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18th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2018

作者： Uhlmann, E. Hein, C. Polte, M. Polte, J. Dähne, L. Fraunhofer Institute for Production Systems and Design Technology IPK Germany Institute for Machine Tools and Factory Management IWF Technische Universität Berlin Germany Surflay Nanotec GmbH Germany

ISBN: (纸本)9780995775121

The technical implementation of a novel biosensor for the highly parallelized screening of biochemical binding reactions depends on the manufacturing of an array of micro-bowls with a diameter dB ≤ 10 μm with an aspect ratio ar ≥ 1. Since the operating principle of the biosensor is based on the stimulation of stationary optical waves in micro-spheres, micro-bowls for the immobilisation of these spheres in a microfluidic environment are necessary. Due to this operating principle, the micro-bowls need to separate the spheres from the fluid flow and ensure the careful adherence of single spheres, coincidently. Moreover, the pathway for the optical accessibility of the micro spheres should be unrestricted. This work presents a process chain for the manufacturing of microfluidic chips with an array of n ≥ 1,000 micro-spheres by ultra-precision milling of mold inserts, the replication by precision injection molding as well as experimental trial results. With regard to manufacturing of the mold inserts, the uniform and burr free ultraprecision milling of large aspect ratio micro posts was investigated within a parametric study. Furthermore, the replication of the micro-bowls was examined by taking the consistent replication of the entire bowl array, the adverse formation of fillets, and the replication of surfaces with optical functions into special account. By the analysis of the microfluidic and optical properties of the replicated structures, the correlation between mold manufacturing, replication, and operating conditions can be performed. © 2018 CURRAN-CONFERENCE. All rights reserved.

关键词： Biosensor Injection molding Micro-bowl Ultraprecision milling

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Model based, modular configuration of cyber physical systems for the information management on shop-floor

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Confederated International International Workshop on Enterprise Integration, Interoperability and Networking, EI2N 2017, Fact Based Modeling, FBM 2017, Industry Case Studies Program, ICSP 2017, International Workshop on Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society, Meta4eS 2017, OnTheMove Academy, OTMA 2017 and ODBASE posters 2017, held as part of OTM 2017

作者： Jaekel, Frank-Walter Torka, Jan Eppelein, Martin Schliephack, Wolf Knothe, Thomas Fraunhofer Institute for Production Systems and Design Technology Pascalstr. 8-9 Berlin10587 Germany

ISBN: (纸本)9783319738048

Many of the current manufacturing systems are still implemented as sequential inflexible production lines. This creates difficulties to fulfil the customer request for customized products. The production of customized products is accompanied by major changes in the production infrastructure. To support more flexible production, the sequential production lines nowadays start to change to workshop production. In that case all production systems will be grouped by their tasks, e.g. all drilling machines are located in the same place. A manufacturing system stands for the different involved hardware and software components at the manufacturing process. Each manufacturing system is connected with the help of the shop-floor IT. The term shop-floor indicates the productive area of a factory and includes the operative work. Shop-floor IT includes the information processes and IT solutions that control, secure and record product activities. Therefore the shop-floor IT supports directly the execution on field level. The model based view of a production process simplifies the understanding of the product lifecycle and planning. To optimize and speed up building and changing of product processes, the modular shop-floor IT has been developed by technologies derived from cyber physical systems and internet of things. However, interoperability issues such as different implementation of controls and process variations are a major challenge. © IFIP International Federation for Information Processing 2018 Published by Springer International Publishing AG 2018. All Rights Reserved.

关键词： Interoperability

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Combining the Advantages of On- and Offline Industrial Robot Programming

Combining the Advantages of On- and Offline Industrial Robot...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jan Guhl Sylvio Nikoleizig Oliver Heimann Johannes Hügle Jörg Krüger Industrial Automation Technology Group Technische Universität Berlin Germany Fraunhofer Institute for Production Systems and Design Technology Berlin Germany

Classic off- and online programming approaches offer different advantages but cannot provide intuitive programming as it would be needed for frequent reconfiguration of industrial robotic cells and their programs. While a simulation and therewith a collision control can be used offline, highest precision can be achieved by using online teach-in. We propose a system that combines the advantages of both offline and online programming. By creating a programming framework that is independent of in- and output devices we allow the use of augmented as well as virtual reality. Thus, enabling the user to choose for a programming technique that best suits his needs during different stages of programming. Bringing together both methods allows us to not only drastically reduce programming time but simultaneously increase intuitiveness of human robot interaction.

