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Offline Path Compensation to Improve Accuracy of Industrial Robots for Machining Applications
(2013)
Homogene Steuerung in einem heterogenen Umfeld = Homogeneous control in heterogeneous environment
(2004)
Das Konzept eines Engineering Portals zur benutzerzentrierten Unterstützung der Anlagenplanung
(2006)
The manufacturing industry is distinguished by regionalization and individualization of products accompaniedby varying customer demands, faster time to market, short innovation cycles and product life cycles. Theintroduction of new materials, new processes as well as struggle to achieve economic and efficient use ofresources has raised complexities to achieve quick and optimal configuration in manufacturing systems. Toresolve the complexities, the reconfiguration at different levels in the manufacturing system is presented byusing three distinct examples. The first example refers to reconfigurable joining cell design for versatile joiningof automotive subassemblies. Second example refers to strategy for quick reconfiguration of robots for precisemachining applications. The third example elaborates fast calibration of monitoring system in joiningprocesses to enable fast reconfiguration of sensors in commissioning as well as in the maintenance.
A Multilevel Reconfiguration Concept to Enable Versatile Production in Distributed Manufacturing
(2011)
The manufacturing industry is confronting challenges due to high diversity of product variants,reduced product life cycles,short innovation cycles, faster time to market as well as strictenvironmental regulations. These challenges have persuaded manufacturers to exploit conceptsrelated to open innovation, distributed manufacturing, modular and scalable production systemdesign and eco-efficient production. This paper aims at providing a short review of state of the art inreconfiguration of distributed production systems and focuses on new strategies to resolvecomplexities that arise subsequently. In this regard, a reconfiguration concept based on newstrategic objectives has been proposed to enable customized production. The approach will beimplemented and validated in the collaborative projects.
Insbesondere die produzierenden Unternehmen in der Automobilindustrie müssen auf kürzere Produktzyklen und steigende Vielfalt zeitnah und wirtschaftlich reagieren, um langfristigen Unternehmenserfolg zu sichern. Diese Anforderungen können heute verfügbare Systeme oftmals nicht leisten. Die kognitiven Fähigkeiten der Mitarbeiter ermöglichen in der manuellen Montage eine hohe Anpassungsfähigkeit. Erwünschte Produktivitätssteigerungen werden durch Erhöhung des Automatisierungsgrades engestrebt, wobei die Fähigkeiten der Mitarbeiter nur selten genutzt werden und die Anpassungsfähigkeit abnimmt. Zukunftsweisende Montagekonzepte können nur durch entsprechende Zielsetzung und methodische Vorgehensweisen erreicht und umgesetzt werden. Ziel des "Robot Farming" Konzept ist es, die Mitarbeiterproduktivität unter voller Nutzung ihrer kognitiven Fähigkeiten zu steigern. Im Beitrag werden die Vorgehensweise zur Konzeptentwicklung, ausgewählte Bausteine des "Robot Farming" und ein Planungssystem für "Robot Farming" Konzepte in der Montage vorgestellt.
Insbesondere die produzierenden Unternehmen in der Automobilindustrie müssen auf kürzere
Produktlebenszyklen und steigende Vielfalt zeitnah und wirtschaftlich reagieren, um langfristigen
Unternehmenserfolg zu sichern. Diese Anforderungen können heute verfügbare
Systeme oftmals nicht leisten. Die kognitiven Fähigkeiten der Mitarbeiter ermöglichen in der
manuellen Montage eine hohe Anpassungsfähigkeit. Erwünschte Produktivitätssteigerungen
werden durch Erhöhung des Automatisierungsgrades angestrebt, wobei die Fähigkeiten der
Mitarbeiter nur selten genutzt werden und die Anpassungsfähigkeit abnimmt. Zukunftsweisende
Montagekonzepte können nur durch entsprechende Zielsetzung und methodische
Vorgehensweisen erreicht und umgesetzt werden. Ziel des „Robot Farming“ Konzeptes ist
es, die Mitarbeiterproduktivität unter voller Nutzung ihrer kognitiven Fähigkeiten zu steigern.
Im Beitrag werden die Vorgehensweise zur Konzeptentwicklung, ausgewählte Bausteine des
„Robot Farming“ und ein Planungssystem für „Robot Farming“ Konzepte in der Montage vorgestellt.
