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Quantitative Evaluation of Automated Behavior Model Creation for Applications of Industrial Automation

Procedia CIRP 2024年 130卷 1327-1333页

作者： Valentin Stegmaier Tobias Eberhardt Nasser Jazdi Michael Weyrich Graduate School of Excellence advanced Manufacturing Engineering (GSaME) University of Stuttgart Nobelstraße 12 70569 Stuttgart Germany Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 70569 Stuttgart Germany J. Schmalz GmbH Johannes-Schmalz-Straße 1 72293 Glatten Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstraße 36 70174 Stuttgart Germany

Creating behavior models for Digital Twins manually requires significant effort, which hinders their widespread use. One possible solution involves using automated approaches to create behavior models. There are several approaches available in literature. Different articles assume that automated creation of behavior models is superior to manual creation, but to provide comprehensive proof, an expert benchmark is necessary. This article conducts such a benchmark with 10 experts setting up 9 different behavior models. The recorded times are compared with an automated method for creating behavior models. The manual creation takes up to 54 times more time compared to the automated method.

关键词： Behavior Models Evaluation Quantitative Automated Creation Bechmark Industrial Automation

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Patterns and tools in Robotic systems Integration

Patterns and tools in Robotic Systems Integration

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IEEE International Conference on Robotic Computing (IRC)

作者： Nadia Hammoudeh Garcia Andreas Wortmann Robot and Assistive Systems Department Fraunhofer Institute for Manufacturing Engineering and Automation (IPA) Nobelstr. 12 Stuttgart Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 Stuttgart Germany

ISBN: (纸本)9781665472616

Software integration activity is crucial to develop robotic applications. However, there is little specific literature dedicated to the integration process in robotics. The research in this field today is mostly focused on a concrete implementation phase and on the development of new technologies, but few researchers target their integration as an application-agnostic process. To shed light on the state of robotics software integration, we conducted a survey among researchers and practitioners in the field. As part of this survey we inquired how robotics software integration is currently performed. This study allowed us to find patterns in the way this process is carried out.

关键词： System integration Software Robots

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control architecture for embedding reinforcement learning frameworks on industrial control hardware 2020

Control architecture for embedding reinforcement learning fr...

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3rd International Conference on Applications of Intelligent systems, APPIS 2020

作者： Schmidt, Alexander Schellroth, Florian Riedel, Oliver Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781450376303

Using reinforcement learning to find new control strategies for manufacturing processes is a promising approach. However, in order to use reinforcement learning in a manufacturing environment, industrial requirements must be met. In this paper, a new control architecture is proposed that allows reinforcement learning frameworks to be executed on programmable logic controllers, which implies requirements regarding real-time execution. An agent exchange module is presented, that allows to automatically load agents from a non real-time learning environment to a control program running in a real-time environment of a programmable logic controller. The proposed architecture is evaluated on an experimental setup with a non-linear process and commercial off-the-shelf control hardware, to meet industrial requirements. A genetic algorithm is used to learn new control strategies without having prior knowledge of the system. © 2020 ACM.

关键词： Genetic algorithms

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Development of a mechanical, biocide-free method of disinfection for cathodic dip coating processes 21

Development of a mechanical, biocide-free method of disinfec...

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21st International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2021

作者： Uhlmann, E. Hilt, M. Hein, C. Cudazzo, M. Huth-Herms, K. Jahnke, C. Quast, M. Fraunhofer Institute for Production Systems and Design Technology IPK Germany Fraunhofer Institute for Manufacturing Engineering and Automation IPA Germany Institute for Machine Tools Factory Management IWF Technische Universität Berlin Germany

ISBN: (纸本)9780995775190

Technical fluids are often contaminated by bacteria as Burkholderia cepacia (B. cepacia), which is found in different industrial issues and affects manufacturing process chains by the formation of planktonic cell-aggregates and biofilms within the working fluids. B. cepacia is one of nine species of the Burkholderia cepacia complex (Bcc), a group of gram-negative, motile, non-spore-forming, and rod-shaped bacteria. Because of the opportunistic pathogenicity to plants, animals, humans, and the multi-drug and biocide resistance, B. cepacia is difficult to treat. This study aims to provide an application to reduce the germ numbers ng in an eco-friendly and continuous process without the use of biocides. The approach to disinfect technical fluids is to apply high shear forces in a rotor-stator assembly to the fluid. A prototype of the rotor-stator assembly with a variably adjustable shear gap gs and rotor speed srot was constructed. First experiments with a frequency frot 10 Hz ≤ frot ≤ 40 Hz a shear gap gs = 83 µm and gs = 166 µm showed a reduction of germ number ngr = 99.6 %. It concluded that the disinfection of technical fluids by a rotor-stator assembly is a biocide-free alternative. In addition to defined process parameters such as shear gap gS, temperature ϑ, frequency frot and time of machining process tmp, also the peripheral speed vp, rotational speed vrot, flow rate fr and shear stresses τ were used to assess the machining result and to develop an overall concept for disinfection of technical fluids. © 2021 Proceedings of the 21st International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2021. All rights reserved.