关键词： Collision avoidance Robot programming Service robots Robot sensing systems Augmented reality

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Assistance Method for the Application-Driven design of Machine Learning Algorithms

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IOP Conference Series: Materials Science and Engineering 2021年第1期1140卷

作者： Adalbert Fono Gregor Thiele Max Klein Jörg Krüger Fraunhofer Institute for Production Systems and Design Technology 10587 Berlin Germany Head of the Department for Industrial Automation at the Institute for Machine Tools and Factory Management Technical University of Berlin 10587 Berlin Germany

Machine learning (ML) offers a lot of potential for applications in Industry 4.0. By applying ML many processes can be improved. Possible benefits in production are a higher accuracy, an early detection of failures, a better resource efficiency or improvements in quantity control. The use of ML in industrial production systems is currently not widespread. There are several reasons for this, among others the different expertise of data scientists and automation engineers. There are no specific tools to apply ML to industrial facilities neither guidelines for setting up, tuning and validating ML implementations. In this paper we present a taxonomy structure and according method which assist the design of ML architectures and the tuning of involved parameters. As this is a very huge and complex field, we concentrate on a ML algorithm for time series forecast, as this can be used in many industrial applications. There are multiple possibilities to approach this problem ranging from basic feed-forward neural networks to recurrent networks and (temporal) convolutional networks. These different approaches will be discussed and basic guidelines regarding the model selection will be presented. The introduced assistance method will be validated on a industrial dataset.

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Notch impact toughness of laser beam welded thick sheets of cryogenic nickel alloyed steel X8Ni9

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Procedia CIRP 2020年 94卷 627-631页

作者： S. Gook S. Krieger A. Gumenyuk A.M. El-Batahgy M. Rethmeier Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstraße 8-9 10587 Berlin Germany Federal Institute for Materials Research and Testing BAM Unter den Eichen 87 12205 Berlin Germany Central Metallurgical R & D Institute CMRDI P. O. Box: 87 Helwan El-Tabbin Cairo Egypt Institut für Werkzeugmaschinen und Fabrikbetrieb IWF Technische Universität Berlin Straße des 17. Juni 135 10623 Berlin Germany

The paper deals with the investigations of the impact toughness of laser beam welded 14.5 mm thick sheets made of cryogenic steel X8Ni9 as a function of preheating. This 9% nickel alloyed steel is widely used in the liquefied natural gas (LNG) industry. An application of highly efficient welding processes such as high-power laser beam welding (LBW) in LNG sector requires an understanding of the interactions between the LBW process parameters and weld properties, in particular the impact toughness. The results show that the original fine-grained martensitic microstructure of the base metal (BM) is significantly changed by melting and crystallization during the LBW, what can lead to a decrease in the impact toughness of the weld metal (WM) below the required level. An optimal preheating temperature range leads to the favorable thermal welding cycle and is of remarkable importance for maintaining the notch impact toughness of laser beam welded joints of these thick steel sheets. A parameter window was identified in which V-notch impact toughness comparable to that of the BM at -196 °C was achieved.

关键词： cryogenic steel laser beam welding preheating welding thermal cycle microstructure hardness V-notch impact toughness

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design alternatives for internationally distributed learning factories in global production engineering

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Procedia Manufacturing 2020年 45卷 392-397页

作者： Bastian C. Schumacher Anja Steinbach Nguyen H. Vi Ahmet Yükseltürk Holger Kohl Jörg Krüger Huy Nguyen Quoc Technische Universität Berlin Chair of Sustainable Corporate Development Straße des 17. Juni 135 10623 Berlin Germany Technische Universität Berlin Chair of Industrial Automation Technology Straße des 17. Juni 135 10623 Berlin Germany Vietnamese-German University Le lai Binh Duong New city Vietnam Turkish-German University Sahinkaya Cd. No: 108 34820 Istanbul Turkey Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstraße 8-9 10587 Berlin Germany

An internationally distributed learning factory (IDLF) provides opportunities to make students aware of intercultural challenges in global production networks. An IDLF is a scalable network of learning factories with value creation processes in spatially distributed locations. It enables collaboration and competition between student groups in distant locations and considers manual and automatic process methods. Due to the high number of design alternatives for IDLFs, a systematic approach for describing attractive characteristics is required. This paper shows design alternatives for IDLFs structural and process organization on the example of learning factories in Germany, Turkey and Vietnam.

