Semantic Modelling of Control Logic in Automation Systems - Knowledge-Based Support of the Engineering and Operation of Control Logic in Building and Industrial Automation Systems

Automatisierungssysteme schaffen in vielen Bereichen die Grundlagen, auf denen heutige, moderne Industriegesellschaften basieren. Obwohl in der Vergangenheit wichtige Errungenschaften in der Forschung zur Automatisierungstechnik erreicht wurden, bestehen weiterhin Herausforderungen bezüglich des Engineerings und des Betriebs von Automatisierungssystemen, die die Nutzung und den Einsatz dieser Systeme erschweren. Als Gründe für diese Probleme sind die Komplexität dieser Systeme durch ihre schiere Grö{\ss}e und ihre Komplexität aufgrund der Kombination von cyber und physikalischen Komponenten zu nennen. Des Weiteren führt der zunehmende Einsatz von Informations- und Kommunikationstechnologien zu einer weiteren Verflechtung dieser System über ihre bisherigen, hierarchischen Strukturen hinaus und damit zu einer weiteren Zunahme der Komplexität. Eine weitere Herausforderung ist, dass für ein reibungsloses Engineering und einen reibungslosen Betrieb dieser Systeme eine Vielzahl von Beteiligten aus unterschiedlichen Fachdisziplinen zusammenarbeiten müssen. Dies wird durch die Heterogenität der eingesetzten Softwarewerkzeuge und Datenformate erschwert, die einen automatisierten Austausch von Wissen behindern. Folglich besteht ein dringender Bedarf an Methoden, die die wissensintensiven Aufgaben in Zusammenhang mit dem Engineering und dem Betrieb von Automatisierungssystemen im Kontext heterogener Softwarewerkzeuge und Datenformate unterstützen und, als Antwort auf die Komplexitätszunahme, automatisieren. Eine Voraussetzung für die Entwicklung solcher Methoden ist die formale Repräsentation von Domänenwissen mit Hilfe eines Modells. Die Analyse des Stands der Technik in dieser Arbeit zeigt, dass kein Ansatz existiert der es erlaubt einen wesentlichen Bestandteil der Domäne Automatisierungssystem, die Domänen Regelung und Steuerung und Regelungslogik, explizit zu beschreiben und dieses Wissen mit angrenzenden Domänen zu vernetzen. Ein wesentlicher Beitrag dieser Arbeit besteht in der Vorstellung eines neuartigen, semantischen Modells, dass es erlaubt, sowohl Wissen der Domänen Regelung und Steuerung, als auch der Domäne Regelungslogik explizit und formal zu beschreiben. Zusätzlich ist es nun erstmals möglich dieses Wissen mit angrenzendem Domänenwissen, wie zum Beispiel aus dem Maschinenbau oder der Elektrotechnik, zu vernetzen. Das Modell wird unabhängig von der Implementierung in der Unified Modeling Language spezifiziert und mit Hilfe von Semantic Web Technologien implementiert. Das Modell ist in zwei Schichten aufgebaut. Auf der oberen Ebene wird allgemeines Wissen der Domäne Regelung und Steuerung modelliert, dass, wie in der Arbeit demonstriert, leicht mit angrenzenden Domänen verbunden werden kann. Auf der unteren Ebene wird das allgemeine Wissen der Domäne Regelung und Steuerung, um die Domäne der Regelungslogik erweitert und für die jeweilige Regelungslogik explizit spezifiziert. Zur Validierung des Modells wird in zwei separaten Fallstudien evaluiert, ob es das notwendige Wissen für zwei neuartige wissensbasierte Methoden repräsentieren kann. In der ersten Fallstudie wird eine wissensbasierte Methode zur Verbesserung des Betriebs von Automatisierungssystemen in Gebäuden prototypisch umgesetzt und getestet. Dabei ermöglicht das entwickelte Modell Faktenwissen, das aus dem Engineering der Regelungslogik gewonnen wurde, formal zu beschreiben. Dieses Wissen wird dann genutzt, um automatisiert Regeln zu instanziieren, die es ermöglichen automatisiert zu überprüfen, ob die tatsächlich implementierte Regelungslogik sich im Betrieb genauso verhält wie ursprünglich entworfen. In der zweiten Fallstudie wird eine wissensbasierte Methode zur Unterstützung des Engineerings von industriellen Automatisierungssystemen vorgestellt. Hier wird gezeigt, dass, basierend auf dem neuen Modell, die gleichzeitige formale Verifikation von verschiedenen Regelungsverfahren und die gleichzeitige formale Verifikation von Regelungsverfahren und Wissen über die automatisierte Anlage möglich ist. Zusätzlich, wird gezeigt, dass die Methode inkrementelle Aktualisierungen des Faktenwissens ermöglicht und ein bidirektionaler Austausch von Fallwissen zwischen dem ursprünglichen Format und der Wissensbasis möglich ist. Durch die Schaffung des neuen Modells ist nun die Möglichkeit gegeben formal und explizit Wissen der Domänen Regelung und Steuerung, sowie Regelungslogik zu beschreiben. Basierend auf diesem Modell werden zwei neuartige, wissensbasierte Methoden vorgestellt, die es ermöglichen das Engineering und den Betrieb von Automatisierungssystemen zu vereinfachen und zu verbessern

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

Formal Digital Description of Production Equipment Modules for supporting System Design and Deployment

The requirements for production systems are moving towards higher flexibility, adaptability and reactivity. Increasing volatility in global and local economies, shorter product life cycles and the ever-increasing number of product variants arising from product customization have led to a demand for production systems which can respond more rapidly to these changing requirements. Therefore, whenever a new product, or product variant, enters production, the production system designer must be able to create an easily-reconfigurable production system which not only meets the User Requirements (UR) but is quick and cost-efficient to set up. Modern production systems must be able to integrate new product variants with minimum effort. In the event of a product changeover or an unforeseen incident, such as the mechanical failure of a production resource, it must be possible to reconfigure the production system smoothly and seamlessly by adding, removing or altering the resources. Ideally, auto-configuration should obviate the need to manually re-programme the system once it has been reconfigured.The cornerstone of any solution to the above-mentioned challenges is the concept of being able to create formalised, comprehensive descriptions of all production resources. Providing universally-recognised digital representations of all the multifarious resources used in a production system would enable a standardised exchange of information between the different actors involved in building a new production system. Such freely available and machine-readable information could also be utilised by the wide variety of software tools that come into play during the different life cycle phases of a production system, thus considerably extending its useful life. These digital descriptions would also offer a multi-faceted foundation for the reconfiguration of production systems. The production paradigms presented here would support state-of-the-art production systems, such as Reconfigurable Manufacturing Systems (RMSs), Holonic Manufacturing Systems (HMSs) and Evolvable Production Systems (EPSs).The methodological framework for this research is Design Research Methodology (DRM) supported with Systems Engineering, Action Research, and case-based research. The first two were used to develop the concept and data models for the resource descriptions, through a process of iterative development. The case-based research was used for verification, through the modelling and analysis of two separate production systems used in this research. The concept, on which this thesis is based, is itself based on the triplicity of production system design, i.e. Product, Process and Resource. The processes, are implemented through the capabilities of the resources, which are thus directly linked to the product requirements. The driving force behind this new approach to production system design is its strong emphasis on making production systems that can be reconfigured easily. Successful system reconfiguration can only be achieved, however, if all the required production resources can be quickly and easily compared to all the available production resources in one unified, and universally accepted form. These descriptions must not only be able to capture all of a production system’s capabilities, but must also include information about its interfaces, kinematics, technical properties and its control and communication abilities.The answer to this lies in the Emplacement Concept, which is described and developed in this thesis. The Emplacement Concept proposes the creation of a multi-layered Generic Model containing information about production resources in three different layers. These are the Abstract Module Description (AMD), the Module Description (MD), and the Module Instance Description (MID). Each of these layers has unique characteristics which can be utilised in the different phases of designing, commissioning and reconfiguring a production system. The AMD is the most abstract (general) descriptive layer and can be used for initial system design iterations. It ensures that the proposed resources for the production system are exchangeable and interchangeable, and thus guides the selection of production resources and the implementation (or reconfiguration) of a production system. The MD is the next level down, and provides a more detailed description of the type of production resource, providing ’finer granularity’ for the descriptions. The MID provides the finest level of granularity and contains invaluable information about the individual instances of a particular production resource. This research involves two practical implementations of the Generic Model. These are used to model and digitally represent all the production resources used in the two use-case environments. All the modules in the production systems (25 in all) were modelled and described with the data models developed here. In fact, we were able to freeze the data models after the first case study, as they didn’t need any major changes in order to model the production resources of the second use-case environment. This demonstrates the general applicability of the proposed approach for modelling modular production resources.The advantages of being able to describe production resources in a unified digital form are many and varied. For example, production systems which are described in this way are much more agile. They can react faster to changes in demand and can be reconfigured easily and quickly. The resource descriptions also improve the sustainability of production systems because they provide detailed information about the exact capabilities and characteristics of all the available resources. This means that production system designers are better placed to utilise ready-made modules, (design by re-use). Being able to use readily available production modules means that the Time to Market and Time to Volume are improved, as new production systems can be built or reconfigured using tested and fully operational modules, which can easily be integrated into an already operational production system. Finally, the resource descriptions are an essential source of information for auto-configuration tools, allowing automated, or semi-automated production system design. However, harvesting the full benefits of all these outcomes requires that the tools used to create new production systems can understand and utilise the modular descriptions proposed by this concept. This, in turn, presupposes that the all the formalised descriptions of the production modules provided here will be made publicly available, and will form the basis for an ever-expanding library of such descriptions

EXPERIMENTAL STUDIES FOR DEVELOPMENT HIGH-POWER AUDIO SPEAKER DEVICES PERFORMANCE USING PERMANENT NdFeB MAGNETS SPECIAL TECHNOLOGY

In this paper the authors shows the research made for improving high-power audio speaker devices performance using permanent NdFeB magnets special technology. Magnetic losses inside these audio devices are due to mechanical system frictions and to thermal effect of Joules eddy currents. In this regard, by special technology, were made conical surfaces at top plate and center pin. Analysing results obtained by modelling the magnetic circuit finite element method using electronic software package,was measured increase efficiency by over 10 %, from 1,136T to13T

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

Friction Force Microscopy of Deep Drawing Made Surfaces

Aim of this paper is to contribute to micro-tribology understanding and friction in micro-scale interpretation in case of metal beverage production, particularly the deep drawing process of cans. In order to bridging the gap between engineering and trial-and-error principles, an experimental AFM-based micro-tribological approach is adopted. For that purpose, the can’s surfaces are imaged with atomic force microscopy (AFM) and the frictional force signal is measured with frictional force microscopy (FFM). In both techniques, the sample surface is scanned with a stylus attached to a cantilever. Vertical motion of the cantilever is recorded in AFM and horizontal motion is recorded in FFM. The presented work evaluates friction over a micro-scale on various samples gathered from cylindrical, bottom and round parts of cans, made of same the material but with different deep drawing process parameters. The main idea is to link the experimental observation with the manufacturing process. Results presented here can advance the knowledge in order to comprehend the tribological phenomena at the contact scales, too small for conventional tribology

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems