production-Systems (CPPS) führt zu einer deutlichen Veränderung der technischen Strukturen im Unternehmen und über Unternehmensgrenzen hinweg. Zum einen sind in Zukunft alle Daten aus den verschiedenen IT-Systemen einer Produktionsanlage überall und zu jeder Zeit global verfügbar, zum anderen kommunizieren die Anlagen/Teilanlagen und die Geräte in den Anlagen mehr und mehr autonom und ohne Eingriff des Menschen. Folge ist eine Flexibilisierung, aber auch eine gesteigerte Komplexität der Produktionsanlagen.

Die kollaborative Fertigung eines gemeinsamen Produktes auf unterschiedlichen Fertigungsmaschinen, welche sowohl örtlich im Unternehmen verteilt oder unternehmensübergreifend stattfindet, ist eine Herausforderung der zukunftsgerichteten Produktion im Rahmen der vierten industriellen Revolution. Dies umfasst die Verkettung von Produktionsanlagen und Robotern mit einer heterogenen Steuerungsarchitektur bei gleichzeitiger dynamischer Verwaltung der an der Produktion und Wartung beteiligten Produktionseinheiten. Ein weiteres Ziel neben der Vernetzung von Anlagen und Steuerungen ist die Integration von aus dem Multimedia-Bereich bekannter Komponenten zur Einbindung des Menschen. Der Beitrag beschreibt die Integration der Aspekte Vernetzung und Auftragsmanagement mit der Losgröße eins und Berücksichtigung der Echtzeit-Randbedingung bei Produktionsmaschinen, hier roboterbasierten Produktionsmaschinen. Zur Umsetzung der genannten Aspekte wird ein Multiagentennetzwerk angewandt, welches intelligente, heterogene Softwareteile vernetzt und eine Optimierung der Abläufe ermöglicht.

Der Begriff Industrie 4.0 ist aktuell in aller Munde und wird auch stark diskutiert. Die von der Bundesregierung gestartete Initiative soll den Industriestandort Deutschland zukunftssicher und konkurrenzfähig halten. Viele Firmen und Forschungsinstitute beschäftigen sich aktuell mit dem Thema und entwickeln neue Ansätze, welche mithilfe von Demonstratoren veranschaulicht werden sollen. Der Begriff Industrie 4.0 wird dabei oft mit unterschiedlicher Bedeutung verwendet und ist deshalb schwer greifbar.

Motivated by the huge effort for adapting discrete field level automation software in case of (even minor) modifications of the technical system, this paper presents an approach to support the engineering and re-engineering of open-loop control software. In contrast to implement what a plant has to do, we suggest a novel modelling approach which enables describing what a plant is able to do. Based on an extension of the Unified Modelling Language meta model, an object-oriented approach for describing a manufacturing system’s state space in a consolidated way is proposed. The strict, declarative semantics of ontologies is utilized to automatically reason about this model for determining the manufacturing system’s state space and deriving an optimal operation sequence to be implemented.

Engineering of manufacturing systems involves multiple disciplines, e.g. mechanical engineering, electrical engineering and software engineering. Due to the increasing functionality of automation systems and, thus, their increasing complexity, reuse of automation control software is currently achieved through copy, paste and modify. Therefore, module libraries containing verified control software are being developed to overcome these challenges. However, due to the differences of module structures in the disciplines participating in automation engineering, a pure syntactic software description based on inputs and outputs is not sufficient. Moreover, automatic retrieval of automation control software is needed to support the engineer implementing the entire system. In this paper, an approach enabling automatic retrieval of software units based on a module’s hardware description by means of ontologies and customized rule-based inference is proposed.

This paper presents the elaboration of a concept to develop and implement real-time capable industrial automation software that increases the dependability of production automation systems by means of soft sensors. An application example with continuous behavior as it is a typical character treat of process automation is used to illustrate the initial requirements. Accordingly, the modeling concept is presented which supports application development and which is supplemented by an implementation approach for standard automation devices, e.g. Programmable Logic Controllers (PLC). The paper further comprises an evaluation which adapts the concept for two use cases with discrete behavior (typical character treat of manufacturing automation) and validates the initially imposed requirements.