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International Conference on Control, Automation and Robotics (ICCAR)

作者： Martin J. Rosenstrauch Jörg Krüger Institute for Machine Tools and Factory Management Institute for Production Systems and Design Technology Fraunhofer IPK Berlin Germany Technische Universitat Berlin Berlin Berlin DE

A core challenge of human robot collaboration is to ensure safety. By renouncing guards potential hazards raise. In this paper an approach is presented where the actual used operating area of an industrial robot gets segmented out of his whole workspace. Therefore an industrial robot gets monitored with a time of flight sensor. Subsequently the recorded 3D data gets processed and the operating area segmented by applying an octree algorithm. The information thus determined about the hazard zone can be used for an application specific adjustment of safety periphery systems. This is exemplary realized by ultrasound distance sensor modules which get individually parametrized depending on the pre-segmented operating area.

关键词： Robot sensing systems Service robots Robot kinematics Monitoring Safety Three-dimensional displays

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Learning Factory for Industry 4.0 to provide future skills beyond technical training

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Procedia Manufacturing 2018年 23卷 27-32页

作者： Burkhard Schallock Christoffer Rybski Roland Jochem Holger Kohl Fraunhofer Institute for Production Systems and Design Technology (IPK) Pascalstr.8-9 Berlin 10587 Germany Technische Universität Berlin Pascalstr.8-9 Berlin 10587 Germany

The paper will describe the design of a learning factory for Industry 4.0 that addresses the growing demand for future skills of production staff. Existing learning factories often focus on the technical skills whereas this learning factory also trains decision making, group work and performance monitoring skills. The paper refers to the existing categorizes of learning factories and unveils its numerous features. The conceptual design includes theoretical and practical parts, which prove to be successful in a German learning factory that was realized by the authors. Especially, for the industry 4.0 environment, the layout consists of three stages of a production system, from manual to automatized manufacturing. The practical tasks cover the introduction of smart devices, connection of information flows as well as monitoring of performance. The didactical design of the training program provides a sustainable approach by not only realizing training courses but also includes preparation with management, mid-term coaching and success monitoring after the training. The learning factory is a part of a whole research institute for intelligent manufacturing in China including consultancy and application support. One of the underlying goals of the learning factory is to enable production staff for change management, decision making and innovation.

关键词： Learning Factory Industrie 4.0 Intelligent manufacturing Future skill demand Performance management

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Smart Life Cycle Monitoring for Sustainable Maintenance and Production – An example for Selective Laser Melting Machine

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Procedia Manufacturing 2017年 11卷 711-717页

作者： Uhlmann, Eckart Pontes, Rodrigo Pastl Laghmouchi, Abdelhakim Geisert, Claudio Hohwieler, Eckhard Fraunhofer Institute for Production Systems and Design Technology – IPK Berlin Germany Institute for Machine Tools and Factory Management IWF - Technische Universität Berlin Germany

Smart linking, evaluation and provision of information over the life cycle of a product are becoming growingly important. The use of information extracted from combination of monitoring data, product data, maintenance information, and from product utilisation data can increase the availability of production machines and reduce the costs and resources cause by machine downtime. Especially for new manufacturing technologies such as Selective Laser Melting, the storage and management of such information are crucially important to develop knowledge and improve the quality of the machines and their products. By acquiring data from the machine, processing them and calculating proper key performance indicators, the critical region where the failures are most commonly found and the critical subsystems responsible for the failures are identified. Moreover, using the historical data, the tolerances for those subsystems can be defined. © 2017 The Authors

关键词： data analysis life cycle monitoring selective laser melting Smart linking

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Decentralized Data Analytics for Maintenance in Industrie 4.0

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Procedia Manufacturing 2017年 11卷 1120-1126页

作者： Uhlmann, Eckart Laghmouchi, Abdelhakim Geisert, Claudio Hohwieler, Eckhard Fraunhofer Institute for Production Systems and Design Technology – IPK Berlin Germany Institute for Machine Tools and Factory Management IWF - Technische Universität Berlin Germany