关键词： Stators

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Web-Based Tracing for Model-Driven Applications

Web-Based Tracing for Model-Driven Applications

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Euromicro Conference on Software engineering and Advanced Applications (SEAA)

作者： Jörg Chrisitian Kirchhof Lukas Malcher Judith Michael Bernhard Rumpe Andreas Wortmann Software Engineering RWTH Aachen University Aachen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Stuttgart Germany

Logging still is a core functionality used to understand the behavior of programs and executable models. Yet, modeling languages rarely consider logging as a first-level activity that is manifested in the language through modeling elements or their behavior. When logging is part of the code generated for the respective models or the corresponding runtime environment only, it must be generic, as the modeler cannot influence, through the models, what and when logging takes place. To enable modelers to log model behavior, we devised a method based on language extension and smart code generation that can integrate logging into arbitrary textual modeling languages. Based on this method, log entries can be produced, traced, and presented through a web application. This method and its infrastructure can facilitate lifting logging to the model level and, hence, improve the understanding of executable models.

关键词： Runtime environment Codes Software Behavioral sciences Software engineering

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Decentralized Motion control for a Novel Planar Motor Intralogistics System

Decentralized Motion Control for a Novel Planar Motor Intral...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Lukas Steinle Nico Helfesrieder Armin Lechler Alexander Verl Ali Montazeri Jinfan Wang Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany FL Technology GmbH Griesheim Germany FL Technology GmbH Southern University of Science and Technology Shenzhen China

Modern production environments place high demands on the logistics systems that are used. High flexibility and high throughput are expected, combined with high availability and efficient operation. To meet these requirements, this paper presents a novel intralogistics system based on the functionality of a planar motor. Following the operating principle of a moving stator, the vehicles are entirely passive and the hardware for the generation of motion is integrated into the floor. This is achieved in the form of compact, decentrally interconnected floor units, several of which are simultaneously involved in a motion. In order to control this system with satisfactory reliability and performance, the theoretical foundations for a proper understanding of the system are examined before a system model is derived and parameterized through measurements. On this basis a specifically designed motion control system is developed, that features precise planar movement, decentralized computation and compensation of position dependent characteristics. Thereafter, a method for model-based parameterization is outlined, that takes into account robustness against disturbances and parameter variations. Finally, the developed approach is implemented on the actual hardware and validated in experimental investigations in terms of path accuracy.

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A Novel Approach for Unsupervised Sensor Error Classification

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Procedia CIRP 2024年 130卷 206-213页

作者： Samiha Durnagöz Tobias Eberhardt Felix Fuchs Peter Reimann Thomas Ackermann Maik Fiedler Mathias Mayer Marco F. Huber Alexander Verl Graduate School of Excellence advanced Manufacturing Engineering GSaME University of Stuttgart Nobelstraße 12 70569 Stuttgart Germany Institute of Industrial Manufacturing and Management IFF University of Stuttgart Allmandring 35 70569 Stuttgart Germany AUDI AG NSU-Straße 1 74172 Neckarsulm Germany Fraunhofer Institute for Manufacturing Engineering and Automation IPA Nobelstraße 12 70569 Stuttgart Germany Institute for Control Engineering of Machine Tools and Manufacturing Units ISW University of Stuttgart Seidenstraße 36 70174 Stuttgart Germany J. Schmalz GmbH Johannes-Schmalz-Straße 1 72293 Glatten Germany Institute of Parallel and Distributed Systems (IPVS) Universitätsstraße 38 70569 Stuttgart Germany

The precise detection and classification of sensor errors is crucial for the optimal operation of smart manufacturing systems. Sensor errors, which can manifest in various forms, such as drifts or constant values, significantly challenge data integrity. This work introduces a novel approach that combines unsupervised learning and system simulations to detect and classify relevant sensor errors. Our approach avoids extensive manual labeling and uses only error-free simulated time series data to create initial embeddings of sensor data. This establishes a baseline for normal sensor behavior. To facilitate a precise identification of error types through a classifier, simulated sensor errors are introduced to create context-aware embeddings. We further analyze and compare conventional to advanced embedding methods such as TS2Vec. We apply our approach to a synthetic dataset obtained from a vacuum handling system and accurately identify and classify relevant sensor error types. Our work contributes to advancing operational efficiency and reliability in automated manufacturing processes within the Industry 4.0 framework by improving the detection capabilities for sensor errors.

