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Implementation of an Intelligent System Architecture for Process Monitoring of machine tools

Procedia CIRP 2021年 96卷 342-346页

作者： B. Schmucker F. Trautwein T. Semm A. Lechler M.F. Zaeh A. Verl Institute for Machine Tools and Industrial Management (iwb Technical University of Munich) Boltzmannstr. 15 85748 Garching b. München Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW University of Stuttgart) Seidenstr. 36 70174 Stuttgart 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.

关键词： machine tools Modal Analysis Industry 4.0 Structural Dynamics

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Maturity Evaluation of Domain-Specific Language Ecosystems for Cyber-Physical Production Systems

Maturity Evaluation of Domain-Specific Language Ecosystems f...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Sandra Greiner Bianca Wiesmayr Kevin Feichtinger Kristof Meixner Marco Konersmann Jérôme Pfeiffer Michael Oberlehner David Schmalzing Andreas Wortmann Bernhard Rumpe Rick Rabiser Alois Zoitl Software Engineering Group University of Bern Switzerland LIT CPS Lab Johannes Kepler University Linz Austria CDL SQI Institute of Information Systems Engineering Technische Universität Wien Austria Software Engineering RWTH Aachen University Germany Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) University of Stuttgart Germany CDL VaSiCS LIT CPS Lab Johannes Kepler University Linz Austria

engineering Cyber-Physical Production Systems (CPPSs) heavily relies on Domain-Specific Languages (DSLs), which are tailored to a specific class of problems inherent to CPPSs. DSLs enable non-programming experts to solve problems in their domain, such as modeling production processes, implementing control software, or managing the variability of production systems. A DSL ecosystem encompasses the entire infrastructure (e.g., libraries and tools) built around its language and contributes to the successful and easy adoption thereof by domain experts. We present a maturity evaluation model for DSL ecosystems serving two aims: to developers, it reveals missing but essential aspects of the ecosystem, and users (e.g., industrial companies) can evaluate the maturity of a DSL ecosystem. We propose criteria to evaluate the maturity of DSL ecosystems and apply them to existing, publicly available DSLs which have been adopted in CPPSs. The results demonstrate that all components of the model are covered and they allow for deriving hypotheses about DSL ecosystems used in CPPSs.

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Foreword

Springer Proceedings in Advanced Robotics

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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

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A Novel Approach for Unsupervised Sensor Error Classification

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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

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Towards a systematic engineering of industrial domain-specific languages

arXiv

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arXiv 2021年

作者： Gupta, Rohit Kranz, Sieglinde Regnat, Nikolaus Rumpe, Bernhard Wortmann, Andreas Siemens AG Munich Germany Software Engineering RWTH Aachen University Aachen Germany Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

Domain-Specific Languages (DSLs) help practitioners in contributing solutions to challenges of specific domains. The efficient development of user-friendly DSLs suitable for industrial practitioners with little expertise in modelling still is challenging. For such practitioners, who often do not model on a daily basis, there is a need to foster reduction of repetitive modelling tasks and providing simplified visual representations of DSL parts. For industrial language engineers, there is no methodical support for providing such guidelines or documentation as part of reusable language modules. Previous research either addresses the reuse of languages or guidelines for modelling. For the efficient industrial deployment of DSLs, their combination is essential: the efficient engineering of DSLs from reusable modules that feature integrated documentation and guidelines for industrial practitioners. To solve these challenges, we propose a systematic approach for the industrial engineering of DSLs based on the concept of reusable DSL Building Blocks, which rests on several years of experience in the industrial engineering of DSLs and their deployment to various organizations. We investigated our approach via focus group methods consisting of five participants from industry and research qualitatively. Ultimately, DSL Building Blocks support industrial language engineers in developing better usable DSLs and industrial practitioners in more efficiently achieving their modelling. Copyright © 2021, The Authors. All rights reserved.

关键词： Problem oriented languages

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Fast Verification of Petri Net-Based Model of Industrial Decision-Making Systems: A Case Study

Fast Verification of Petri Net-Based Model of Industrial Dec...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Remigiusz Wiśniewski Justyna Patalas-Maliszewska Marcin Wojnakowski Marcin Topczak Mengchu Zhou Institute of Control and Computation Engineering Univ. of Zielona Góra Zielona Góra Poland Inst. of Mechanical Eng. Univ. of Zielona Góra Zielona Góra Poland Institute for Machine Tools and Production Processes Chemnitz University of Technology Germany Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland The Doctoral School of Exact and Techn. Sciences University of Zielona Góra Zielona Góra Poland ECE Department New Jersey Institute of Technology Newark NJ USA

This work deals with the verification of a decision-making system for additive manufacturing (AM) technology adoption specified by a Petri net. An innovative verification technique of a Petri net-based system is oriented toward practical applications, and can detect errors at the early design and modelling stage. The idea is illustrated by a real-life case study of supporting decision making in AM technology adoption affecting supply chain management (SCM). Two main issues are addressed. Firstly, making optimal decisions about AM technology requires models rarely possessed within a company. Therefore, this work proposes a model supporting the decision making related to the implementation of AM technology, based on a Petri net, by utilizing its main advantages: graphical modelling, and strong mathematical support of formal verification techniques. Contrary to the most popular analysis methods (which are bounded exponentially in a general case), it is proved that the presented method is bounded by a cubic polynomial with net size. Secondly, an investment in AM technology is often financially assessed and does not affect other processes, as in our SCM case. Hence, strong connectivity within the proposed Petri net-based model is examined.

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Implementation of an Intelligent System Architecture for Process Monitoring of machine tools 8

Implementation of an Intelligent System Architecture for Pro...

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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

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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