Due to the increased digital networking of machines and systems in the production area, large datasets are generated. In addition, more external sensors are installed at production systems to acquire data for production and maintenance optimization purposes. Therefore, data analytics and interpretation is one of the challenges in Industrie 4.0 applications. Reliable analysis of data (e.g. internal and external sensors), such as system-internal alarms and messages produced during the operation, can be used to optimize production and maintenance processes. Furthermore, information and knowledge can be extracted from raw data and used to develop data-driven business models and services, e.g. offer new availability contracts for production systems. This paper illustrates an approach for decentralized data analytics based on smart sensor networks. © 2017 The Authors

关键词： algorithms classifier data analytics Industrie 4.0 production systems

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Cluster identification of sensor data for predictive maintenance in a Selective Laser Melting machine tool

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Procedia Manufacturing 2018年 24卷 60-65页

作者： Eckart Uhlmann Rodrigo Pastl Pontes Claudio Geisert Eckhard Hohwieler Fraunhofer Institute for Production Systems and Design Technology (IPK) Pascalstraße 8-9 Berlin 10587 Germany Technische Universität Berlin – Institute for Machine Tools and Factory Management (IWF) Pascalstraße 8-9 Berlin 10587 Germany

Selective laser melting has become one of the most current new technologies used to produce complex components in comparison to conventional manufacturing technologies. Especially, existing selective laser melting machine tools are not equipped with analytics tools that evaluate sensor data. This paper describes an approach to analyze and visualize offline data from different sources based on machine learning algorithms. Data from three sensors were utilized to identify clusters. They illustrate the normal operation of the machine tool and three faulty conditions. With these results, a condition monitoring system can be implemented that enables those machine tools for predictive maintenance solutions.

关键词： Selective laser melting sensor data machine learning clustering predictive maintenance

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Smoothed Particle Hydrodynamics simulation of the machining process of Inconel 718

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Procedia Manufacturing 2018年 18卷 1-11页

作者： Eckart Uhlmann Enrico Barth Fraunhofer Institute for Production Systems and Design Technology (IPK) Pascalstr. 8-9 10587 Berlin Germany Institute for Machine Tools and Factory Management (IWF) Technische Universität Berlin Pascalstr. 8-9 10587 Berlin Germany

The Smoothed Particle Hydrodynamics (SPH) is a meshfree simulation method which allows to describe the machining process of the nickel-based alloy Inconel 718. This paper analyses the accuracy of a developed simulation model for an orthogonal turning process. The simulation results show the occurring process forces. Subsequently, the model is extended with a variable chip thickness to consider the different engagement condition during a peripheral down milling process. The model allows to investigate the influence of geometry parameters of the cutting edge for possible tools designs with little economic and financial expenses.

关键词： nickel-based alloys milling tool Smoothed-particle hydrodynamics, simulation machining process tool development cutting forces

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Manufacturing of carbide tools by Selective Laser Melting

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Procedia Manufacturing 2018年 21卷 765-773页

作者： Eckart Uhlmann André Bergmann Robert Bolz Fraunhofer Institute for Production Systems and Design Technology (IPK) Pascalstraße 8-9 Berlin 10587 Germany Technische Universität Berlin – Institute for Machine Tools and Factory Management (IWF) Pascalstraße 8-9 Berlin 10587 Germany

Application fields of electrical discharge machining (EDM) are limited due to given process conditions. When producing structures of high aspect ratios or using multi-axis machining, removed particles assemble at the machining zone, leading to process instabilities and increasing tool wear. A promising approach to improve EDM process conditions is the utilization of flushing channels in the tool electrode. However, with increasing complexity of the electrode geometry and the local integration of the mentioned flushing channels, conventional electrode manufacturing reaches its limitations. By applying Selective Laser Melting (SLM), these limitations are eliminated. An additional benefit is the efficient use of material during SLM, where nearly no waste is produced, because remaining powder can be used for the next SLM-process. The appropriate integration of flushing channels, even for complicated electrode geometries, improves process conditions during EDM in a variety of applications, leading to a higher material removal rate V W and reduced tool wear ϑ compared to machining without flushing. Additionally, the number of required tool electrodes can be reduced, as SLM enables an efficient integration and miniaturization of all features in a single electrode, what results in a far more sustainable process chain. Of particular interest in the field of EDM is carbide. Because of its wear resistance and stability, it is an ideal electrode material, which is commonly applied in µEDM. Tungsten carbide-cobalt is representative for this group of materials, which is already used in tool manufacturing. Several tests show a general suitability of carbide tool electrodes made by SLM for EDM-processing. However, the SLM process parameters and the composition of the carbide-cobalt show significant impact to the EDM results. A lower proportion of cobalt leads to reduced material removal rates, whereas the level of tool wear remains at a similar level. In order to benefit from the a