Sophisticated screwing processes in modern screwing equipment are marked with complex parameter settings of the
screwing operations and with their assessment requirements. To gain the potential for improvement, the screwing processes must be handled using a special strategy. To determine the exact parameters and to achieve improved process quality requires development of analysis tools to diagnose the parameter attributes. Increased requirements in the screwing processes demand operator best fit training procedures. A continuous improvement concept for the process control is required to enhance work quality. An information system with a maturity degree for automated screwing processes is developed. To avoid the technical risks, some mechanisms were developed, which automatically extract the process related data and provide it to operator afterwards. By using the information system, information (process and control data) about the parameterization of the screwing control with standardized correlations and a clear tracing of working steps is provided. In this way the running, modification and optimization of the screwing process can be implemented without errors. The developed information system was evaluated on an experimental platform for screwing process in the research laboratory. Thereby, the functionalities of the platform and their components are described and a validation of the developed system is carried out. The development and assembly of the components is presented. Data interrelations are also described in detail. With the developed information system the correct parameterization of the screwing processes with a degree of maturity of the process parameters were achieved. The evaluation of the maturity degree is made with the help of functional properties of the parameters. Consequently, an obvious minimization of the mistakes and a simple screwing process control is achieved.
Industry 4.0 is still in its development phase and it promises to bring remarkable benefits to the manufacturing industry around the world when employing the Smart Factory application in large organizations and their supply chains. However, there is a risk of a miss-match when trying to introduce Industry 4.0 to Small and Medium Enterprises (SME) as the concept is mainly being developed around large manufacturing companies. The purpose of this research is to analyze the readiness level and feasibility of implementing Industry 4.0 technologies for SME’s in the federal state of Brandenburg (Germany). The work is based on the survey of 20 SME’s assessing their current problems emphasizing on automation, Enterprise Resource Planning (ERP), CAD/CAM, factory layout planning and logistics. Five SME’s from different domains out of the 20 surveyed are taken as case studies to evaluate the potential benefits, trade-offs and barriers from an implementation of these integrated technologies. The findings revealed that the companies are still coping with the issues relating to planning, logistics and automation. It was also found that all the concepts of i4.0 may not be necessary or even beneficial to an enterprise in the current scenario and new strategies need to be developed for its realization in SME’s.
This paper presents a novel approach for automated smart factory based on the ideas of Internet of Things (IoT) and the usage of mobile technology of the german „Industry 4.0“ [6]. IoT enables the achievement of greater value and service by exchanging data between different devices and the manufacturer. The data collected from all devices will be exchanged via wireless networks. Mobile technology can be used to cover non value-added processes [3] i.e. transportation in the manufacturing. By combining transportation tasks and value adding production steps, waste of production time, cost and effort can be reduced. This paper presents the first step toward this approach [7]: the mobile robot moves alongside the moving object and executes the manufacturing tasks during its transportation. For the demonstration of the developed solution a mobile
platform and an optical measurement system was used. The synchronization between the mobile platform and the object will be experimentally tested. Consequently the results will demonstrate how the mobile robot is able to follow the moving object.
Die steigende Produktvielfalt und die Anforderung nach höherer Flexibilität in der Produktion sowie nach Steigerung der Produktivität erfordern im industriellen Umfeld eine Erhöhung des Automatisierungsgrades. Vor diesem Hintergrund steigert sich der Robotereinsatz in der Industrie seit Jahren. Jedoch liegt der Automatisierungsgrad im Montagebereich immer noch auf einem niedrigen Niveau, weil entweder der hohe Zeitbedarf zur Entwicklung eines Robotersystems und/oder der hohe Aufwand zur Umsetzung ins Zielsystem hinderlich auf die Erhöhung des Automatisierungsgrads wirken. In diesem Paper wird eine neue Methode zur Entwicklung eines Robotersystems für Montageaufgabe vorgestellt. Diese Methode zielt auf Erstellung einer Montageaufgabe durch Anwendung der Erweiterten Realität (Augmented Reality, Abkürzung AR). Eine virtuelle Montageaufgabe mit virtuellen Bauteilen wird händisch ausgeführt, dadurch wird diese Montageaufgabe visualisiert dargestellt und automatisch im Zielsystem erstellt.
