Now showing 1 - 10 of 1902
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Implementing human-robot collaboration in highly dynamic environments: Assessment, planning and development

2024 , Bastidas Cruz, Arturo , Jaya, T. , Thiele, Gregor , Krüger, Jörg

Human-robot collaboration (HRC) applications have been slowly making their path in the industry. Although the required hardware and the methods for the planning and development of collaborative robotic applications are mostly already developed, some industrial branches still struggle to implement HRC. This is the case in motorcycle production, where, unlike car production, the assembly line has been optimized for manual work. Based on the use case described above, this paper identifies new requirements of HRC for automated screwing assembly operations in flexible production environments. In order to compensate deviations in the position of the tool relative to the workpiece, a screwing strategy based on force control is proposed. Parameter sensitivity is considered and supported experimentally with a screwing task performed by a cobot, where a method for contact detection between the nutrunner and the screw head is analyzed. This paper brings a guideline for experts from the manufacturing system engineering to implement HRC in highly dynamic assembly environments.

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Investigation on stereo-ToF data fusion for the inspection of used industrial parts

2024 , Krumpek, Oliver , Schlüter, Marian , Hügle, Johannes

Optical systems for automated or partially automated inspection have been making important contributions to ensure the quality and functionality of technical products for many years. Often used to monitor the quality of newly produced goods, vision systems also aim to play an important role in identification and condition description of used industrial parts such as aged vehicle components. In this work, a passive stereo system and a Time-of-Flight (ToF) sensor of the latest generation were used to create the desired sensor system. In the first step, the pixel-based information of both sensors was exploited to spatially calibrate the transformation between the left stereo camera and the ToF sensor by forming a 2D-3D correspondence set of detected feature points. To compensate for the resolution difference of the sensors, numerous interpolation points were randomly sampled on the reconstructed sparse surface mesh of the ToF sensor to create the missing sub-pixel information. It could be shown that the fused sensor information led to an increase in incompleteness by 7.81% on average for all components examined. The higher noise in the ToF measurement data in the fill-ins could be mitigated by using an adapted median kernel filtering. The average deviation of the measurement from a reference dataset was 1.30mm for the stereo system, 2.51mm for the ToF system, and 1.42mm for the fused result. The result of this work is promising as the quality of the surface mesh could be raised especially for critical surface areas and the underlying RGB data itself can be used for pixel-wise classification and segmentation.

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With synthetic data towards part recognition generalized beyond the training instances

2024 , Koch, Paul , Schlüter, Marian , Krüger, Jörg

In this work we investigate the effect of using synthetic data, generated in a simulation, in order to pre-train an AI-based image classification for industrial components. After pre-training we use real camera-captured training images to fine-tune the AI with the aim to close the Sim2Real domain gap. We compare our approach to purely using real training images of a single candidate object instance. In an exemplary case study for screw recognition, we found that a given AI classification algorithm dropped its recognition rate from 99.8% to 88.5% when testing the algorithm with known and unknown screw instances of the learned object classes, respectively. Employing our pre-training method on the basis of synthetic data, the drop in recognition rate is decreased from 99% to 96.95%. Thus, our proposed method has only a relative drop of 2.05% when shifting towards a generalized domain (including unknown part instances), while a compared approach on the basis of real camera-captured data showed a drop of 11.3%.

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Verbesserung der Übertragbarkeit eines künstlichen neuronalen Netzes zur Qualitätsvorhersage beim Widerstandspunktschweißen von hochfesten Stählen

2023-09-11 , El-Sari, Bassel , Biegler, Max , Rethmeier, Michael

Eine typische Automobilkarosserie kann bis zu 5000 Widerstandspunktschweißverbindungen aufweisen, welche hohen Qualitätsanforderungen genügen müssen. Daher ist eine durchgehende Prozessüberwachung unerlässlich. Die Transformation zur E-Mobilität in der Automobilindustrie und die damit einhergehende Reichweitenproblematik treiben die Entwicklung und Einführung neuer hochfester Stähle an. Dies resultiert in einem gesteigerten Fertigungsaufwand hinsichtlich einer stabilen Prozess-führung in der Fügetechnik. Um diesen Anstieg an Komplexität zu bewältigen, sind die Methoden der künstlichen Intelligenz ein geeignetes Mittel. Mit Ihnen kann, durch Auswertung der Prozessparameter und -signale, die individuelle Schweißpunktqualität sichergesellt werden. Die Vorhersagegenauigkeit von neuen Daten, also das extrapolieren, stellt für die meisten Algorithmen eine große Herausforderung dar. In dieser Arbeit wird ein künstliches neuronales Netz zur Vorhersage des Punktdurchmessers von Widerstandspunktschweißungen anhand von Prozessparametern implementiert. Die Vorhersagegenauigkeit und Extrapolationsfähigkeit des Modells wird durch die Auswertung des dynamischen Widerstandssignals verbessert. Um die Extrapolationsfähigkeit zu untersuchen, wird die Vorhersagegenauigkeit des Modells mit Daten getestet, die sich in Bezug auf den Werkstoff und der Beschichtungszusammensetzung deutlich von den Trainingsdaten unterscheiden. Dazu wurden mehrere Schweißexperimente mit Werkstoffen verschiedener Hersteller durchgeführt und nur ein Teil der Daten in das Training einbezogen. Die Ergebnisse dieser Arbeit verdeutlichen den positiven Einfluss der Prozesssignale auf die Robustheit des Modells und die Skalierbarkeit der Algorithmen künstlicher neuronaler Netze auf Daten außerhalb des Trainingsraums.