关键词： Unsupervised learning Sensor errors TS2Vec System simulation

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Data Model for Adaptive Robotic Construction in Architecture

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Procedia CIRP 2022年 107卷 1035-1040页

作者： Martin Wolf Benjamin Kaiser Sebastian Hügle Alexander Verl Peter Middendorf Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany Institute of Aircraft Design University of Stuttgart Pfaffenwaldring 31 D-70569 Stuttgart Germany

Robotic fabrication plays an essential role for the construction industry in the pursuit of higher productivity and greater flexibility. Modular robotic systems enable the off-site prefabrication of components for high-performance building systems from wood or fiber composites, while digital planning methods and computational design enable the efficient planning of highly specialized and unique lightweight structures. However, existing manufacturing systems do not provide an interface between the two domains that allows to utilize their combined potential. manufacturing instructions for the individual components are currently generated directly from the design model and don’t consider the precise setup and configuration of the modular system. The parametric description in computational design thus ends in the planning phase and is converted into a non-parametric description in native robot code, losing a lot of information in the process. For a continuous description of the building components from planning to fabrication, a data model for the parametric description of the fabrication tasks is therefore needed. We present and such a data model for timber and fiber prefabrication applications. The model allows the generic description of the manufacturing process within a task graph, which gives the manufacturing system a way of adapting the tasks to its specific configuration and setup. In addition to the description of jobs, tasks and actions, the model also includes a description of the considered manufacturing environment, as well as a monitoring component for the acquisition of sensor values and system configurations for individual tasks. This not only allows the identification of manufacturing issues like collisions ahead of time, but also enables the implementation of a feed-back loop for iterative optimization of the paths for any given environment. In this work, we give the design considerations for this data model.

关键词： Co-Design CAD CAM Iterative CAM Robotic Construction Data Model

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Time-optimal Path Planning of Multi-axis CNC Processes Using Variability of Orientation

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Procedia CIRP 2021年 96卷 324-329页

作者： Frederik Wulle Max Richter Christoph Hinze Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstrasse 36 70174 Stuttgart Germany

In multi-axis processes, such as welding or 3D printing, the determination of the orientation of the tool relative to the workpiece is usually determined by technology-dependent geometric algorithms. In the simplest case, the orientation of the tool is defined according to the surface normal vectors of the workpiece surfaces. However, with large curvature gradients, this method can lead to jumps in the orientation which lead to unwanted stopping of the translational motion. In the linear interpolation of this movement, the path speed usually decreases significantly due to the relatively large compensating movement of a kinematic system. This type of path movement usually has negative effects on the CNC process, which requires constant path velocities. This paper describes a method for time-optimized path planning that utilizes the orientation tolerances of multi-axis processes. Orientation tolerances are process-dependent tolerances that indicate which orientation ranges (angular positions) from tool to workpiece are permissible without decreasing the process quality. The potential time savings of this method are shown with an extreme example of a planar 3-axis kinematics and on an industrial 7-axis CNC system.

关键词： Dynamics Additive manufacturing machine tool Optimization Tool path

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Learning Feedforward control for Laser Powder Bed Fusion

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Procedia CIRP 2021年 96卷 127-132页

作者： Colin Reiff Wolfgang Bubeck Daniel Krawczyk Maximilian Steeb Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstrasse 36 70174 Stuttgart Germany

Additive manufacturing is becoming increasingly important for industrial applications. Especially laser powder bed fusion processes play a decisive role. However, the technology often lacks in reliability and part quality due to complex process interactions and disturbing influences. To counteract these limitations, a flexible and high-dynamic control of relevant process parameters, taking into account the transient process conditions, is indispensable. Currently, the most process parameters are often kept constant, since the used control systems do not offer real-time capable interfaces for intervention. To enable the adjustment of parameters during the process, an open control architecture for galvanometer scanners and laser sources was developed. The architecture is based on an industrial control system in combination with a field-programmable gate array (FPGA) communicating via a real-time fieldbus. The novel control architecture is used to integrate a model-based feedforward control, adjusting the laser power, scan speed and scan strategy based on the current powder bed temperature calculated by a two-dimensional thermal model during run time. An integrated learning algorithm autonomously tunes the process parameters during the manufacturing process and determines the optimal combination of laser power, scan speed and powder bed temperature to achieve a homogeneous melt pool. On average, the standard deviation of the powder bed temperature along the scan path was reduced by 48% for the simulated test cases.

关键词： Additive manufacturing Laser Powder Bed Fusion Feedforward control

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