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A simulation model extension to enable continuous control tests during the Virtual Commissioning

Procedia CIRP 2022年 112卷 97-102页

作者： Erik-Felix Tinsel Prof. Dr.-Ing Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Seidenstr. 36 70174 Stuttgart Germany

Model-, Software-, and Hardware-in-the-Loop simulations are used in the Virtual Commissioning of machines and plants to reduce costly control errors early in the engineering process. Each simulation type represents a different grade of detail. As a result, the underlying models change on every transition between the three types. Regarding the model structure there is no solution to enable a continuous and effortless transition. This work proposes a model extension concept which allows cycling all X-in-the-Loop configurations during Virtual Commissioning. The extension includes abundant submodules describing every component transformation required to switch to a specific simulation configuration.

关键词： X-in-the-Loop Simulation model Virtual Commissioning

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Ambiguity Tolerant Commissioning Ontology: From an upper ontology to a domain specific implementation

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Procedia CIRP 2022年 112卷 91-96页

作者： Carsten Ellwein Marc Hekeler Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany

There are no standardized interfaces or descriptions for the outsourcing of production orders, e.g. through cloud manufacturing. For this reason, an upper ontology was developed in a preliminary work; associated models describe the entire process and parameters from the request for quotation over its return to the conclusion of the contract. Products can either be described by their final state or by the initial product in conjunction with the applied processes. In this paper, the process from this upper ontology to a concrete implementation is further elaborated and a middleware is introduced which offers a machine-readable interface to edit the ontology as well as various validation options are addressed.

关键词： Industry 4.0 Cloud manufacturing Data model Ontology

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On data, information, and knowledge in the context of online simulation in industrial automation

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Procedia CIRP 2024年 130卷 1188-1193页

作者： Darius Deubert Andreas Selig Alexander Verl Bosch Rexroth AG Bgm.-Dr.-Nebel-Straße 2 97816 Lohr am Main Germany Institute for Control Engineering of Machine Tools and Manufacturing Units - University of Stuttgart 70049 Stuttgart Germany

In the course of digitalization and Industry 4.0, data-based optimization strategies and AI technologies are increasingly applied in industrial automation. To achieve benefits from this, it is necessary to contextualize and interpret the widely available data and process them to value adding information and knowledge. This paper deals with the processing of data, information, and knowledge in the context of online simulation in industrial automation. It forms a basis by defining the terms within an industrial perspective and examining the data landscape regarding properties that get important in cyber-physical systems including online simulation. Subsequently the generation of resulting information and knowledge with online simulation is discussed. Within this work, by changing the point of view from a technical perspective to an abstraction it is shown that known principles from intelligent systems and knowledge engineering also hold for manufacturing systems that are supported by an online simulation system. Additionally, this contemplation points out that online simulation systems exceed the level of information by gaining and processing knowledge, which enables to infer new information. By this, the influence of online simulation in industrial automation on data, information, and knowledge handling is expounded comprehensively.

关键词： simulation digital twins manufacturing robotics automation semantics

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Offline and Online Energy Simulation using Virtual Commissioning Models with Extended Dynamical Behavior

Offline and Online Energy Simulation using Virtual Commissio...

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IEEE/SICE International Symposium on System Integration

作者： Darius Deubert Denis Pfeifer Christian Scheifele Jörg Fehr Alexander Verl Bosch Rexroth AG 97816 Lohr am Main Germany and Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany Denis Pfeifer is with ISG Industrielle Steuerungstechnik GmbH 70563 Stuttgart and Institute of Engineering and Computational Mechanics University of Stuttgart Stuttgart Germany ISG Industrielle Steuerungstechnik GmbH Stuttgart Institute of Engineering and Computational Mechanics University of Stuttgart Stuttgart Germany Alexander Verl is with Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Considering energy consumption and dynamical behavior within the simulation of manufacturing systems emerges as an important objective for their development, commissioning, and operation. Currently, these aspects are often neglected in many fields including virtual commissioning. This work presents an approach to extend highly detailed virtual commissioning models of components from industrial automation by dynamics models for the calculation of energy consumption in an offline simulation and for reuse in an online simulation. To validate the presented approach, an exemplary offline virtual commissioning simulation of a pick-and-place robot application is implemented and subsequently transferred to an online simulation. The validation shows a good accuracy of the simulated energy consumption, enabling virtual commissioning engineers to analyze and optimize energy consumption already in the design phase of manufacturing systems. Additionally, the dynamical behavior was well reflected in the online simulation, contributing to the capability of simulation in the operation phase.

关键词： Energy consumption Automation Accuracy Service robots System integration manufacturing systems

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Model-based automatic generation of digital twin models for the simulation of reconfigurable manufacturing systems for timber construction

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Procedia CIRP 2022年 107卷 387-392页

作者： Benjamin Kaiser Alexander Reichle Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany

Reconfigurable manufacturing systems adapt to changing requirements and therefore offer a solution to the challenges associated with increasing product variety and shorter product life cycles. This is especially helpful in the prefabrication in timber construction, as components and requirements vary widely between projects. However, reconfigurations must be quick to keep downtimes short. The planning of reconfigurations is a complex problem where digital twins and simulation models of the manufacturing systems are necessary for simulation and validation. In our timber prefabrication use case, building components and requirements change from project to project, and the manufacturing system needs to reconfigure frequently. The building components and the configuration of the manufacturing system are designed simultaneously during a co-design process to ensure the integrity of the manufacturing process in a changing manufacturing environment. Hence, this may require many iterations of the planning process. Each iteration needs validation through a simulation. However, the manual generation of simulation models is time-consuming and error-prone and thus poses an obstacle for the digital planning phase. This paper addresses this issue and presents a model-based approach to generate simulation models for reconfigurable manufacturing systems. Our system and its components are modeled in automation markup language as this domain-specific language allows us to model not only kinematics and geometry but also behavior, skills, and interfaces to check the compatibility of components. We apply the method to our use case with the IntCDC wood prefabrication system. The proposed method builds a component graph for a configuration of the manufacturing system and generates the required packages for the simulation in Gazebo and ROS. To build simulation models automatically, we apply model-to-model and model-to-text transformation techniques. The proposed method is suitable for integr

关键词： AutomationML ROS URDF Software Defined manufacturing Reconfigurable manufacturing System Simulation Timber Prefabrication IntCDC

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Test-Driven Reward Function for Reinforcement Learning: A Contribution towards Applicable machine Learning Algorithms for Production Systems

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Procedia CIRP 2022年 112卷 103-108页

作者： Florian Jaensch Karl Kübler Elmar Schwarz Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidentraße 36 D-70174 Stuttgart Germany

Reinforcement Learning algorithms find more and more application in fields where complex tasks need to be solved. The automation of production systems is one of those fields. Normally, programming a control system defines the automation strategy. Previous contributions by the authors have shown that a so-called agent can learn automation strategies for production systems using a Reinforcement Learning setup. However, the development of the reward function for the agent can be challenging and needs Reinforcement Learning domain knowledge. This paper introduces a novel approach in combining Test-Driven Development with Reinforcement Learning in order to solve the problem of a suitable reward function. In the presented approach predefined test cases are used to derive rewards for the agent. The use of an automated test framework allows for continuous learning sequences until all test cases are passed. An application example of a robot cell is used to demonstrate the novel approach and verify its suitability and usability. The first application shows promising results for further examination towards more application scenarios.

关键词： Virtual Commissioning Simulation Test-Driven Development Reinforcement Learning

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Adaptive CAM planning to support co-design in the building industry

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Procedia CIRP 2022年 109卷 78-83页

作者： Alexander Reichle Carsten Ellwein Alexander Verl Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 D-70174 Stuttgart Germany

Co-design describes a collaborative design process between different stakeholders. These stakeholders usually come from various domains. To enable co-design, data has to be exchanged between the stakeholders. Current approaches to data management in the building industry are usually oriented along the process chain and therefore only allow a unidirectional flow of information. This is an obstacle in the implementation of co-design within the building industry. As more and more buildings are built by utilizing prefabricated modules to accelerate the on-site building process and to reduce the cost, a major effort in terms of implementing co-design is to link the design information of the building industry with the production information of the manufacturing industry. The problem occurs as the building industry mainly uses the fndustry Foundation Classes and the manufacturing industry uses the Standard for the Exchange of Product Model Data as a data format to exchange information. This leads to a break in the flow of information. Furthermore, information about the manufacturability of products, that is generated during the computer-aided manufacturing process, cannot be easily returned to the architect who can utilize the information to adapt the design in the computer-aided design process. This paper addresses these problems by defining a data processing pipeline that enables the conversion of the geometric design information stored in IFC into the STEP data format. From there, the CAM strategy can be defined and results in an executable G-Code. The information of the CAM planning is returned to the architect, who can adapt the design by interpreting the results of the CAM processing. To close the co-design loop, the G-Code for the design adaptions can be generated automatically by reusing the predefined CAM strategy.

