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19th Global Conference on Sustainable manufacturing, GCSM 2023

作者： Lindner, M. Duckstein, R. Mennenga, M. Herrmann, C. Chair of Sustainable Manufacturing and Life Cycle Engineering Institute of Machine Tools and Production Technology Technische Universität Braunschweig Langer Kamp 19B Braunschweig38106 Germany Fraunhofer Institute for Surface Engineering and Thin Films IST Riedenkamp 2 Braunschweig38108 Germany

ISBN: (纸本)9783031774287

For securing a high-quality plating process, one of the main challenges in electroplating is the dosing of electrolytes. The optimal dosing and the related demand for resources do not only influence the coating quality but can also have a high environmental and economic relevance. Currently, the condition monitoring approaches related to dosing are mostly model-based and are seldom real-time capable. Therefore, a concept for real-time data-based condition monitoring of electrolytes is proposed. The paper discusses the challenges of pre-processing and modeling time series data with machine learning algorithms and quality requirements and availability of data within the electroplating process. Moreover, the usage of neural networks for condition monitoring of time series data is presented and discussed in a case study with a focus on anomaly detection. With this example, the applicability of a data-based approach for dynamic prediction of electrolyte chemicals is presented and evaluated. © The Author(s) 2025.

关键词： Electroplating shops

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Resilience-oriented design of technical building services for the manufacturing industry

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Procedia CIRP 2024年 130卷 1158-1163页

作者： Kilian Dickel Max Juraschek Christoph Herrmann Institute of Machine Tools and Production Technology Chair of Sustainable Manufacturing and Life Cycle Engineering Technische Universität Braunschweig Germany

Unexpected disruptions of material and energy supply can pose severe challenges to the manufacturing industry, increasing the need for resilient production technologies and supply chains. However, the technical building services of factories and production sites, relevant for auxiliary materials and the energy supply, are often overlooked when discussing resilient manufacturing systems. These systems are quite complex and influenced by internal and external parameters. However, the technical building services bear a high potential to introduce resilience factors to strengthen the capabilities of a production site. In order to utilize said potential, these systems need to be designed accordingly. The consideration of resilience increases the number of influential factors in system design and evaluation. Technical building services are already commonly designed with the support of digital methods. Computer aided engineering (CAE) has the ability to consider an even wider range of options regarding the system components and their performance in different scenarios. However, for the resilience-oriented evaluation and comparison of different system designs, quantifiable methods are currently still scarce. While there are a few approaches to assess and quantify resilience for manufacturing or energy systems in engineering, these approaches are directly applicable for technical building services. Against this background, a new metric to quantify engineering resilience for the computer-based design of technical building services is proposed based on existing approaches for the quantification of resilience.

关键词： Resilience technical building services energy supply computer aided engineering renewable energy

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Inter-Stream Dependencies in Time-Sensitive Networking 28

Inter-Stream Dependencies in Time-Sensitive Networking

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28th Conference on Innovation in Clouds, Internet and Networks, ICIN 2025

作者： Chahed, Hamza Yarvis, Mark Frick, Florian Kassler, Andreas Intel Deutschland GmbH Germany Intel Corporation United States Department of Mathematics and Computer Science Karlstad University Karlstad Sweden Institute for Control Technology of Machine Tools and Manufacturing Equipment University of Stuttgart Germany Faculty of Applied Computer Science Deggendorf Institute of Technology Deggendorf Germany

ISBN: (纸本)9798331542399

Effective configuration of Time-Sensitive Networks is crucial for providing timeliness and reliability guarantees for real-time industrial applications, where many inter-dependent streams may co-exist. However, existing methods for specifying the characteristics of real-time streams to the Centralized Network Configuration element (CNC) do not allow the specification of stream dependencies. Consequently, the CNC may schedule the real-time streams in a sub-optimal way, leading to low number of real-time applications supported. To address this pressing issue, we present methods that allow to model and express such inter-stream dependencies and propose extensions to the user network interface (UNI) to convey these dependencies to the CNC, transforming it into an intent-based UNI. We define a novel metric to evaluate a specific network configuration regarding the latency budget available for scheduling the transmission of a stream. Using a set of numerical simulations, we show that when exploiting the knowledge of inter-stream dependencies, we can derive better network schedules, which results in significant increase in applications onboarding up to 2.2x and increased network utilization for real-time streams up to 3x. © 2025 IEEE.

关键词： Budget control

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Edge-Cloud Automation of manufacturing machines: Analysis of Potential Designs and their Impact on the machine Performance

Edge-Cloud Automation of Manufacturing Machines: Analysis of...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Marco Giani Timur Tasci Patrick Wiener Alexander Verl Robert Bosch GmbH Renningen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units Stuttgart Germany

The migration of industrial automation systems to an edge-cloud hosted on factory 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. One limiting factor in the realization of edge-cloud automation systems (ECASs) lies in its operation mode over the network. This may result in tangible delays between the industrial process and the edge-cloud. This paper analyzes how the network delay affects the process performance of an industrial machine on the base of the real-time requirements of the control functions hosted in the edge-cloud. For this purpose, two potential scenarios for the migration of the control system of a real machine to the edge-cloud are implemented. Each scenario features the offloading of more real-time critical control functions to the edge-cloud, which is then tested under increasing load on the network. The study derives classes of automation functions according to the real-time requirements of a potential offloading to the edge-cloud. Furthermore, it shows how complementary designs of an ECAS can affect the performance of the automated systems. In this sense, the results reveal that firm real-time functions can be offloaded to the edge-cloud without any significant loss of performance even if non-real-time networking components are used. On the base of these results, potentials applications domains of ECASs are discussed prospectively and future work is proposed.

