An intelligent agent-controlled and robot-based disassembly assistant

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations

Towards Intelligent Robot Assistants for the non-destructive Disassembly of End of Life Products

The effective collaboration between humans and robots in complex and task rich environments like End of Life product disassembly depends on the ability of the robot to anticipate the workflow as well as the assistance the human co-worker wants. Our approach towards such an intelligent system is the development of an informed software agent that controls the robot assistance behavior. We inform the agent with procedural and declarative knowledge about the disassembly domain through models of the product structure and actor/object models. The product structure is then transformed to a directed graph and used to build, share and define a goal-orientated coarse workflow. Depending on the tasks and wanted assistance, the system can generate adaptable and detailed workflows through searching in the situation space on the basis of predefined and task dependent actions. The created detailed workflow consists of a sequence of actions that are used to call, parameterize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with higher cognitive skills to allow them to be autonomous in the performance of their assistance to improve the ergonomics of disassembly workstations

An ontology and rule-based method for human–robot collaborative disassembly planning in smart remanufacturing

Disassembly is a decisive step in the remanufacturing process of End-of-Life (EoL) products. As an emerging semi-automatic disassembly paradigm, human–robot collaborative disassembly (HRCD) offers multiple disassembly methods to enhance flexibility and efficiency. However, HRCD increases the complexity of planning and determining the optimal disassembly sequence and scheme. Currently, the optimisation process of heuristic methods is difficult to interpret, and the results cannot be guaranteed as globally optimal. Consequently, this paper introduces a general ontology model for HRCD, along with a rule-based reasoning method, to automatically generate the optimal disassembly sequence and scheme. Firstly, the HRCD ontology model establishes the disassembly-related information for EoL products in a standardised approach. Then, customised disassembly-related rules are proposed to regulate the precedence constraints and optional disassembly methods for each disassembly task of EoL products. The optimal disassembly sequence and scheme are automatically generated by combining supportive rules with the ontology model. Lastly, the human–robot collaborative disassembly planning of a gearbox is presented as a case study to validate the feasibility of the proposed methods. Our method generates an optimal disassembly scheme compared with other heuristic algorithms, achieving the shortest process time of 308 units and the fewest number of disassembly direction change of 3 times. Additionally, the reasoning procedure can be easily tracked and modified. The proposed method is both universal and easily reproducible, allowing it to be extended to support the entire remanufacturing process

Konzeption und Entwicklung eines Robot Cognition Processors für adaptive Demontageanwendungen

Im Rahmen der perspektivischen Einführung einer Kreislaufwirtschaft sind ökonomische und ökologische Aspekte entscheidend für die Attraktivität der Umsetzung in beteiligten Wirtschaftsunternehmen. Die Demontage stellt innerhalb von Verwertungsprozessen in diesen Konzepten einen wichtigen Schritt dar, der aufgrund von hoher Varianten- und Zustandsvielfalt überwiegend manuell ausgeführt wird. Diese Forschungsarbeit untersucht die Möglichkeiten der nachhaltigen Verbesserung des Demontageprozesses durch selektive (Teil-)Automatisierung mit Hilfe eines Konzeptes aus dem Bereich der kognitiven Robotik. Es wird dabei auf Grundlage der Anforderungen aus realen Demontageprozessen ein System entwickelt, das in einer agentenbasierten Modulstruktur die Funktionsumfänge bietet, die für eine autonome, flexible Demontageplanung unter Berücksichtigung von Produkt- und Lebenszyklusdaten erforderlich sind und die effiziente Ausführung der Demontageoperationen im Rahmen einer Mensch-Roboter-Kollaboration erlauben. Grundlage für die entwickelten Module stellt ein standardisiertes Informationsmanagement-Konzept dar, welches die Anlagenebene der Demontage technisch mit allen beteiligten Stakeholdern der zirkulären Wertschöpfungskette verknüpft. Mit Hilfe von Industrie 4.0 Technologien, wie beispielsweise dem Einsatz von KI-unterstützten Entscheidungssystemen oder einer intelligenten Bilderkennungseinheit können so produktindividuelle Verwertungsszenarien innerhalb der Kreislaufwirtschaft bestimmt werden, welche die Schlüsselposition der Demontage am Beginn der zirkulären Wertschöpfungskette bestmöglich nutzen. Die Untersuchungen des Systemkonzeptes am Beispiel der Moduldemontage von Elektrofahrzeug-Batterien zeigen, dass mit dem entwickelten Konzept eine Verbesserung gegenüber manueller Demontageoperationen erzielt werden kann. Die Verknüpfung der Systemeinheiten lässt sich durch die verwendeten Interoperabilitätsstandards skalieren und erlaubt so auch den industriellen Einsatz. Durch bidirektionale Kommunikationsstrukturen wird gezeigt, dass es möglich ist validierte Prozessinformationen aus einer Demontageeinheit an anderen Stellen zu nutzen. Dies reduziert den effektiven Aufwand im Umgang mit einer hohen Variantenvielfalt. Die Verwendung der entwickelten Modulkonzepte ist grundsätzlich auch in angrenzenden Feldern möglich, erfordert jedoch weitere Entwicklungs- und Abstimmungsarbeit. Aus den Ergebnissen dieser Konzeptentwicklung folgen zahlreiche Weiterentwicklungs- und Anwendungspotenziale für Robotiksysteme im Bereich der kreislaufwirtschaftlichen Verwertungsprozesse. Vor dem Hintergrund der Notwendigkeit der Rückgewinnung kritischer Elemente und einer effizienten Ressourcennutzung durch höherwertige (Teil-)Nutzungs- und Verwertungsoptionen, ist der Einsatz hierauf aufbauender Konzepte eine lohnenswerte Zukunftsperspektive.In the pursuance of a Circular Economy, both economic and ecological aspects are crucial for the implementation in private companies. The disassembly process itself is a very important step in end-oflife utilization and because of the high variance of products and their conditions it is mainly carried out manually. This work investigates the possibilities of a sustainable improvement of such processes by selective automation with cognitive robotics. Based on requirements of real disassembly cases, a robot system is conceptualized and developed which is able to facilitate an autonomous, flexible disassembly planning while taking both product and lifecycle data into account. Furthermore, the execution of the disassembly process in the concept is carried out as a human-machine-collaboration. The overall foundation of the system is an information management concept which connects shopfloor level disassembly with all stakeholders within the circular value chain. Using Industry 4.0 technologies, for instance AI decision systems or an intelligent image recognition, part-individual utilization scenarios can be defined this way. The investigation of the system concept on the case study of module disassembly of electric vehicle batteries shows that automation is both more effective and efficient in comparison to manual operations. Interfaces are highly scalable because of the interoperability standards used, preparing the concept to be implemented in industry. Moreover, bidirectional communication pipelines enable the exchange of valid process knowledge between several stakeholders, reducing the effort of dealing with a high variance of products and conditions. Transfer of the concept to other fields of industry or recycling operations is possible but requires further development for the actual use case. Conclusively, the concept developed opens up a manifold of different application scenarios for cognitive robotics in the Circular Economy domain. Keeping the necessity of recovering critical elements and the reuse of valuable components in mind, an implementation of future concepts based on this approach is a perspective worthwhile