Ontology-based assistance system for control process reconfiguration of Robot-Based Applications

Due to increasing global competition, companies are challenged to make their production flexible and adaptable. This leads to a steadily increasing complexity of production systems and thus their automation and control processes. At the same time, control processes must be quickly configurable in order to be able to react to short product life cycles. Robot-based adhesive application in automotive body assembly represents one such control and automation process. In car body assembly, industrial robots are increasingly being used for gluing side panels, enabling flow operation in assembly. In the event of a functional change in the production process, such as the replacement of the adhesive to be used, all the given process interrelationships must be analysed again and reconfigured if necessary in order to ensure the quality of the bonded joint. Comprehensive data management systems that provide an overview of all the system parameters and control levers are often not available in companies, so that reconfiguration is based on experience. Correct adjustment of the process parameters thus requires the user to have precise knowledge of the complex interrelationships between the process and bonding parameters, which makes the search for solutions in the event of a process change more difficult and time-consuming. In order to master the complexity of process planning and configuration, a large number of user-supporting solutions exist in the area of product lifecycle management (PLM). However, these neither have the functionality to generate solution and optimization proposals, nor do they map the existing expert knowledge with so-called empirical values about the system behaviour. The advantages of semantic technologies including ontologies, such as their graph structure and suitability for the use of optimization algorithms, illustrate their potential as the basis of a knowledge-based assistance solution. Against this background, the aim of this paper is to develop an ontology-based knowledge management system that can consolidate existing product and process information and add expert knowledge to it. The resulting knowledge graph of the process is then examined using selected optimization algorithms (PMS, Parallel Machine Scheduling). From the analysis, configuration suggestions can be derived, which can be presented to the user with a visualisation interface. Finally, the potential of ontologies as the basis of a knowledge-based assistance system is evaluated based on given results

A Performance Assessment System incorporating indirect indicators and semantics

Measuring performance is key to reengineering and optimization of business processes. Although many of them cannot easilybe measured due to their quantitative or non-deterministic nature, most performance measurement systems rely on the usageof numeric parameters (Key Performance Indicators, KPIs). So, performance problems stay invisible that could be assessedby other indirect indicators like goals, complexity, maturity, relations or dependencies. In this paper, a Four-Box-Model ispresented that also includes internal process views, descriptive approaches and semantics in addition to KPIs. It offers a broadrange of possibilities to better identify performance problems and hence, to increase process performance

Semantic Model Alignment for Business Process Integration

Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects

Planungswerkzeug zur wissensbasierten Produktionssystemkonzipierung

Kürzere Produktlebenszyklen zwingen Unternehmen dazu notwendige Produktionssysteme in immer kürzeren Abständen neu zu planen oder anzupassen. Grundlegende Entscheidungen über den Aufbau des Produktionssystems werden bereits in der Konzipierungsphase festgelegt. Anhand des vorliegenden Produktkonzepts sind Produktionsprozesse zu spezifizieren und umsetzende Betriebsmittel auszuwählen. Zur Reduzierung der Planungsaufwände und zur Wiederverwendung bewährter Lösungen ist eine gezielte Bereitstellung von Fach- und Lösungswissen erforderlich.Die vorliegende Arbeit beschreibt ein Planungswerkzeug, welches die Planer während der Produktionssystemkonzipierung durch den kontinuierlichen Zugriff auf verfügbares Wissen unterstützt. Mittels semantischer Technologien wird das Wissen repräsentiert und in einer Wissensbasis bereitgestellt. Benötigte Abfragen werden automatisch erzeugt und das Wissen direkt für die graphische Spezifikation des Produktionssystemkonzepts verwendet. Eine einheitliche Spezifikation wird über Modellierungsregeln sichergestellt. Ein Vorgehensmodell beschreibt die einzelnen Planungsschritte, die exemplarisch am Praxisbeispiel einer Knetstraße erläutert werden.Shorter product life cycles force companies to develop or adapt production systems in shorter intervals. Important decisions about the structure of the production system are already defined in the early design phase. Based on the principal solution of the product the necessary production processes have to be specified and appropriate production resources have to be selected. To reduce the planning effort and to support the reuse of proven solutions, knowledge available in the company has to be used in an efficient manner. The present work describes a planning tool that supports the planners during the conceptual design of a new production system. This is achieved by continuous access to available knowledge about known processes and resources. Using semantic technologies the knowledge is represented and provided in a knowledge base. Required queries are generated automatically and the knowledge is directly used for the graphical specification of the production system concept. Modeling rules ensure a uniform specification and a procedure model describes the necessary activities. The use of the planning tool is illustrated and explained by means of an application example.Tag der Verteidigung: 18.12.2014Paderborn, Univ., Diss., 201

Wandlungsfähige und angepasste Automation in der Automobilmontage mittels durchgängigem modularem Engineering -Am Beispiel der Mensch-Roboter-Kooperation in der Unterbodenmontage-

Die Automobilindustrie steht vor Herausforderungen durch verkürzte Lebenszyklen, wachsende Vielfalt und schwankende Märkte. Hersteller benötigen eine anpassungsfähige Produktion mit intelligenter Kombination aus Automatisierung und Handarbeit. Neue Technologien wie cyberphysische Systeme (CPS) und Mensch-Roboter Kooperation (MRK) bieten sich als Lösungen an. Aufgrund hoher Komplexität und anwendungsspezifischer Lösungen ist die Umsetzung aufwändig und schränkt Wiederverwendbarkeit und Anwendungsbereich ein. Der gezeigte Ansatz besteht darin, das Potenzial angepasster Automatisierung zu nutzen, um Produktivität und Qualität zu verbessern mit gleichzeitiger Wandlungsfähigkeit. Die entwickelte Methodik beschreibt einen durchgängigen Prozess von der Montageplanung bis zur technischen Realisierung. Ein einheitliches Datenmodell ermöglicht die Zuordnung von Prozessanforderungen zu ausführbaren Ressourcenmethoden, die aus einem modularen System konfiguriert sind. Diese Ressourcen sind als physische und cyber Komponenten integriert, was einfache Rekonfiguration ermöglicht. Die Beschreibung der Arbeitsaufgaben des Systems als Workflow Liste ermöglicht eine flexible Prozessanpassung. Aufwändige Programmierung wird durch Parametrierung von wiederverwendbaren Modulen in Kombination mit angepasster Aufgabenbeschreibung ersetzt. In der Praxis zielt die Methodik darauf ab, kürzere Planungszeiten zu erreichen sowie den Einsatz von CPS in der angepasst automatisierten Montage zu erleichtern.The automotive industry faces challenges due to shortened lifecycles, growing variety and fluctuating markets. Manufacturers require an adaptable production with an intelligent customized combination of automation and manual labour. Novel technologies like cyber-physical systems (CPS) and human-robot collaboration (HRC) evolved as solutions for this demand. Due to high complexity and application specific solutions, the implementation process causes large efforts. This limits the scope of application and reusability. A consistent cross-disciplinary planning approach is missing. The approach is to use the potential of customized automation to improve productivity and quality while maintaining flexibility and versatility. A methodology was developed to describe an integrated process from assembly planning to technical realization. A uniform data model allows assignment of process requirements to executable methods of resources, configured from a modular system. These resources are integrated as physical and cyber components, allowing easy reconfiguration. The description of the system’s work tasks as a workflow-based work list allows a flexible adaptation of process steps. Elaborate programming efforts are replaced by parameterization of reusable modules in combination with an adapted task description. In practical application, the methodology aims to achieve shorter planning periods by consistency and reusability, as well as easier use of CPS in customized automated assembly

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains