检索结果-内蒙古大学图书馆

2nd IEEE Eurasia Conference on IOT, Communication and engineering, ECICE 2020

作者： Brovkina, Daniella Kienzlen, Annika Riedel, Oliver Stuttgart70569 Germany The Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart70174 Germany

ISBN: (纸本)9781728180601

Simulation models are used during the entire life cycle of a factory. Because of a factory's complexity, different simulation tools with different scope emerged over time. The holistic mapping requires coupled simulations that consider the factory from different perspectives. Each simulation requires a new tool and simulation model, which, up to now, has usually been created manually. This paper presents an analysis of existing approaches and data models for factory simulation description. These approaches allow data exchange between single simulation models, but do not provide dynamic coupling and model generation, and often cannot include all relevant information for the factory simulation. To achieve a continuous and comprehensive factory simulation, a concept for a metamodel for factory simulation description is outlined. Its goal is not only to describe a skeleton of the factory and provide simulation coupling and data exchange but also to provide a dynamic model generation. © 2020 IEEE.

关键词： Electronic data interchange

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Unsupervised Sensor Error Classification

引用

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

来源：评论

学校读者我要写书评

暂无评论

Prediction of the configuration of objects in a bin based on synthetic sensor data 13

Prediction of the configuration of objects in a bin based on...

引用

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

作者： Fur, Shan Boughattas, Bilel Verl, Alexander Pott, Andreas Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidentraße 36 StuttgartD-70174 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. © 2020 The Authors.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Shop-floor service connector - A message-oriented middleware focused on the usability and infrastructure requirements of SMEs developing smart services 3

Shop-floor service connector - A message-oriented middleware...

引用

3rd IEEE International Conference on Knowledge Innovation and Invention, ICKII 2020

作者： Strljic, Matthias Milan Vollmann, Chris Riedel, Oliver Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart70174 Germany Fraunhofer Institute for Industrial Engineering IAO Stuttgart70569 Germany

ISBN: (纸本)9781728193335

Digitalization causes an intensive change in the way software components are developed within the shop floor. The blending of technology domains with current automation technologies leads to high integration efforts with a low degree of reusability. This problem is further reinforced by a diverging system understanding within individual domains and the use of heterogeneous development platforms. Existing solutions from the field of cloud computing are applied in the context of the Industrial Internet of Things (IIoT). However, these systems do not fulfill the requirements of user-friendliness, resource demands, performance, and infrastructure, which is why they are only partially suitable for the current needs of small and medium-sized enterprises (SMEs). For this purpose, the communication middleware Shop-Floor-Service-Connector (SFSC) is developed. Based on the broker-less messaging system ZeroMQ, an overlaid SFSC protocol is implemented. Subsequently, an example scenario is used to illustrate the usage of the system. Finally, the next steps for further developing the middleware are presented. © 2020 IEEE.

关键词： Middleware

来源：评论

学校读者我要写书评

暂无评论

Orientation smoothing in multi-axis additive manufacturing

引用

Procedia CIRP 2022年 107卷 357-362页

作者： Maxime Chalvin Frederik Wulle Sébastien Campocasso Anja Elser Vincent Hugel Alexander Verl Université de Toulon COSMER Toulon France Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstraße 36 70174 Stuttgart Germany ARENA2036 e.V. Pfaffenwaldring 19 70569 Stuttgart Germany

In multi-axis processes, such as material extrusion like Fused Filament Fabrication (FFF), the orientation of the tool relatively to the workspace is usually set by the CAM software to an angle that is locally constant relative to the manufacturing surface. However, in the case of large curvature gradients or small curvature radius of the surface or the path, this method leads to significant variations of the tool orientation. These variation require large compensating movements of the axes to maintain the desired deposition tool orientation along the path. Kinematic constraints such as acceleration or jerk limits can lead to a reduction of the path velocity or noticeable positioning errors along the movement, as well as unwante vibrations, which means poor process conditions and defects in the parts. The paper presents a post path planning algorithm that allows smooth in of the tool orientation to avoid jerky compensation motion of the CNC system by varying the orientation within a defined tolerance. This tolerance depends on the deposition process, and is determined experimentally for a FFF process. The proposed methodology was successfully validated b the manufacturing of two sample parts using a robotic additive manufacturing cell.

关键词： Additive manufacturing Robot machine tool Optimization tool path

来源：评论

学校读者我要写书评

暂无评论

In-Process Workpiece Geometry Estimation for Robotic Arc Welding based on Supervised Learning for Multi-Sensor Inputs

In-Process Workpiece Geometry Estimation for Robotic Arc Wel...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Alexander Schmidt Christian Kotschote Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany AUDI AG Neckarsulm Germany

Due to manufacturing tolerances, the geometry parameters of workpieces are not constant in industrial welding applications. Today, this problem is addressed by either accepting fluctuating part quality or by measuring the geometry and adjusting the configuration of the robot and process controller for each individual part. However, measuring the geometry requires additional manufacturing time or reduces the accessibility of the welding tool. This paper presents an approach for estimating the workpiece geometry based on process data during the welding process, which eliminates the need of measuring the geometry in advance, yet provides the same accessibility of the welding tool. For this approach, a data set is generated by conducting welding experiments with varying part geometries. Welding current, welding voltage and acoustic emissions are recorded. Three supervised learning techniques, which are Support Vector machines, Random Forest Decision Trees and k-Nearest-Neighbors, are used to train models for estimating the geometry. The results show, that the trained models successfully estimate the part geometry with over 90% accuracy.

