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8th CIRP Global Web Conference on Flexible Mass Customisation, CIRPe 2020

作者： Schmucker, B. Trautwein, F. Semm, T. Lechler, A. Zaeh, M.F. Verl, A. Boltzmannstr. 15 Garching b. München85748 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units Seidenstr. 36 Stuttgart70174 Germany

State of the art machine tool controllers offer several Internet-of-Things (IoT) interfaces for machine data acquisition using industrial or edge computers. However, the available data exchange rates for these communication platforms are limited to a few hundred Hertz. As the data is not available in high frequency resolution, such a network communication is not suitable for monitoring and optimizing highly dynamic machining processes. This paper describes an efficient system architecture, which enables the acquisition of internal machine data as well as the high frequency sampling of external sensors. Based on this data, an Operational Modal Analysis (OMA) approach can be used to determine the tool tip dynamics during the machining process. Identification of tool tip frequency response requires the reconstruction of the excitation of the machine tool structure, i.e. the occurring machining forces. For this purpose, an approach relying on monitoring the commanded motor currents is applied. © 2020 Elsevier B.V.. All rights reserved.

关键词： Frequency response

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Integrative data processing for cyber-physical off-site and on-site construction promoting co-design

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Procedia CIRP 2021年 100卷 451-456页

作者： Carsten Ellwein Alexander Reichle Melanie Herschel Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany Institute Parallel and Distributed Systems University of Stuttgart Universit” atsstr. 38 D-70569 Stuttgart Germany

The term co-design describes a collaborative design process, usually across the boundaries of individual areas. A major aspect, and often an obstacle in the implementation of the co-design approach, is the establishment of a centralized data management system. In the past, the data management concept has been approached from different perspectives. Current approaches usually are oriented along the process chain and thus reflect a unidirectional flow of information. Neither the information feedback nor the reaction to adjustments in upstream model steps is supported, which makes continuous collaboration more difficult and at best reduces the co-design approach for continuous data usage. This paper addresses these weaknesses while outlining an integrative data processing concept enabling co-design between the domains of construction and industrial prefabrication. Geometrical information generated during architectural design and construction planning is reused for the production of components, manufacturing-related design adjustments are transferred back into the domain of construction. Changes throughout the entire process are centrally recorded. To ensure independence from the software tools used and to consider their great diversity, data exchange is largely based on standards, namely industry foundation classes and the standard for the exchange of product model data. In order to counteract the sequential processing according to a waterfall model and to support the co-design approach, the industrial prefabrication toolchain, consisting of computer-aided manufacturing software and downstream postprocessors, is largely automated, so that reprocessing of a workpiece for minor geometric adjustments no longer requires any interaction of the production planner.

关键词： Co-Design Data Processing AutomationML IFC STEP CAD CAM

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Connected production planning and control systems – Implementation and the optimization process for subcontracting 13

Connected production planning and control systems – Impleme...

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13th CIRP Conference on Intelligent Computation in Manufacturing engineering, CIRP ICME 2019

作者： Ellwein, Carsten Elser, Anja Vollmer, Marcel Riedel, Oliver Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 StuttgartD-70174 Germany University of Stuttgart Kepplerstr.7 StuttgartD-70174 Germany

Production planning and control (PPC) systems are used to organize operating materials. In order to address connectivity demands of interacting PPC systems a new software architecture has been presented in prior work. This software architecture provides a basis for data exchange in-between such systems. It is up to this paper to describe an implementation approach realizing the theory. Furthermore, a new optimization process which targets subcontracting, dynamics and communication of interconnected PPC systems is presented. As a result, the mandatory and optional content of an order enquiry as well as of a response message is discussed. © 2020 The Authors.

关键词： Industry 4.0

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Method for generating manufacturable, topology-optimized parts for Laminated Layer Manufacturing

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Procedia CIRP 2020年 93卷 38-43页

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

The great flexibility provided by generative manufacturing offers immense potential for the structural component optimization. However, this freedom needs to be utilized by appropriate CAx tools. In this paper, we present a novel slicing method, enabling the automatic generation of topology-optimized Laminated Layer Manufacturing (LLM) parts. With this method a part of arbitrary shape can be automatically sliced and equipped with a uniform virtual grid that is suitable for manufacturing. The optimal density distribution is then mapped onto the individual slices and locally approximated through the introduction of variably shaped cavities. By using 3D modeling techniques all LLM sheets are modeled parametrically and assembled automatically. To verify the functionality of the presented method, it is applied to two practical parts and compared with a conventional topology optimization method.

关键词： Topology Optimization Laminated Layer Manufacturing Sheet Lamination Hybrid Manufacturing Slicing

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Predicting coupling signals in a material flow real-time co-simulation with a Kalman filter

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Procedia CIRP 2020年 88卷 9-14页

作者： Annika Kienzlen Christian Scheifele Alexander Verl University of Stuttgart Institute for Control Engineering of Machine Tools and Manufacturing Units Seidenstr. 36 70174 Stuttgart Germany

A hardware-in-the-loop simulation has to use the control cycle as simulation clock. This time-deterministic clocking can be difficult to meet for complex behavior models in a real-time simulation. To accelerate a real-time simulation, the calculation can be parallelized by co-simulation whereby multiple, differently detailed behavior models can be simulated parallelly. In these multi-scale models, a slower, detailed model guides a fast, abstract model. In this work, a Kalman filter is examined as a multi-rate method to predict the signals of a physical-based model for a material flow simulation in real-time. To improve the results, smoothing and boundary conditions are added.