关键词： learning factory design alternatives intercultural international

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A method to design Smart Services based on information categorization of industrial use cases

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Procedia CIRP 2019年 83卷 77-82页

作者： Konrad Exner Elisa Smolka Till Blüher Rainer Stark Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Technische Universität Berlin Pascalstraße 8-9 10587 Berlin Germany

Smart Services can be described as a specific manifestation of Product-Service systems, which mainly refer to customer individual solutions based on the utilization of data derived from cyber-physical products and production systems. In this context the usage data is allocated and analyzed on a platform in order to extract valuable information, thus enabling the development and operationalization of new data-driven business models. In order to support the initial design of Smart Services companies have to achieve a thorough understanding of their existing or obtainable data as well as the related potential options to utilize these data. Based on the analysis of 51 industrial Smart Service use cases data flows and areas of application have been derived and clustered. Moreover, the defined categories are interlinked and mapped to the use cases. The findings have been comprised into an applicable Smart Service design method addressing early design stages. Finally, the approach (DAU flow method) has been applied and evaluated with two case companies, indicating sound qualitative results and providing valuable feedback.

关键词： Smart Services use case design method information categorization

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Integration of Active Pharmaceutical Ingredient production into a pharmaceutical Lean Learning Factory

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Procedia Manufacturing 2019年 31卷 245-250页

作者： Natalie Petrusch Felix Sieckmann Jan P. Menn Holger Kohl Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Technische Universität Berlin Pascalstraße 8-9 10587 Berlin Germany

In the context of the implementation of Lean production systems, companies have become significantly more aware of the need for employee qualification and motivation. Due to the high share of practice, Learning Factories have proven to be an effective approach to respond to this circumstance. While the focus of Learning Factories has so far mainly been on discrete manufacturing, applications in the pharmaceutical industry are still comparatively rare. Based on this, a Learning Factory, that takes into account the special requirements and needs of the pharmaceutical industry, was developed and implemented in collaboration with a German pharmaceutical company. So far, Lean culture and tools have been trained on formulation and packaging processes. However, the active pharmaceutical ingredient (API) production, which is characterized by a higher level of automation as well as chemical and process engineering procedures, was initially not displayed, as no sufficient demand was assumed. Due to the increasing need for a holistic consideration of the whole value chain, the API production is moving into the focus of Lean improvements. In this context, many established tools need to be adapted. From feedback of over 120 conducted trainings and a series of interviews, it became clear, that for employees from API production, it is difficult to transfer the necessary knowledge to their work environment, leading to resistance in implementing Lean tools. In order to counter this problem, the Learning Factory was expanded by an additional API learning module. This increased the willingness of employees to participate in the trainings and to implement the contents.

关键词： Learning Factories Lean production systems Lean Management pharmaceutical industry

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Understanding PLM and PLM customizing: A theoretical fundament for a conceptual approach 15th

Understanding PLM and PLM customizing: A theoretical fundame...

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15th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2018

作者： Venghaus Sucuoglu, Ezgi Stark, Rainer Volkswagen AG Wolfsburg Germany Fraunhofer Institute for Production Systems and Design Technology Berlin Germany Technische Universität Berlin Berlin Germany

ISBN: (纸本)9783030016135

The continuous development of product lifecycle management (PLM) technology depicts many needs for clarification and action especially in PLM understanding and PLM implementation. The adaptation and customizing of PLM technologies become unavoidable and implicate high expenditure in form of costs, time and effort which is often underestimated by organizations. Despite of the importance of PLM adaptation and PLM customizing and its influence on the success of a PLM implementation project, there is no clear basis for an understanding of what PLM adaptation and customizing really is. Furthermore a lack of solution approaches exists that can guide companies during the process of PLM adaptation and customizing. The aim of this paper is to build a foundation for understanding PLM and the customizing of PLM. Furthermore a solution area beyond the software driven focus will be suggested. © IFIP International Federation for Information Processing 2018.

关键词： Life cycle

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Framework for energy efficiency optimization of industrial systems based on the Control Layer Model

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Procedia Manufacturing 2019年 33卷 414-421页

作者： Gregor Thiele Oliver Heimann Knut Grabowski Jörg Krüger Fraunhofer-Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany ÖKOTEC Energiemanagement GmbH EUREF-Campus Haus 13 Torgauer Str. 12-15 10829 Berlin Germany

In the context of sustainable manufacturing, the energy efficient operation of industrial systems is of major interest. This paper presents a modular framework for practical research about energy efficiency optimization of complex technical systems. Whereas many approaches focus on stand-alone machines or processes, this approach is concerned with energy-related coupling of several entities. Using a method for energy-related key performance indicators, the overall efficiency is deduced from all subsystems. A given topology is modeled in an XML-based format, inspired by AutomationML. The framework gives the opportunity to analyze and compare optimization algorithms. First experiments with two optimization algorithms were applied to a simulated cooling system.

关键词： optimization energy efficiency supply technology chiller system control layer model system-of-systems key performance indicator topology based optimization EnEffReg optimizerOne optimizerZero model-based control set-point optimization similarity based optimization

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