关键词： Geometry Support vector machines Service robots Welding Supervised learning Time series analysis Estimation

来源：评论

学校读者我要写书评

暂无评论

Foreword

Springer Proceedings in Advanced Robotics

引用

Springer Proceedings in Advanced Robotics 2025年 36 SPAR卷 v-vi页

作者： Huber, Marco Verl, Alexander Kraus, Werner Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany ISW-Institute for Control Engineering of Machine Tools and Manufacturing Units Universität Stuttgart Baden-Württemberg Stuttgart Germany

来源：评论

学校读者我要写书评

暂无评论

Cloud manufacturing: Theoretical localization within production theory 14

Cloud manufacturing: Theoretical localization within product...

引用

14th CIRP Conference on Intelligent Computation in manufacturing engineering, CIRP ICME 2020

作者： Henzel, Robert Ellwein, Carsten Herzwurm, Georg Riedel, Oliver Nobelstr. 12 Stuttgart70569 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 StuttgartD-70174 Germany University of Stuttgart Department of Information Systems II Keplerstr. 17 Stuttgart70174 Germany

The industrial production landscape is significantly affected by digitization. In the course of this development, various production paradigms have been proposed, such as ubiquitous manufacturing, distributed manufacturing or, most recently, cloud manufacturing. A selective discussion and interpretation of these similar concepts remains in the literature as a research gap. Following the call for research, the aim of this paper is to distinguish the concept of cloud manufacturing from neighboring production paradigms and to locate it within the theory. This goal will be achieved by means of a literature analysis as well as argumentation based on it and finally presented graphically. © 2021 The Authors. Published by Elsevier B.V.

关键词： Industrial research

来源：评论

学校读者我要写书评

暂无评论

Self-adaptive manufacturing with digital twins

arXiv

引用

arXiv 2021年

作者： Bolender, Tim Bürvenich, Gereon Dalibor, Manuela Rumpe, Bernhard Wortmann, Andreas Software Engineering RWTH Aachen University Aachen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

Digital Twins are part of the vision of Industry 4.0 to represent, control, predict, and optimize the behavior of Cyber-Physical Production Systems (CPPSs). These CPPSs are long-living complex systems deployed to and configured for diverse environments. Due to specific deployment, configuration, wear and tear, or other environmental effects, their behavior might diverge from the intended behavior over time. Properly adapting the configuration of CPPSs then relies on the expertise of human operators. Digital Twins (DTs) that reify this expertise and learn from it to address unforeseen challenges can significantly facilitate self-adaptive manufacturing where experience is very specific and, hence, insufficient to employ deep learning techniques. We leverage the explicit modeling of domain expertise through case-based reasoning to improve the capabilities of Digital Twins for adapting to such situations. To this effect, we present a modeling framework for self-adaptive manufacturing that supports modeling domain-specific cases, describing rules for case similarity and case-based reasoning within a modular Digital Twin. Automatically configuring Digital Twins based on explicitly modeled domain expertise can improve manufacturing times, reduce wastage, and, ultimately, contribute to better sustainable manufacturing. © 2021, CC BY.

关键词： Case based reasoning

来源：评论

学校读者我要写书评

暂无评论

A System for Reproducible 3D Ultrasound Measurements of Skeletal Muscles

TechRxiv

引用

TechRxiv 2023年

作者： Sahrmann, Annika S. Handsfield, Geoffrey G. Gizzi, Leonardo Gerlach, Jenin Verl, Alexander Besier, Thor F. Röhrle, Oliver University of Stuttgart Germany The Institute for Modelling and Simulation of Biomechanical Systems University of Stuttgart Stuttgart70569 Germany The Stuttgart Center for Simulation Science SimTech EXC2075 – 390740016 Germany The Auckland Bioengineering Institute Auckland10202 New Zealand The Institute for Control Engineering of Machine Tools Manufacturing Units University of Stuttgart Stuttgart70569 Germany

In 3D freehand ultrasound imaging, operator dependent variations in applied forces and movements can lead to errors in the reconstructed images. In this paper, we introduce an automated 3D ultrasound system, which enables acquisitions with controlled movement trajectories by using motors, which electrically move the probe. Due to integrated encoders there is no need of position sensors. An included force control mechanism ensures a constant contact force to the skin. We conducted 8 trials with the automated 3D ultrasound system on 2 different phantoms with 3 force settings and 10 trials on a human tibialis anterior muscle with 2 force settings. For comparison, we also conducted 8 freehand 3D ultrasound scans from 2 operators (4 force settings) on one phantom and 10 with one operator on the tibialis anterior muscle. Both freehand and automated trials showed small errors in volume and length computations of the reconstructions, however the freehand trials showed larger standard deviations. We also computed the thickness of the phantom and the tibialis anterior muscle. We found significant differences in force settings for the operators and higher coefficients of variation for the freehand trials. Overall, the automated 3D ultrasound system shows a high accuracy in reconstruction. Due to the smaller coefficients of variation, the automated 3D ultrasound system enables more reproducible ultrasound examinations than the freehand scanning. Therefore, the automated 3D ultrasound system is a reliable tool for 3D investigations of skeletal muscle. © 2023, CC BY.

关键词： Phantoms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：