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Automated Manufacturing Toolchain using Skill-based Digital Twins

Procedia CIRP 2024年 128卷 923-928页

作者： David Dietrich Michael Neubauer Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany

Digital twins with a skill-based description are increasingly finding their way into industrial production. Their models link properties of a product with available process capabilities that are realized by resource skills. A matchmaking derives capable resources, e.g. for modular assembly systems. For capability-based planning in manufacturing, integration with computer-aided design (CAD) and computer-aided manufacturing (CAM) programs is missing. This paper presents an automated toolchain with focus on subtractive manufacturing using skill-based digital twins. Product-Process-Resource (PPR) models are used and enriched with subtractive manufacturing information and further relations. A configurator allows the design of the individual digital product twin, which can synchronously be generated as a 3D model using a CAD service. Necessary subtractive manufacturing steps including capable resources are then determined in a planning environment and fed into the CAM system. This allows an individual generation of machining code based on PPR information, which can be validated on a simulation model. The result is an automated tool chain of different software services, which are composed by a common description of the PPR model and the software services themselves. By defined models and interfaces the toolchain is not restricted to subtractive manufacturing but enables the integration of computer-aided everything (CAx) services.

关键词： Skill-based manufacturing Digital twins Design methodology tools technologies

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Towards learning digital twin: case study on an anisotropic non-ideal rotor system 57

Towards learning digital twin: case study on an anisotropic ...

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18th IFAC Workshop on Time Delay Systems, TDS 2024

作者： Zhou, Zhibo Walther, Michael Verl, Alexander Robert Bosch GmbH Robert Bosch Campus 1 Renningen71272 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstraße 36 Stuttgart70174 Germany

In the manufacturing industry, the digital twin (DT) is becoming a central topic. It has the potential to enhance the efficiency of manufacturing machines and reduce the frequency of errors. In order to fulfill its purpose, a DT must be an exact enough replica of its corresponding physical object. Nevertheless, the physical object endures a lifelong process of degradation. As a result, the digital twin must be modified accordingly in order to satisfy the accuracy requirement. This article introduces the novel concept of"learning digital twin (LDT)," which concentrates on the temporal behavior of the physical object and highlights the digital twin's capacity for lifelong learning. The structure of a LDT is first described. Then, in-depth descriptions of various algorithms for implementing each component of a LDT are provided. The proposed LDT is validated on the simulated degradation process of an anisotropic non-ideal rotor system. © 2024 The Authors.

关键词： Anisotropy

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Case Study on using Layer Laminate Manufacturing for Large Lightweight Parts with high Structural Damping

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Procedia CIRP 2024年 130卷 28-34页

作者： Nico Helfesrieder Florentin Furcoi Oliver Jud Armin Lechler Alexander Verl University of Stuttgart Institute for Control Engineering of Machine Tools and Manufacturing Units Seidenstraße 36 70174 Stuttgart Germany

Layer Laminated Manufacturing (LLM) enables the inner optimization of parts through the joining of individually structured layers. Particularly for high-volume metal parts, for which structural optimization and additive manufacturing is possible but typically too expensive, LLM can offer a good alternative. Using adhesive bonding to join the layers, stiffness is expected to decrease, but part damping may be increased strongly. These effects have already been shown individually, but using scientific examples rather than real world examples. Therefore, this paper presents a case study that investigates the extent to which lightweight design and damping can be applied specifically by LLM with adhesive bonding. For this, a machine table of a feed axis is topology optimized, manufactured using the LLM-method, and examined experimentally. The validation includes experimental modal analysis, static bending tests and damping identification in the installation situation. The results indicate high design freedom and lightweight potential for large metallic parts. Additionally, the damping is significantly increased in the isolated examination, but only minor improvements are recognizable in the actual installation situation.

关键词： Layer Laminated Manufacturing (LLM) Laminated Object Manufacturing (LOM) Lightweight Damping Experimental Modal Analysis (EMA)

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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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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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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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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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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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