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

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Toward Automating the Composition of Digital Twins Within System-of-Systems

Toward Automating the Composition of Digital Twins Within Sy...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Milapji Singh Gill Jingxi Zhang Andreas Wortmann Alexander Fay Institute of Automation Technology Helmut Schmidt University Hamburg Germany Institute of Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Germany Chair of Automation Ruhr University Bochum Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Cyber-Physical Production Systems necessitate efficient configuration and continuous reconfiguration to adapt to evolving requirements and shifting goals. This process involves integrating various system structures to derive new functions and behaviors. The concept of the Digital Twin, which allows for effective integration and testing, is instrumental in facilitating this task. However, a fundamental prerequisite is that Digital Twins of individual system components must be composed efficiently and in accordance with dynamic System-of-Systems. We address this challenge by introducing an approach for the automated horizontal and vertical composition of Digital Twins, aimed at minimizing manual intervention and enhancing adaptability. Therefore, a pipeline specifically designed for this goal is proposed, which includes the generation of new functions and behaviors. This approach is intended to provide a foundation for future research.

关键词： Production systems Instruments Pipelines Digital twins manufacturing automation Testing

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Direct Trajectory Generation on Parametric Compound Surfaces in a Numerical control to Improve Surface Homogeneity for Material Extrusion

SSRN

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SSRN 2023年

作者： Elser, Anja Lechler, Armin Verl, Alexander Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Seidenstr. 36 Stuttgart Baden-Württemberg70174 Germany

HighlightsSurface quality in the sense of homogeneity and exactness of Material Extrusion processes depends on material extrusion control as well as trajectory generation. In this paper, the authors improve the trajectory generation process, that can then be combined with existing material extrusion control to maximize surface quality while at the same time ensuring high process velocity. In the currently established Slicer-CNC interface, the tool path description is transferred by the use of discrete points. There are four main deficits that result from this discretization: (i) The path error is unknown in the CNC. (ii) The computed tool path tends to oscillate. (iii) Parallel paths are processed differently in the CNC. (iv) Transitions between two surface patches of a compound surface are blurred. To overcome these drawbacks, in this paper, the surface description of curved compound surfaces is transferred to the CNC. A CNC architecture dealing with this description is presented, including the information flow, the definition of manufacturing paths, and different smoothing methods. Smoothing methods on a single surface as well as across surface boundaries are defined. In particular, a corner smoothing method is developed, that results in $G^2$-continuous transitions for arbitrary boundary conditions, such as non-zero curvatures. The smoothing methods are validated experimentally and discussed. The produced parts show remarkable increase in surface quality. © 2023, The Authors. All rights reserved.

关键词： Surface properties

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Introduction of an industrial transfer learning use case systematization for machine tools

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Procedia CIRP 2023年 120卷 398-403页

作者： Dr.-Ing. Markus Netzer Jonas Michelberger Alexander Puchta Prof. Dr.-Ing. Alexander Verl Prof. Dr.-Ing. Jürgen Fleischer wbk Institute of Production Science Karlsruhe Institute of Technology Kaiserstraße 12 76131 Karlsruhe Germany ISW Institute for Control Engineering of Machine Tools and Manufacturing Units Keplerstraße 7 70174 Stuttgart Germany

Traditional intelligent systems such as fault detection are mainly developed for isolated use on single machines and are mostly trained individually. A cross-machine knowledge transfer of intelligent systems holds an immense potential and can reduce implementation effort of intelligent systems. To enable a structured analysis of real-world transfer problems, an industry-relevant, far-reaching systematization of typical machine tool use cases is developed. This provides the overview over different typical use case classes from the industrial use case perspective. Based on the derived transfer criteria of each use case class, a conceptual approach of concrete transfer methods is proposed.

关键词： Transfer learning industrial transfer learning knowledge transfer transfer learning systemization machine tools

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