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34th CIRP Design Conference, CIRP 2024

作者： Giani, Marco Walker, Moritz Neubauer, Michael Frank, Nelly Wiener, Patrick Verl, Alexander Robert Bosch GmbH Robert-Bosch-Campus 1 Renningen71272 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 Stuttgart70174 Germany

The migration of field-level automation systems to an edge-cloud hosted on premises can reduce the operation costs of a manufacturing line and increase its flexibility thanks to computation scalability and use of cloud-native operation concepts. Nonetheless, due to the novelty of the concept, a transparent life-cycle costs (LCC) assessment for edge-cloud automation systems (ECASs) is complex to achieve. In particular, uncertainties concerning costs related to the engineering and operation of an ECAS, such as commissioning delays or unexpected failures, increase the risks of investments towards its adoption. In this paper we propose a sensitivity analysis approach based on Monte Carlo (MC) life-cycle simulations. Through the approach, design parameters of an edge-cloud are investigated concerning their impact on the magnitude and distribution of LCC. The use of the approach is tested on a real-world case study to optimize the choice of the edge-cloud components and reduce the economic risks for its adoption. The proposed approach is expected to be integrated in early stages of the design process of a production line to identify cost-viable designs of ECASs, thus fostering the transition towards smart manufacturing systems. © 2024 The Authors. Published by Elsevier B.V.

关键词： Smart manufacturing

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Improved control for the Impact Actuator

Improved Control for the Impact Actuator

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European control Conference (ECC)

作者： Alexander Schulte Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

The impact actuator uses the momentum transfer during mechanical impacts to accelerate linear feed axes. As a result, nearly abrupt changes in velocity can be achieved. So far, the impact and thus the velocity change have been idealized as abrupt within the controller. Since very high but not infinite accelerations occur, no actual jumps in velocity can be achieved, resulting in position and contour errors at corners in planned trajectories. In this paper, an extended control method is considered which takes into account these physical limitations of the approach in order to improve the system behavior. Using a reference trajectory, a comparison is made between regular trajectory planning, the previous control method with idealized impacts, and the new approach with improved control.

关键词： Actuators Systematics Trajectory planning Force Dynamics Europe Trajectory

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High Bandwidth Force control for Robotic Friction Stir Welding

High Bandwidth Force Control for Robotic Friction Stir Weldi...

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Iberian Robotics Conference (ROBOT)

作者： Valentin Kamm Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Due to their flexibility and cost efficiency, industrial robots are increasingly being used for manufacturing processes. One such process is friction stir welding, which places high demands on the manipulator due to the high process forces and force gradients involved. The high compliance of industrial robots compared to traditional machine tools necessitates the implementation of force control for robotic friction stir welding. This paper presents an approach to increasing the bandwidth during force control of robotic friction stir welding. To achieve this, an industrial robot is controlled through an open control architecture, which offers the possibility to employ advanced force control structures. An admittance controller with inner velocity loop and a parallel force controller are compared to the state-of-the-art external force controller and validated in a digital twin of the robot. The most promising structure of the admittance controller is then implemented and validated on the test system, demonstrating an increase in accuracy and efficiency.

关键词： Service robots Welding Friction Force Bandwidth Industrial robots Digital twins Admittance Force control Robots

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Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series

Modeling Load-, Velocity-, and Temperature-Dependent Transmi...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Christian J. E. Bauer Valentin Kamm Marcel Dzubba Lukas Steinle Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Stuttgart Germany

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Industrial robots are rarely used for machining tasks due to their limited path accuracy. This accuracy is mainly limited by inaccuracies in the drive trains. Compliance and transmission errors occur in the joint gearboxes. While transmission errors have been extensively studied for strain wave gears, there is little research on these errors in cycloidal drives. This gearbox type is commonly used in industrial robots for medium to heavy payloads. It is proposed to model the mainly periodic transmission errors using a Fourier series where amplitude and phase are defined as a polynomial function of the main influence factors load-torque, velocity, and temperature. Measurements of the transmission errors were conducted using an experimental setup representing a single robot joint. In the evaluation of the measurement data, harmonic frequencies were related to mechanical properties of the cycloidal drive. These frequencies were used to identify the parameters of the polynomial Fourier series model. Compared to validation measurements, the derived model shows an average root mean square error of 0.026 mrad. It is proposed to use the output of the resulting model in a feedforward control approach to compensate the transmission errors and to increase the path accuracy of industrial robots.

关键词： Temperature measurement Accuracy Temperature Gears Measurement uncertainty Industrial robots Polynomials Frequency measurement Fourier series Load modeling

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Learning Compensation of the State-Dependent Transmission Errors in Rack-and-Pinion Drives

Learning Compensation of the State-Dependent Transmission Er...

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European control Conference (ECC)

作者： Lukas Steinle Valentin Leipe Armin Lechler Alexander Veri Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Rack-and-pinion drives are commonly used in large machine tools to provide linear motion of heavy loads over long travel distances. A key concern in this context is the achievable path accuracy, which is limited by assembly and manufacturing tolerances of the gearing components in conjunction with load-dependent deformation and the inherent backlash of the system. To address this issue, this paper presents a method for robust modeling of the individual and state-dependent transmission errors of a drive utilizing a two-stage machine learning approach. Based on this, the position control is extended to include an error compensation, which suppresses the modeled deviations in the mechanical system including the position-dependent backlash. The achievable increase in path accuracy as well as the robustness of the approach are evaluated and quantified by an experimental validation on a system with industry standard components.

