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Proceedings of the 12th International Conference on the Internet of Things

作者： Marco Giani Nelly Frank Alexander Verl Robert Bosch GmbH: Corporate Sector Research and Advance Engineering Germany University of Stuttgart: Institute for Control Engineering of Machine Tools and Manufacturing Units Germany

ISBN: (纸本)9781450396653

The migration of industrial controls to an edge-cloud hosted on factory premises can reduce operation costs and increase the interoperability and flexibility of industrial machines. However, the adoption of Industrial Internet of Things (IIoT) technologies to realize an industrial edge-cloud for factory automation is likely to lead to a number of challenges that have not yet been investigated. Based on an expert interviews study, this paper provides two main contributions: (1) the identification of 11 technology-, engineering-, organization-, and strategy-related challenges that, according to industrial experts, will hinder the adoption of edge-cloud control (ECC) in future factories, (2) the derivation of a structural model showing how challenges are interlinked. The results illustrate the dependency between profitability and both engineering and operation of an ECC system, suggesting the importance of improving the usability of ECC for automation experts with limited IT know-how, for instance through the reorganization of departments and the standardization of integration concepts for ECC in factories.

关键词： Industrial Automation Cloud Computing IIoT Edge Computing

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A Virtual Assistant System for the Requirements Elicitation and Initial Simulation Model Variant Generation of Modular Industrial Plants

A Virtual Assistant System for the Requirements Elicitation ...

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International Conference on Mechatronics and machine Vision in Practice (M2VIP)

作者： Erik-Felix Tinsel Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (纸本)9798350334340

Errors during the commissioning of machines and plants are costly and time-consuming. Costs increase the later an error is discovered in the development process. The earliest occurring errors can already result from insufficient coordination with the customer. This paper presents the ongoing research on a virtual assistance system designed to bridge the gap between the early requirements phase and the virtual commissioning of modular plants by creating interfaces for customers allowing them to outline their project, validate it by themselves and be actively integrated in the process of the virtual plant creation.

关键词： Mechatronics Costs Virtual assistants machine vision Industrial plants

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Study on Available Cloud Manufacturing Platforms for Additive Manufacturing Technologies

Study on Available Cloud Manufacturing Platforms for Additiv...

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IEEE Eurasia Conference on IOT, Communication and engineering (ECICE)

作者： Matthias Milan Strljic Islam Younes Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781665482097

Additive manufacturing technologies provided one of the most adaptable manufacturing processes for digital commissioning via the growing cloud manufacturing paradigm. This was facilitated by a low-complexity tool chain for the manufacturing process along the CAD-CAM chain and the process to be executed on the equipment. However, additive processes have grown far beyond the initial FDM processes and also offer more complex materials with unique properties in addition to other processes. The four most common manufacturing processes FDM, SLA, SLS, and SLM were used as a basis, and existing cloud manufacturing platforms offering all these four technologies as a bundle were gathered via a structured survey. Out of 42 platforms, 17 platforms were researched, filtered and analyzed using sample components and a catalog of requirements consisting of five requirement clusters: material, functional scope, final costs, delivery and user-friendliness. The results were weighted for each technology and finally evaluated in an overarching discussion. The achieved scores and the special features of a platform are discussed and a recommendation is made.

关键词： Manufacturing processes Costs Additives Production Three-dimensional printing Manufacturing Frequency division multiplexing

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Study on Available Cloud Manufacturing Platforms for CNC Milling Processes

Study on Available Cloud Manufacturing Platforms for CNC Mil...

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IEEE Eurasia Conference on IOT, Communication and engineering (ECICE)

作者： Matthias Milan Strljic Aleksandar Bakovic Oliver Riedel Institute for Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781665482097

CNC milling processes represent the main group of production processes for components with a non-trivial surface geometry that are either brittle or have a material with a high melting point or have sensitive requirements for the manufacturing tolerances. Thus, a study was conducted on the adoption of CNC milling processes in the cloud manufacturing segment, highlighting the range of functions provided as well as the unit prices. In the process, multiple application scenarios were addressed via part enquiries to be manufactured, which have different technical requirements for the CNC milling machine cell to be manufactured. Thus, components were designed that require at least three, four, or five synchronous axes for production. In addition, components with geometric properties were added that can be realized either on a 4-axis system or on a 3-axis system with a reclaiming process. For the evaluation, 50 platform providers were researched via a structured search, which were filtered through an automated ordering process, accessibility, and available materials to a final eleven platforms to be evaluated. On these platforms, a total of 55 application scenarios were then compared in terms of their performance with the application of 22 evaluation criteria. After a weighted evaluation of the results, recommendations were made for component requests from identified groups in terms of geometry complexity, material, and number of pieces that resulted from the analysis.

关键词： Geometry Technical requirements Cloud computing Production Milling Software Manufacturing

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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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Efficient data acquisition for traceability and analytics

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Procedia CIRP 2024年 122卷 73-78页

作者： Heiner Reinhardt Mahtab Mahdaviasl Bastian Prell Anton Mauersberger Philipp Klimant Jörg Reiff-Stephan Steffen Ihlenfeldt Fraunhofer Institute for Machine Tools and Forming Technology IWU Reichenhainer Straße 88 09126 Chemnitz Germany Technical University of Applied Sciences Wildau Hochschulring 1 15745 Wildau Germany Professorship Virtual Technologies Hochschule Mittweida - University of Applied Sciences Technikumplatz 17 09648 Mittweida Germany Institute of Machine Tools and Control Engineering Technische Universität Dresden 01062 Dresden Germany

Implementing processes for traceability is required in various industries to assure product quality during manufacturing, provide evidence on required processing conditions or facilitate product recalls. Commonly, radio-frequency identification (RFID) or code recognition techniques (e.g. Data Matrix) are applied to track the flow of workpieces through a manufacturing system and link processing data accordingly. Although the analysis of tracking data is well-examined, we still see a gap in the research on the trade-off between data acquisition, data analytics and data quality. Here, we present a framework to increase the value of existing data by enabling data analytics while addressing common pitfalls and reducing the costs of data management.

关键词： Identification Knowledge management Manufacturing system Process control Quality assurance Sustainable development Decision making Complexity Analysis Design

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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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A production scheduling and control system for CAR T cell manufacturing

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Procedia CIRP 2024年 125卷 36-41页

作者： Tamás Kis Simon Hort Péter Györgyi Evelin Szögi Robert H. Schmitt HUN-REN Institute for Computer Science and Control Kende str 13-17 Budapest 1111 Hungary Fraunhofer Institute for Production Technology IPT Aachen Germany Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University Aachen Germany

This paper addresses some of the new challenges posed by scheduling and controlling the production of chimeric antigen receptor (CAR) T cells for personalized therapies. In this therapy, the patient’s T cells are genetically modified by adding a gene for a receptor to help T cells attach to the cancer cell antigens. Then, the modified cells are grown and multiplied (called cell expansion) and finally returned to the patient. The production takes place in a manufacturing system that comprises several devices, which are capable of processing cells from multiple patients at the same time. The efficient operation of such a complex system requires a sophisticated control system accompanied by a scheduler to optimize the production of CAR T cells for several patients simultaneously. We propose a scheduling algorithm, which can handle the uncertain duration of cell expansion, and the maximum time lags between consecutive processes simultaneously, a combination hardly studied in the literature. We also describe the main features of an adaptive control system including service-oriented device connections as well as centralized control and monitoring. Finally, we describe how the overall system works, including a JSON based communication between scheduler and control system.

关键词： Scheduling Production control CAR T cell manufacturing

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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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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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