Jürgen Elger

Engineering Processes for Decentralized Factory Automation Systems

The necessity to improve the current automation concepts for cost reduction in factory automation represents a widely discussed problem. Research has developed solutions for this problem area for quite some time based on decentralized automation concepts (e.g., holonic systems, agent systems). For an overview of agent-oriented systems, please refer to (Jennings, 2000; Weis, 2002); for agent-oriented or holonic automation systems, see (Parunak 1998; Shen et. al, 2006; Barata, 2001; Wagner et. al., 2003). However, industrial companies have shown reluctance concerning a broad application in practice. The reasons reside mainly in lacking engineering methods for systematic implementation in industrial businesses (Hall et. al., 2005) and lacking reliable evaluation of the consequences for application domains over the entire life cycle (Lu & Jafari, 2007). The main goal for the development of decentralized automation concepts and systems is to achieve flexibility in factory automation systems, driven by ever more rapidly changing production conditions, such as order variations, changing products, load variations, or plugp Wagner & Goehner, 2006). Hence, the value promised by decentralized automation concepts mainly resides in the improvement of operative parameters of a plant, for instance, through more flexibility of usage, higher efficiency, or availability. Such parameters were evaluated based on prototypes, as well as by means of simulation, and were verified with a relatively good validity (Sundermeyer & Bussmann, 2001; Thramboulidis, 2008). However, the costs for introducing and applying decentralized automation concepts and systems – in terms of total cost of ownership (TCO) – have not been properly investigated yet, neither in science nor in industrial application. The reason is that we know much about the operation phase behaviour of production facilities using decentralized automation systems, but there exists hardly any explanation of the impact, in terms of benefits and risks, on the entire industrial life cycle (Habib 2007). In addition to operating costs, the second most important aspect of TCO lies in the activities and processes for engineering (design, realization, and commissioning) of production facilities. The related cost potential is certainly significant. In 2005, automotive manufacturers identified the portion of 1

Mechatronic models as a driver for digital plant engineering

The digital plant is still a vision since standard engineering tools and systems currently address only specific areas or phases in the engineering process and engineering methodologies are difficult to derive. This paper points out the importance of mechatronic domain models for integrated engineering tool and system landscapes and their significance as a driver for digital plant engineering. A strategy for developing an integrated tool and system landscape is suggested based on user-centric mechatronic domain models. In addition, the definition of mechatronic domain models is discussed.

Evaluation of effectiveness and impact of decentralized automation

The necessity to improve the current automation concepts for cost reduction in plant engineering represents a widely discussed problem. Although research has been developing solutions for this problem area for quite some time on the basis of decentralized automation concepts, industrial companies have been showing reluctance concerning their broad application in practice. This contribution discusses the potential for use of decentralized automation of industrial plants in the context of strategic developments. The ramifications of such technological perspectives to the different stakeholders in an industrial life cycle, their interests and their processes are discussed and a method for the evaluation of decentralized solutions over their entire life cycle is presented, offering a basis for a well founded assessment of their cost effectiveness.

Business processes and technical processes a comprehensive meta model for execution and development

The interaction between business processes and technical processes is getting more and more important. Throughout this paper, we present how concepts that are used in automation technology can be transferred into concepts that are suitable for use in business process modeling, too. An important aspect is the description of the procedures which have to be executed. In contrast to technical systems, humans as executing agents can, but do not have to follow predefined procedures due to their ability to use their knowledge to work independently in different situations. In a second part, the paper discusses the generation of business processes by project business processes on a meta model, and provides a reference model for a project business layer model.

Optimization of the information chain within the engineering process of production systems

Engineering processes of complex production systems have an increasing impact on the life cycle costs of the production systems. Thus, it is naturally of interest to optimize them with respect to correctness and efficiency. Therefore, methods for process modeling and problem identification are required, applicable also by engineers not familiar with process modeling but with their own engineering process. Within this paper such a method is described and first application experiences are given.

Evaluation of the importance of mechatronical concepts in practical applications

Mechatronical engineering is a strong trend within engineering of manufacturing systems. To enable a most efficient and beneficiary application of mechatronical engineering within engineering organizations the mechatronical engineering has to be based on basic concepts realizing the mechatronical thinking and supporting the user. Even though such concepts have been identified they might be of different interest depending on application cases, industry focus, engineering phases, and much more. Within this paper the results of an expert survey will be given enabling the estimation of the practical impact of mechatronical concepts and the believes of practitioners about the moment of availability of such concepts in engineering tools or tool chains.

Zusammenfassung und Fazit: Das Internet der Dinge als neues Vorgehensmodell

Fur eine systematische Analyse der Auswirkungen dezentraler Automatisierungssysteme wurde wie in Kap. 16 beschrieben eine Referenz-Modell Methodik entwickelt. Dieses Vorgehen wurde angewendet um die Auswirkungen des ebenfalls in diesem Kapitel dargestellten modular-mechatronisch motivierten Automatisierungssystems zu untersuchen.

Entwicklungen in der Automatisierungstechnik

Der Artikel beschreibt die Veranderungen in der Automatisierungstechnik in den letzten Jahren. Er verweist auf neue Kommunikationstechniken und ihre Moglichkeiten und formuliert die Erwartung, dass die Automatisierungstechnik eine ahnlich tiefgreifende Veranderung durchlaufen wird, wie sie die IT-Landschaft in der Folge des Internet-Booms durchlaufen hat.

Der Lebenszyklus heutiger Materialf lusssysteme – eine Übersicht

Aktuelle Ansatze fur dezentrale Automatisierungssysteme werden insbesondere wegen der damit verbundenen, gewunschten Verbesserungen und Vorteile wahrend des Betriebs untersucht. Die Nutzung dieser Systeme hat allerdings weitreichende Folgen – nicht nur fur den Betrieb sondern insbesondere fur das Engineering, in welchem zunachst die Grundlagen fur die neue Technologie gelegt und sie anschliesend projektspezifisch angewandt werden mussen. Die Einfuhrung solcher Systeme ist damit erst dann tragbar, wenn die Auswirkungen auf den gesamten Lebenszyklus von Automatisierungslosungen auch deutlich werden. Das Problem hierbei ist, dass dies vor einer breiten Praxisanwendung geschehen muss. Ein Vergleich auf Basis monetarer Zahlen ist deshalb schwer moglich.

Modellbasiertes Requirements Engineering

Engineering und Betrieb groser Materialflusssysteme sind aufgrund der hohen Komponentenanzahl sowie der herzustellenden Schnittstellen sehr komplex. Komplexitat tritt in allen Phasen der Lebensdauer logistischer Systeme auf. Die Optimierung von Kosten, Qualitat und Leistung einzelner Bestandteile eines Systems wirkt sich in der Regel auf den gesamten Life Cycle aus. Vor diesem Hintergrund ist die Wirksamkeit technischer und organisatorischer Optimierungsmasnahmen an den unterschiedlichen Anforderungen zu spiegeln, die im Lebenszyklus eines Logistiksystems auftreten.