关键词： Deformable models Training Accuracy Deformation System dynamics Training data machine learning

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Methods for Localization in Multi-Scale Material Flow Simulation for Virtual Commissioning

Methods for Localization in Multi-Scale Material Flow Simula...

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Electrical, Computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Annika Kienzlen Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

While the importance of virtual commissioning is increasing and not only individual machines but also production lines are being simulated, the simulation of material flow for numerous piece goods is still a challenge. Combining models in a multi-scale simulation can exploit their advantages. The macroscopic flow model excels at modeling the behavior of large quantities of piece goods, however, it cannot provide information about individual piece goods. This led to the approach of the combination with a microscopic physics-based model in a multi-scale material flow simulation. To switch between models, the coordinates of the positions (microscopic) have to be translated in one direction into the material description of the macroscopic flow model (the density distribution). In the other direction, the density distribution has to be translated into the coordinates of the positions, leading to a computationally intensive optimization problem. This paper develops various methods for finding a start solution and compares them to a method of the state of the art. The evaluation is based on their accuracy with reference to various parameters of the data set. The results show the best accuracies for the method which traverses the density distribution and calculates the sum of the densities until it matches a single piece good. Depending on the accuracy required, it may be possible to use the start solution directly without further optimization.

关键词： Location awareness Accuracy Mechatronics Computational modeling Microscopy Switches Production Optimization

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Towards Efficient Real-Time Model Adaption for Online Simulation at machine Level 2

Towards Efficient Real-Time Model Adaption for Online Simula...

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2nd International Conference on Intelligent control and Computing, IC-C 2024

作者： Deubert, Darius Zhou, Zhibo Selig, Andreas Verl, Alexander Bosch Rexroth AG Lohr am Main Germany Robert Bosch GmbH Corporate Sector Research and Advance Engineering Renningen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (纸本)9798350351873

The simulation of components, machines or plants provides many benefits in today's manufacturing. Online simulation, in this context, means that a system is simulated in parallel to its operation. This is beneficial to extract relevant information from the system, which could be used for control, monitoring, service or maintenance of the industrial system. To ensure the reliability of online simulation, especially for dynamically changing behavior, an online adaption of the simulation models is necessary. Real process data and further observations should be used to track the real behavior with the online simulation. This requires metrics to compare simulation with reality, an appropriate triggering mechanism for the adaption, suitable parameter selection and estimation methods to determine optimal model parameters. There are a lot of mathematical tools, which could be considered to solve these problems. However, all of them have individual characteristics regarding their suitability for online simulation. This paper gives an overview of methods that are needed for online model adaption in form of a narrative review and assesses them based on their applicability for real-time online simulation. Furthermore, it addresses realization challenges and adaption of first-principle models. This work therefore provides a theoretical foundation for real-time model adaption for online simulation at machine level. © 2024 IEEE.

关键词： Smart manufacturing

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Cobot for Automated Vision Data: Streamlining Production with Automated Annotations for machine Learning

Cobot for Automated Vision Data: Streamlining Production wit...

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Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), International Conference on

作者： Manuel Zürn Marcel Dzubba Colin Reiff Samed Ajdinović Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

Robotic vision tasks require a large amount of annotated data for effective training and performance. However, the manual creation of such datasets is a complex and time-consuming process. Particularly for smaller companies or those with high product variability, there is a need to optimise the resources dedicated to creating datasets for machine vision applications. This paper investigates novel ways to acquire annotated vision data through the integration of collaborative robots. Two methods are outlined to streamline the generation of annotated datasets. One of these methods is then used to construct a dataset tailored for 6D robotic gripping of an automotive connector. The effectiveness of automated annotated dataset generation is demonstrated by training a deep learning model to accurately estimate the orientation of the automotive connector.

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RTNNIgen – An Open-Source PLC Library and Python Generator Converting Keras Models to Realtime Capable Structured Text

RTNNIgen – An Open-Source PLC Library and Python Generator ...

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Annual Conference of Industrial Electronics Society

作者： Christoph Hinze Zexu Zhou Haijia Xu Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Recent advances in AI research are boosting the relevance of realtime neural networks in automation technology. To facilitate the deployment of trained neural networks for realtime applications, where hard limits on upper cycle time are required, this paper contributed a two-fold approach: A Python library for parsing Keras sequential models to structured text using a single function-call, which can be run directly on industrial PLCs and a structured text library to encapsulate reoccurring code and to provide a readable, tested interface for the generated code. The resulting models are experimentally validated regarding their inference time and precision of the outputs.

关键词： Software design Runtime Computational modeling Neural networks Predictive models Libraries Hardware Data models Python Periodic structures

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A Digital Twin Platform for service-based Testing and Optimization

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Procedia CIRP 2024年 126卷 260-265页

作者： Shengjian Chen Michael Neubauer Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany

The use of digital twins enables the trend toward a flexible and dynamic production system. As an aspect of digital twins, virtual commissioning models are used to test machines in the engineering phase, before they are even built. These models, however, are no longer used after the engineering phase. In this paper, a concept is presented, for utilizing these models during the production phase in order to optimize the production process. In addition, simple geometrical faults can be detected in the virtual commissioning model and optimized before the control program of the product is deployed on the real machine.

关键词： digital twin platform simulation virtual commissioning software-defined manufacturing

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