A maturity assessment approach for conceiving context-specific roadmaps in the Industry 4.0 era
(2019)
The digital transformation of the production sector is setting the scene for a major industrial change. The need for supporting companies in this transformation is currently covered by several maturity models, generally operationalized through standardized questionnaires, which provide, as an outcome, an assessment of the current maturity stage and a set of general improvement recommendations according to it. However, to provide companies with a more tangible support, there is a need for more individual approach. In order to deal with this need, this paper proposes, following a design science research framework, a novel approach based on Problem-Based Learning for structuring the assessment procedure as a dialectic process. This approach aims at facilitating the contextualization of the assessed company and, consequently, the identification of context-specific improvement recommendations. The proposed approach, supported by a maturity model used for framing information collected during the assessment process, is tested in three industrial cases. Although these have been assessed at the same maturity stage, different improvement recommendations have been proposed according to contextual factors such as strategic goals, core processes and key performance indicators.
As Convolutional Neural Network based models become reliable and efficient, two questions arise in relation to their applications for industrial purposes. The usefulness of these models in industrial environments and their implementation in these settings. This paper describes the autonomous generation of Region based CNN models trained on images from rendered CAD models and examines their applicability and performance for part handling application. The development of the automated synthetic data generation is detailed and two CNN models are trained with the aim to detect a car component and differentiate it against another similar looking part. The performance of these models is tested on real images and it was found that the proposed approach can be easily adopted for detecting a range of parts in arbitrary backgrounds. Moreover, the use of syntheic images for training CNNs automates the process of generating a detector.
This work describes three technical improvements to the handling assistant, a collaborative robot for handling and commissioning, concerning the depth of information the robot can extract from the teaching process. The teaching process involves an unskilled worker setting up the robots movements and actions through hand guiding to instruct the robot to perform a given task. The possibilities of improvements in picking, placement and path demonstrated are identified and solutions for the same are presented. The task of picking of the part is improved through the use of null space motion of the robot and exploiting part symmetry. The task of placement of parts is improved through the use of data collected during the demonstration. Finally the path of the robot is optimized using regression with a cost function targeted minimizing the time required for path movement. The developed methods are implemented and validated on a test case using a handling assistant which has a KUKA iiwa robot and collaborative gripper.
Due to the extensive changes along with Industry 4.0 many established barriers drop. One of those barriers which increasingly disappears separates the workspace between human beings and robots and thus prevents a versatile collaborating environment. This change has led to the development of a wide field of research focusing on the prevention of human-robot impacts and/or the minimization of related risks. This paper is focused on safety regulations introduced as a consequence of those developments over the last ten years and particularly on an approach for demonstrating the unintended gap arising between human and robot due to those regulations. Modularity and integrability as two of the key characteristics in the concept of Reconfigurable Manufacturing Systems (RMS), serve as the comparative parameters.
Fertigungsanlagen flexibel gestalten – Konzept einer plattform- und serviceorientierten Lösung
(2016)
In addition to the already required functionality, future production systems should consider the requirements of flexible and demand-oriented resource utilization. Those are not only related on fields of energy, but also material-efficient and time-efficient use of available means of production. Modular system architectures and modular solutions facilitate the planning and implementation of these requirements. Using service-oriented architectures in automation allow an approach for new or modified system components that can be integrated in the available plant environment without a high additional investment of project engineering. This aspect is interesting for companies with manageable machinery, which are able to react immediately and flexible to changes. Service-oriented solutions include among other things the identification, classification and synchronization of possible services. The paper will show general prerequisites for an implementation of a service-oriented architecture in a module-based test field.
In this paper the use of a mobile lightweight robot is evaluated to perform an assembly task while simultaneously moving. The motion of the mobile platform results into a variable end effector position in space. The paper assesses
the existing method of placing a screw in an assembly where the location of placement is variable due to end effector movement. Experiments have been conducted to evaluate the task performance by monitoring the applied force on the
end effector, the position data and the task time. The results show that with impedance configuration, a moveable compliant robot is a possible solution for use in assembly operation.
In this paper a flexible robot system for assembly operations in a semi structured environment is proposed. The system uses a moveable robot equipped with an arbitrarily mounted 3D camera and a 2D camera on the robot gripper for accurate object detection. The system is developed based on the Robot Operating System (ROS) and uses the state of the art trajectory planner MoveIt for collision free robot motion planning. The object recognition for the system is performed using a combination of the two camera's and robot end effector and the deviation of objects in the robot workspace is found to be in the range of 2.2 mm along X and Y axes. Furthermore, an implementation procedure of the proposed system for assembly task is explained.