关键词： additive manufacturing selective laser melting electrical discharge machining tungsten carbide

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Concept of Sustainable Data for a Selective Laser Melting Machine

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Procedia Manufacturing 2018年 21卷 655-662页

作者： Eckart Uhlmann Rodrigo Pastl Pontes Abdelhakim Laghmouchi André Bergmann Fraunhofer Institute for Production Systems and Design Technology (IPK) Pascalstraße 8-9 Berlin 10587 Germany Technische Universität Berlin – Institute for Machine Tools and Factory Management (IWF) Pascalstraße 8-9 Berlin 10587 Germany

Due to increased digitalization in the production environment, data, information, and sustainable management approaches should be developed in order to enable production machines for data acquisition, data exchange and data analysis. Especially for additive manufacturing technologies, those approaches are extremely important to detect and avoid failures in the manufacturing process. A critical failure during the manufacturing process could lead to a defective workpiece, wasting resources. Within this context, this work addresses the concept of sustainable data for a selective laser melting machine tool. The selective laser melting process is one of the additive manufacturing technologies that is capable of producing lighter and more complex functional workpieces in comparison to conventional manufacturing technologies. Beyond the use of the machine tool system internal data (e.g. process data, internal sensors), additional information such as energy consumption and data provided using external sensors are required to detect the current condition of production process. In order to observe if the considered data sources are capable of identifying abnormal conditions of the machine tool, failures from five subsystems were inserted during a manufacturing process of a reference workpiece. Four of the five data sources detect failures that influenced the layer quality while they are occurring. Thus, the results could be used to allow the operator to take measures to save energy and resources.

关键词： Production SLM machine data management information analysis

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Wear behaviour of diamond coated micro-milling tools during micro machining 17

Wear behaviour of diamond coated micro-milling tools during ...

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17th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2017

作者： Uhlmann, E. Kuche, Y. Oberschmidt, D. Polte, J. Fraunhofer Institute for Production Systems and Design Technology IPK Germany Institute for Machine Tools and Factory Management IWF Technische Universität Berlin Germany

ISBN: (纸本)9780995775107

Graphite electrodes are used in the die sinking process for manufacturing of micro structured tools in the die and mould fabrication. They are machined using the micro-milling process. During the cutting process graphite grains have strong abrasive effects on the cutting edges and lead to high tool wear. Consequences are short path length lc and geometrical errors. One approach to reduce tool wear is the tool coating with diamond. The diamond coating changes the cutting edge micro geometry which has influences on the process behaviour. In this paper, the wear behaviour of micro-milling tools with diameter D = 0.5 mm and different micro geometries is analysed and discussed. The results show better wear behaviour for prepared and coated tools.

关键词： Coatings

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Modeling approach regarding surface functionalization by force-controlled micro and nano forming 17

Modeling approach regarding surface functionalization by for...

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17th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2017

作者： Uhlmann, E. Kühne, S. Jagodzinski, M. Malcher, M. Trevino, R. Institute for Machine Tools and Factory Management IWF Technische Universität Berlin Germany Fraunhofer Institute for Production Systems and Design Technology IPK Germany

ISBN: (纸本)9780995775107

Surface functionalization allows the control of fluidic, tribological, biological or optical properties. Suitable processes are interference lithography (IL), ultra-precision machining and micro and nano forming. The force-controlled forming process enables a reproducible production of structures with an absolute height in the double-digit nanometer range. The deformation is a complex process consisting of controlled and uncontrolled material deposition. Knowledge about the uncontrolled behaviour, however, allows a reproducible production of defined structures. A model approach with regard to machining parameter prediction is presented here. The tool shape is transferred into the surface by plastic penetration of a faceted diamond tool. By means of a superimposed tool movement, linear structures can be generated. Larger areas can be structured by repeating this process. The advantage of the force control in comparison to the displacement control is a defined penetration depth relative to the surface with reproducibility in the single-digit nanometer range. The force-control is carried out gravimetrically (0.05 N -1-1, 30 nm 2neg2) is considered as ideal load. As additional result of these experiments, physical approaches are available, which can later form the basis of a physical model.

关键词： Optical properties

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