关键词： Hardware-in-the-loop simulation real-time co-simulation multi-rate methods multi-scale models Kalman filter

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Kinematic Multibody Model Generation of Deformable Linear Objects from Point Clouds

Kinematic Multibody Model Generation of Deformable Linear Ob...

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2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Markus Wnuk Christoph Hinze Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

control and localization of deformable linear objects (DLOs) require models to handle their deformation. This paper proposes an approach to automatically generate a model from available visual sensor information. Based on point cloud data obtained from a 3D stereo camera, the kinematics of a multibody model formulation are derived. The approach aims to balance the tradeoff between computational complexity and model accuracy. This is achieved with a geometric error criterion that reduces the introduced degrees of freedom (DOF) of the model to a necessary minimum, representing the continuous shape with as few bodies as possible. The approach is evaluated analytically and validated with an experimental scenario of DLO manipulation.

关键词： Deformable models Three-dimensional displays Computational modeling Kinematics Skeleton Data models Strain

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Nonlinear Trajectory control for Deformable Linear Objects based on Physics Simulation

Nonlinear Trajectory Control for Deformable Linear Objects b...

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Annual Conference of Industrial Electronics Society

作者： Christoph Hinze Manuel Zürn Markus Wnuk Armin Lechler Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

The handling of deformable linear objects (DLOs), such as cables or hoses, with industrial robots is hardly industrially automated due to the underactuated material behavior. Increasing computing power and decreasing cost of processors over the last decades are now allowing the online computation of more complex handling processes. Within this paper, DLOs are approximated as a multibody chain with a finite number of degrees of freedom. Based on that model, a nonlinear, partially IO-linearizing controller is derived to control an underactuated end point on a trajectory when grasped by a robot arm at the other end. The controller is verified in simulation for high dynamics and shown to significantly reduce the tracking error. A practical evaluation finally shows the qualitative suitability of the multibody approximation and is used to validate the functionality of the controller in an open-loop experiment.

关键词： Robots Trajectory Cameras Manipulators Deformable models Manipulator dynamics Grippers

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A software architecture for a multi-axis additive manufacturing path-planning tool

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Procedia CIRP 2020年 88卷 433-438页

作者： Martin Wolf Anja Elser Oliver Riedel Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany

Direct-deposition Additive Manufacturing technologies like Fused Deposition Modeling suffer from several drawbacks such as anisotropic mechanical properties which impair part quality. Multi-Axis Additive Manufacturing (MAAM) promises to significantly reduce these drawbacks. However, path-planning for the complex kinematics still poses a problem which has only been solved partly and for very specific applications. This paper proposes a software architecture for a general purpose path-planning tool for MAAM technologies enabling the simultaneous implementation of different strategies. The architecture is designed to be extensible, largely machine independent and enables granular multi-scale optimizations. First implementation results and illustrating examples demonstrate the modularity and extensibility.

关键词： Additive manufacturing Computer-aided manufacturing (CAM) Multi-axis additive manufacturing

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Prediction of the configuration of objects in a bin based on synthetic sensor data

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Procedia CIRP 2020年 88卷 54-59页

作者： Shan Fur Bilel Boughattas Alexander Verl Andreas Pott Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidentraße 36 D-70174 Stuttgart Germany

Bin picking describes a robot system that picks unsorted objects from a bin based on sensor data. The object recognition is one of the main difficulties when calculating the grasping pose. In the worst case, a faulty object recognition leads to a system standstill. This work introduces a framework concept for improving the object recognition by predicting the configuration of all the objects in the bin based on an initial scan in form of a point cloud. This is done by taking advantage of an online simulation, with the goal of reducing the total number of scan cycles, which leads to a reduced risk of failure and improves the overall performance of a bin picking system.

关键词： Neural Network Simulation 6D pose

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Deep Reinforcement Learning using Cyclical Learning Rates

arXiv

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arXiv 2020年

作者： Gulde, Ralf Tuscher, Marc Csiszar, Akos Riedel, Oliver Verl, Alexander Institute of Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart70174 Germany

Deep Reinforcement Learning (DRL) methods often rely on the meticulous tuning of hyperparameters to successfully resolve problems. One of the most influential parameters in optimization procedures based on stochastic gradient descent (SGD) is the learning rate. We investigate cyclical learning and propose a method for defining a general cyclical learning rate for various DRL problems. In this paper we present a method for cyclical learning applied to complex DRL problems. Our experiments show that, utilizing cyclical learning achieves similar or even better results than highly tuned fixed learning rates. This paper presents the first application of cyclical learning rates in DRL settings and is a step towards overcoming manual hyperparameter tuning. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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