Die in diesem Artikel beschriebene, praktische, Verwendung einer Augmented Reality Umgebung findet statt für die Fehlerbeseitigung und Fehlerkorrektur bei der Arbeit in einer Laboranlage, die verschiedene Fehler simuliert kann. Innerhalb der Anlage sind alle wesentlichen Komponenten mit Sensorik ausgestattet, so dass jederzeit Informationen über
den Zustand des Systems in Echtzeit bereitliegen. Sobald sich einen Fehler innerhalb der Anlage befindet, kann das Steuerungssystem durch die vorliegenden Sensordaten dieses
Problem identifizieren. Die verschiedenen Teile der Anlage sind mit Positions-Markern zur Identifizierung eines
Anlagenbereiches ausgerüstet. Wird die Anlage durch einen Fehler gestoppt ist, muss der Mitarbeiter die Anlage mit Hilfe des Kamerasystems eines mobilen Endgerätes (mit dem
Tablet) erfassen. Die erfassten Daten aus diesem Scan werden mit Hilfe der Software verarbeitet. Durch die visuelle Rückmeldung (z.B., auf dem Tablet) erhält der Anwender die Information über den aufgetretenen Fehler innerhalb der Anlage und zur Behebung des Zustandes. Auf
Grundlager der erkannten Marker können positionsgenau Objekte eingeblendet werden die dem Anwender den Ort des Fehlers anzeigen und Hinweise zur Bedienerführung zur
Aufnahme des ordnungsgemäßen Betriebs der Anlage geben. Der Anlagenführer wird in die Lage versetzt, die Fehlerbeseitigung und Fehlerkorrektur schnell und erfolgreich zu realisieren. Ein Einsatz des Systems für Schulungsprozesse ist vorgesehen, da sich dies
positiv auf die Verringerung von Stillstandszeiten auswirkt. So demonstriert das beschriebene, realisierte Verfahren wie die praktische Verwendung der
AR zur Reduzierung des zeitlichen Aufwandes für die Fehlerbeseitigung und die Fehlerkorrektur der Maschinenumgebung bei der Mensch-Maschinen-Integration in Industrie 4.0 Umgebungen beiträgt und den gesamten Integrationsprozess zwischen Mensch und Maschine vertiefet.
Intelligente Assistenzsysteme unterstützen die Mitarbeiter in der Produktion und erhöhen die Effizienz durch das Einblenden von situationsbasierten Aufgabeninformationen. Im Projekt Advanced Robot Assistance Solution (ARAS) im Rahmen des Kuka Innovation Awards 2021 wurde eine Assistenztechnologie entwickelt, um automatisiert Roboterprogramme für Montageabläufe zu generieren. Durch innovative Mensch-Maschine-Schnittstellen werden Montageschritte per maschinellem Lernen erkannt und in ausführbare Programme für Industrieroboter übersetzt. Dadurch können roboterbasierte Montageprozesse innerhalb von Minuten auf neue Produkte angepasst werden, ohne dass die Mitarbeiter über Kenntnisse des Programmierens oder der Robotik verfügen müssen. Ein Mitarbeiter muss den Montageprozess nur einmal vormachen. Das ARAS-System ermöglicht die kosten- und zeiteffiziente Integration und Adaption von Industrierobotern in der Montage für große und mittelständische Unternehmen.
Synchronisation von mobilen Robotern zu einer kontinuierlichen Fließfertigung für Montageaufgaben
(2015)
Strategies for Energy-oriented Process-Control: Requirements on Use Case of Container Handling.
(2014)
Technical conditions for the use of autonomous systems: A general approach for holistic engineering
(2013)
Mensch-Roboter-Kollaboration im Spannungsfeld von Rekonfigurierbarkeit, Sicherheit und Effizienz
(2019)
The automotive industry is experiencing several limitations due to high mass customization on product side and the consequent evolution of newer ones as well as the expansion of existing production setups. There exist various complexities in planning and control of istributed production setups. This paper addresses issues related to planning using knowledge management approaches in the decentralized manufacturing domain with two distinct cases. The first case relates to the higher level planning methodology to automate experts’ knowledge in production ramp-up whereas the second case relates to optimization of production processes using knowledgebase as an intelligent assistance system for optimization.