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Comparison of Ethereum Smart Contract Analysis and Verification Methods

2024 , Happersberger, Vincent , Jäkel, Frank-Walter , Knothe, Thomas , Pignolet, Yvonne Anne , Schmid, Stefan

Ethereum allows to publish and use applications known as smart contracts on its public network. Smart contracts can be costly for users if erroneous. Various security vulnerabilities have occurred in the past and have been exploited causing the loss of billions of dollars. Therefore, it is in the developer’s interest to publish smart contracts that serve their intended purpose only. In this work, we study different approaches to verify if Ethereum smart contracts behave as intended and how to detect possible vulnerabilities. To this end, we compare and evaluate, different formal verification tools and tools to automatically detect vulnerabilities. Our empirical comparison of 140 smart contracts with known vulnerabilities shows that different tools vary in their success to identify issues with smart contracts. In general, we find that automated analysis tools often miss vulnerabilities, while formal verifiers based on model checking with Hoare-style source code annotations require high effort and knowledge to discover possible weaknesses. Specifically, some vulnerabilities (e.g., related to bad randomness) are not detected by any of the tools. Formal verifiers perform better than automated analysis tools as they detect more vulnerabilities and are more reliable. One of the automated analysis tools was able to find only three out of 16 Access Control vulnerabilities. On the contrary, formal verifiers have a hundred percent detection rate for selected tests. As a case study with a smart contract without previously known vulnerabilities and for a more in-depth evaluation, we examine a smart contract using a two-phase commit protocol mechanism which is key in many smart contract applications. We use the presented tools to analyze and verify the contract. Thereby we come across different important patterns to detect vulnerabilities e.g. with respect to re-entrancy, and how to annotate a contract to prove that intended the restriction and requirements hold at any time.

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Unified edge control for mobile robots based on VDA5050 and basys 4.0 - Architecture and interfaces

2024 , Vick, Axel , Behling, Sebastian , Gesien, Phillip , Funk, Eugen

Following the Industry 4.0 paradigm, flexible manufacturing systems are now researched and implemented to allow fast reaction on changing market conditions. The trend leads to the development of low volume and high mixture production. Here, automated guided vehicles (AGV) and autonomous mobile robots (AMR) interconnect machine tools and automated assembly stations. Current integration of mobile robots in industrial manufacturing processes often rely on single solutions by various equipment suppliers that are not compatible with each other. Extending the factory's intra-logistics with additional AGV applications results to raising number of control systems with specific MES-interfaces. To combine different mobile robots into a managed fleet with common master control is difficult and needs a lot of implementation effort. This work contributes with a proposed Unified Control System for Mobile Robots on three layers allowing direct control of robot tasks, single robots or even particular on-board components. The proposed unified interfaces extend the VDA5050 as a common specification towards a fully open mobile robot control system using ROS together with an AAS-based automation middleware BaSys 4.0. The experiments show the feasibility of such distributed control system for mobile robots even in unknown and unstructured environments. Three case studies were carried out to assess the installation time of mobile robots in new applications. This installation time is reduced to 30 minutes including mapping, definition of points-of-interest (POI) as well as first mission design.

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Wire Electron Beam Additive Manufacturing von niedriglegierten Zinnbronzen – Erreichbare Bauteileigenschaften und Prozessmerkmale

2023-12-05 , Raute, Maximilian Julius , Seitz, Georg , Biegler, Max , Rethmeier, Michael