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

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Procedia CIRP 2024年 130卷 689-694页

作者： Zhibo Zhou Michael Walther Alexander Verl Robert Bosch GmbH Robert Bosch Campus 1 Renningen 71272 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstraße 36 Stuttgart 70174 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.

关键词： Digital twin Lifelong learning Model calibration

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A sensitivity analysis approach to reduce economic risks in the design of edge-cloud automation systems in industry

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Procedia CIRP 2024年 128卷 526-531页

作者： Marco Giani Moritz Walker Michael Neubauer Nelly Frank Patrick Wiener Alexander Verl Robert Bosch GmbH Robert-Bosch-Campus 1 71272 Renningen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 70174 Stuttgart 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.

关键词： edge-computing industrial automation Design methodology tools technologies

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Automated workflow generation supporting the value stream design of reconfigurable robot assembly cells

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Procedia CIRP 2024年 128卷 609-614页

作者： Marc Ungen David Kampert Benedikt Feldotto Elias Huber Oliver Riedel Robert Bosch GmbH Robert-Bosch-Campus 1 71272 Renningen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr.36 70174 Stuttgart Germany

The paper addresses the automated generation of value stream optimized assembly workflows for reconfigurable robot cells. The focus is on the generation of asynchronous concurrent action workflows from assembly task descriptions. The main motivation is to enable automated search for optimized solutions within the enormous design spaces of these systems which results from their structural and procedural configurability. The proposed approach conducts task assignment, task sequencing and logical task planning (AI Planning) for multiple agents. The approach combines existing methods from the distinct research fields of robot task sequencing and discrete task planning. The contribution of the research is twofold. Firstly, the paper proposes a generic domain meta model enabling automated workflow generation for multi-agent assembly tasks. Secondly, a workflow generation approach based on artificial intelligence planning combined with the game-theoretic concept of extensive form games is presented. The approach iteratively generates a cooperative strategy for acting agents which is subsequently optimized in terms of individual strategies. The obtained logical action plans are further transformed into parametric concurrent action schedules to support downstream design activities. Both the meta model and the workflow generation approach are applied in a case study and provide valuable information on achievable assembly speedup.

关键词： Model-based systems engineering Artificial intelligence Design methodology tools technologies

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Quantitative Evaluation of Automated Behavior Model Creation for Applications of Industrial Automation 57

Quantitative Evaluation of Automated Behavior Model Creation...

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18th IFAC Workshop on Time Delay Systems, TDS 2024

作者： Stegmaier, Valentin Eberhardt, Tobias Jazdi, Nasser Weyrich, Michael University of Stuttgart Nobelstraße 12 Stuttgart70569 Germany Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 Stuttgart70569 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstraße 36 Stuttgart70174 Germany J. Schmalz GmbH Johannes-Schmalz-Straße 1 Glatten72293 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. © 2024 The Authors.

关键词： Office automation

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Automated Configuration of Optimized Customer Specific Mechatronic Systems Using Behavior Models 17

Automated Configuration of Optimized Customer Specific Mecha...

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17th CIRP Conference on Intelligent Computation in manufacturing engineering, CIRP ICME 2023

作者： Stegmaier, Valentin Eberhardt, Tobias Schaaf, Walter Jazdi, Nasser Weyrich, Michael Verl, Alexander University of Stuttgart Nobelstraße 12 Stuttgart70569 Germany Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 Stuttgart70569 Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstraße 36 Stuttgart70174 Germany J. Schmalz GmbH Johannes-Schmalz-Straße 1 Glatten72293 Germany

The diversity of component manufacturers' product portfolios is often one of their greatest assets, as it allows them to offer appropriate solutions to a wide variety of customers. However, this diversity is also one of the greatest challenges, as it often makes it nearly impossible to design an optimal mechatronic system by manually selecting components. This is where the Digital Twin of the components can help. By providing behavior models and relevant information, existing optimization algorithms can be used to optimize for system-relevant key performance indicators enabling an automated system design process. The method presented in this paper is validated for a vacuum gripping systems. © 2024 Elsevier B.V.. All rights reserved.

关键词： Smart manufacturing

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Additive manufacturing of Ceramics opens the door to Components for Biomanufacturing Applications with high Functionality 6

Additive Manufacturing of Ceramics opens the door to Compone...

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6th CIRP Conference on Biomanufacturing, BioM 2024

作者： Scheithauer, Uwe Holtzhausen, Stefan Wiemer, Hajo Fraunhofer Institute for Ceramic Technologies and Systems Group Additive and Hybrid Manufacturing Winterbergstr. 28 Dresden01277 Germany TUD Dresden University of Technology Institute of Machine Elements and Machine Design Virtual Product Development Group Advanced Geometric Modeling And Analysis Dresden01062 Germany TUD Dresden University of Technology Institute of Mechatronic Engineering Machine Tools Development and Adaptive Controls Department of Machine Data Processing Dresden01062 Germany

Significant advancements in production technology, materials, component design, and data science foster innovation across industries, including biomanufacturing. Ceramic materials, adapted additive manufacturing processes, and novel construction methods hold immense innovation potential due to ceramics' exceptional thermal, chemical, and mechanical properties. Additive manufacturing enables the creation of intricate ceramic components with unprecedented functionality. Hybridizing manufacturing technologies and materials facilitates direct integration of additional features like sensors and actuators. Despite their potential, ceramic materials remain underutilized. This article aims to spark a discourse on leveraging high-performance ceramic components in biomanufacturing, leveraging superior material properties, innovative design methods, additive manufacturing, process data analysis, and AI. © 2024 The Authors.

关键词： Ceramic materials

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