Die heutige Automobilindustrie ist durch zunehmende Individualisierungswünsche der Kunden sowie einer Verkürzung der Konjunkturzyklen gekennzeichnet. Für Fahrzeughersteller, wie der Daimler AG äußert sich diese Marktsituation in einer hohen Variantenvielfalt und Stückzahlschwankungen. Da die Ausprägungen dieser Einflüsse weitgehend unbekannt sind, muss das Produktionssystem darauf vorbereitet sein, bedarfsgerecht der Marktsituation angepasst zu werden. Diese Anpassungen müssen schnell, mit wenig Aufwand und geringen Kosten möglich sein. Wandlungsfähige Produktionssysteme gehören deshalb zu den strategischen Erfolgsgrößen für die Automobilindustrie. Innerhalb dieses Beitrags wird ein modularer, skalierbarer Produktionsbaukasten vorgestellt, der Bestandteil einer Planungs- und Entwicklungsumgebung wandlungsfähiger roduktionskonzepte ist. Die hierfür genutzte grenzwerttheoretische Entwicklungsmethodik wird erläutert und die Skalierungsmöglichkeiten des Produktionsbaukastens mit Hilfe neuer Produktionstechnologien betrachtet. Dabei zeichnet sich die Mensch-Roboter-Kooperation als wesentlicher Bestandteil wandlungsfähiger Produktionskonzepte ab. „Smarte Produktionsassistenten“ sind intelligente und sichere Roboter-Applikationen, die sich als Möglichkeit hervortun die Mensch-Roboter-Kooperation als Schlüsseltechnologie in industriellen Anwendungen zu realisieren.
The optimization processes in production planning often encounter problems due to unavailability of skilled workers in the concerned production departments since the decisions made in uncertain situations rely mainly on the knowledge possessed by the relevant planners. This paper further presents and elaborates the unified web-based knowledge based decision support system concept to automate and reuse implicit knowledge generated during interaction with the dedicated software tools as well as during interaction with real hardware setups in an industrial environment. The unified concept has been devised considering two pilot cases i.e. decision making on eco-efficient decentralized production schemes for manufacturing customized products and decision support for solving problems in ramp-up management process. This paper further discusses the development issues concerning web-based knowledge based decision support system to demonstrate the unified concept. The software modules from both pilot cases are validated considering two pilot cases.
The Smart Production Vision
(2022)
In this chapter, the Smart Production vision is discussed. The Smart Production approach is developed and described, and Smart Production is positioned in relation to Industry 4.0. Smart Production operationalize the journey towards Industry 4.0 and beyond. First, the need for a new approach to manufacturing is discussed, and from the perspectives of Industry 4.0, the Smart Production concept is derived. Then the framework is explored and finally, the approach is outlined. The Smart Production vision is an approach to make an integrated production system smarter by continuous digitizing, automating, and organizing towards supporting the company specific missions.
This chapter will introduce the second part of the book. This part contains a collection of chapters aimed at supporting the SMEs in the transformation toward the Smart Production vision. In this part, different approaches are presented, which can assist SMEs in the formulation of a smart production vision and in the identification and prioritization of relevant initiatives, guiding the outline of a project roadmap. Furthermore, the part will introduce different regional innovation platforms in Denmark and Germany which support the SME transformations. Finally, it will be discussed how subscription-based methods could be used by SMEs to cut upfront investments and reduce requirements for digital competencies.
Nutzung von Erfahrungswissen im Fahrzeuganlaufmanagement. Bewertung und Auswahl geeigneter Methoden
(2013)
Borck et al. evaluate the challenges and opportunities of Industrial Internet of Things (IIoT) and smart sensors in human-centered manufacturing. Particularly in small and medium-sized manufacturing with fewer machines and smart tools, it is significantly more difficult to automate processes and get the required information from the shop floor. Therefore, they give proven recommendations for the use of sensors based on a set of frequently occurring tasks in assembly, maintenance and logistics to achieve the support of smart data models in the context of Industry 4.0. “IIoT and smart sensors in human-centered manufacturing” concludes with concrete sample scenarios and describe the challenges and one solution using smart sensors and data models.
In this paper we present a novel method for performing in site real time quality inspection (QI) and consequently, digitalization of manual processes performed by human workers. It complements and improves our previous work in this area, which makes use of telemetry gathered from a smartwatch to classify manual actions as successful or unsuccessful. This new methodology provides the worker with a real time capable, robust and more accurate quality inspector. This work enhances the existing system through the elimination of input from the user by making use of a BIOX bracelet that detects gestures. The signal processing and classification methods are simplified and optimised by using assembled neural networks thus merging together the data gathered from multiple signal sources. Consequently, the overall QI system is improved with around 70%, thus furthering the necessary development needed to have a system ready to be used on a production environment.