Die Additive Fertigung gewinnt zunehmend an Bedeutung für die Verarbeitung von Kupferwerkstoffen im industriellen Umfeld. Hierbei wird verstärkt auf drahtförmige Ausgangswerkstoffe gesetzt, da diese Vorteile im Handling bieten, bereits aus der Schweißtechnik bekannt sind und sich zumeist durch geringere Beschaffungskosten auszeichnen. In den letzten Jahren entwickelte sich unter den drahtbasierten Verfahren der Directed-Energy-Deposition (DED) eine Prozessvariante unter Nutzung des Elektronenstrahls zur industriellen Marktreife. Dabei zeigt die Technologie Wire Electron Beam Additive Manufacturing (DED-EB) besondere Vorteile gegenüber anderen DED-Prozessen für die Anwendung an Kupfer. Um das Verfahren einem breiten Anwenderkreis in der Industrie zugänglich zu machen, fehlen jedoch Daten zu Leistungsfähigkeit, Prozessgrenzen und Anwendungsmöglichkeiten. Die vorliegende Untersuchung beschäftigt sich mit dieser Problemstellung am Beispiel der Legierung CuSn1MnSi. Über mehrstufige Testschweißungen werden die physikalisch möglichen Prozessgrenzen ermittelt und Rückschlüsse über die Eignung der Parameter zum additiven Aufbau gezogen. An verschiedenen additiv gefertigten Probekörpern werden anschließend Kennwerte für Aufbaurate, Härte, Mikrostruktur, Oberflächenqualität sowie mechanische Festigkeitswerte ermittelt. Es zeigt sich, dass das die durch DED-EB hergestellten Proben, trotz des groben Gefüges sowie der thermischen Belastung im Aufbauprozess, in ihren Eigenschaften gut mit den Spezifikationen des Ausgangsmaterials übereinstimmen.

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Dynamic error characteristics of robot motion analyzed for the suitability of visual-servoing

2024 , Radke, Marcel , Haninger, Kevin , Kröger, Ole , Krumpek, Oliver

The knowledge of the absolute positioning accuracy of a robotic arm is crucial to assess the feasibility of certain tasks. In evaluating the feasibility, a robot manipulator as well as a possibly external sensing system must be chosen. In choosing a robot arm, lightweight robots are often preferred because they require less safety precautions, but they can also be less accurate compared to a stiff industrial robot. A stiff industrial robot resists external loads better, resulting in a higher accuracy with payload or process forces, and oscillates less in motions. Additionally, typical robot inaccuracies must be considered: (i) absolute positioning errors due to kinematic model errors, (ii) error due to resonance or external forces, (iii) path-following errors from limitations in the dynamic model and control. For tasks where the goal object has an unknown or varying pose, its pose can be measured with a vision system and used to compensate the robot motion. When the measurement and compensation is done continuously, it realizes closed-loop visual servoing. This can reduce the absolute error, but only the components of the error which are of a low frequency relative to the motion control bandwidth of the robot. To evaluate whether a specific robot can meet a certain accuracy requirements with a visual servoing system, better understanding about the characteristics of the robot error is needed. For example, the frequency distribution of the robot error can indicate what proportion can be compensated with closed loop control - only that less than the position bandwidth of the robot (typically 3-7 Hz). Datasheets typically provide the accuracy value only for repeatability while the accuracy during motion and the influence of dynamic effects are ignored. If the endeffector oscillates during motion causing a positional error and at which frequency is typically not reported - leaving unanswered, if it can be compensated by control. The contribution of this paper is the experimental evaluation of an absolute accuracy during the robot motion, towards evaluating the accuracy with a visual servoing system. A tracker system is used to collect the motion data of a CNC milling machine, a Universal Robots UR5, and an industrial robot (Comau Racer7-1.4) under various motion speeds. The frequency distribution and histograms of the error are analysed with regard to possible sources and the suitability to reduction with visual servoing.

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Energy efficiency measures for metal forming using hydraulic and mechanical presses

2024 , Preuß, Mandy , Thiele, Gregor , Krüger, Jörg

In conventional hydraulic presses only around 13 percent of the energy supplied is converted into the plastic forming of the metal. Mechanical presses achieve an overall efficiency of 13 to 30 percent. A variety of approaches aspire efficiency improvements by tuning process parameters. For the operation engineers it is a crucial task to find measures which are both technical suitable and economical promising. This paper summarizes popular tuning parameters and presents the assessment by seven experts who participated in semi-structured interviews. For hydraulic presses, the most recommend tuning parameter to be adjusted is the pressing force. For mechanical presses the continuous stroke operation is the most popular measure.

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Laser-Pulver-Auftragschweißen von funktional gradierten Materialien auf Cobalt-Chrom Basis

2023-11 , Marquardt, Raphael , Biegler, Max , Rethmeier, Michael

Um Bauteile vor Verschleiß und Korrosion zu schützen werden Beschichtungen aus resistenteren Materialien aufgetragen. Hierzu zählen unter anderen die Legierungen auf Cobalt-Chrom Basis. Der diskrete Materialsprung ist jedoch unter thermischen und mechanischen Belastungen häufig Ursache für das Versagen der Beschichtung. In dieser Arbeit werden daher Materialgradierungen von verschiedenen Stahllegierungen zu einer Cobalt-Chrom Basislegierung untersucht. Die Ergebnissen werden dafür auch mit Resultaten zu vorangegangenen Untersuchungen verglichen. Kern der Arbeit bilden geätzte Schliffbilder der Materialpaarungen und Auswertungen mittels Farbeindringprüfung sowie die metallografische Bestimmung der Porosität. Ziel der Arbeit ist ein defektfreier Aufbau der funktional gradierten Materialpaarungen.