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Intuitive robot programming through environment perception, augmented reality simulation and automated program verification

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Procedia CIRP 2018年 76卷 161-166页

作者： Jonas Wassermann Axel Vick Jörg Krüger Technische Universität Berlin Pascalstrasse 8-9 10587 Berlin Germany Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstrae 8-9 10587 Berlin Germany

The increasing complexity of products and machines as well as short production cycles with small lot sizes present great challenges to production industry. Both, the programming of industrial robots in online mode using hand-held control devices or in offline mode using text-based programming requires specific knowledge of robotics and manufacturer-dependent robot control systems. In particular for small and medium-sized enterprises the machine control software needs to be easy, intuitive and usable without time-consuming learning steps, even for employees with no in-depth knowledge of information technology. To simplify the programming of application programs for industrial robots, we extended a cloud-based, task-oriented robot control system with environment perception and plausibility check functions. For the environment perception a depth camera and pointcloud processing hardware were installed. We detect objects located in the robot’s workspace by pointcloud processing with ROS and the PCL and add them to the augmented reality user interface of the robot control. The combination of process knowledge from task-oriented application programming and information about available workpieces from automated image processing enables a plausibility check and verification of the robot program before execution. After a robot program has been approved by the plausibility check, it is tested in an augmented reality simulation for collisions with the detected objects before deployment to the physical robot hardware. Experiments were carried out to evaluate the effectiveness of the developed extensions and confirmed their functionality.

关键词： Industrial Robotics Robot Programming Augmented Reality

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Safe human robot collaboration — Operation area segmentation for dynamic adjustable distance monitoring

Safe human robot collaboration — Operation area segmentatio...

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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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Microstructure of Inconel 718 parts with constant mass energy input manufactured with direct energy deposition

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Procedia Manufacturing 2019年 36卷 256-266页

作者： Torsten Petrat Christian Brunner-Schwer Benjamin Graf Michael Rethmeier Fraunhofer Institut for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Federal Institute for Materials Research and Testing Unter den Eichen 87 12205 Berlin Germany Technical University Berlin Institute of Machine Tools and Factory Management Pascalstraße 8-9 10587 Berlin Germany

The laser-based direct energy deposition (DED) as a technology for additive manufacturing allows the production of near net shape components. Industrial applications require a stable process to ensure reproducible quality. Instabilities in the manufacturing process can lead to faulty components which do not meet the required properties. The DED process is adjusted by various parameters such as laser power, velocity, powder mass flow and spot diameter, which interact with each other. A frequently used comparative parameter in welding is the energy per unit length and is calculated from the laser power and the velocity in laser welding. The powder per unit length comparative parameter in the DED process has also be considered, because this filler material absorbs energy in addition to the base material. This paper deals with the influence of mass energy as a comparative parameter for determining the properties of additively manufactured parts. The same energy per unit length of 60 J/mm as well as the same powder per unit length of 7.2 mg/mm can be adjusted with different parameter sets. The energy per unit length and the powder per unit length determine the mass energy. The laser power is varied within the experiments between 400 W and 900 W. Energy per unit length and powder per unit length are kept constant by adjusting velocity and powder mass flow. Using the example of Inconel 718, experiments are carried out with the determined parameter sets. In a first step, individual tracks are produced and analyzed by means of micro section. The geometry of the tracks shows differences in height and width. In addition, the increasing laser power leads to a higher dilution of the base material. To determine the suitability of the parameters for additive manufacturing use, the individual tracks are used to build up parts with a square base area of 20×20 mm². An investigation by Archimedean principle shows a higher porosity with lower laser power. By further analysis of the mic

关键词： direct energy deposition porosity Inconel 718 additive manufacturing laser metal deposition

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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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The bulging effect and its relevance in high power laser beam welding

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IOP Conference Series: Materials Science and Engineering 2021年第1期1135卷

作者： Antoni Artinov Xiangmeng Meng Nasim Bakir Ömer Üstündağ Marcel Bachmann Andrey Gumenyuk Michael Rethmeier Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 12205 Berlin Germany Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Institute for Machine Tools and Factory Management Technische Universität Berlin Pascalstraße 8-9 10587 Berlin Germany

The present work deals with the recently confirmed widening of the weld pool interface, known as a bulging effect, and its relevance in high power laser beam welding. A combined experimental and numerical approach is utilized to study the influence of the bulge on the hot cracking formation and the transport of alloying elements in the molten pool. A technique using a quartz glass, a direct-diode laser illumination, a high-speed camera, and an infrared camera is applied to visualize the weld pool geometry in the longitudinal section. The study examines the relevance of the bulging effect on both, partial and complete penetration, as well as for different sheet thicknesses ranging from 8 mm to 25 mm. The numerical analysis shows that the formation of a bulge region is highly dependent on the penetration depth and occurs more frequently during partial penetration above 6 mm and complete penetration above 8 mm penetration depth, respectively. The location of the bulge correlates strongly with the cracking location. The obtained experimental and numerical results reveal that the bulging effect increases the hot cracking susceptibility and limits the transfer of alloying elements from the top of the weld pool to the weld root.

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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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Investigation of the gap bridgeability at high-power laser hybrid welding of plasma-cut thick mild steels with AC magnetic support

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Journal of Physics: Conference Series 2021年第1期2077卷

作者： Ömer Üstündag Nasim Bakir Andrey Gumenyuk Michael Rethmeier Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 12205 Berlin Germany Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Institute of Machine Tools and Factory Management Technische Universität Berlin Pascalstraße 8-9 10587 Berlin Germany

One of the challenges of the high-power hybrid laser welding of thick steels is the sensitivity of the process of the process to manufacturing tolerances. This usually leads to a time-consuming preparation of the welding edges, such as milling. The study deals with the influence of the edge quality of milled and plasma-cut steel made of S355J2 with a wall thickness of 20 mm on the laser hybrid welded seam quality. Furthermore, the gap bridgeability and the tolerances towards edge misalignment was investigated. An AC magnet was used as backing support to prevent sagging and positioned under the workpiece, to generate an upwards directed electromagnetic pressure. The profiles of the edges and the gap on the top and root side were measured using a digital camera. Single-pass laser hybrid welds of plasma-cut edges could be welded using a laser beam power of just 13.7 kW. A gap bridgeability up to 2 mm and misalignment of edges up to 2 mm could be achieved successful. Additionally, the independence of the cutting side and the welding side was shown, so that samples were welded to the opposite side to their cutting. For evaluation of internal defects or irregularities, X-ray images were carried out. Charpy impact strength tests were performed to determine the toughness of the welds.

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Influence of an external applied AC magnetic field on the melt pool dynamics at high-power laser beam welding

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IOP Conference Series: Materials Science and Engineering 2021年第1期1135卷

作者： Ömer Üstündağ Nasim Bakir Andrey Gumenyuk Michael Rethmeier Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 12205 Berlin Germany Fraunhofer Institute for Production Systems and Design Technology Pascalstraße 8-9 10587 Berlin Germany Institute for Machine Tools and Factory Management Technische Universität Berlin Pascalstraße 8-9 10587 Berlin Germany

The study deals with the determination of the influence of an externally applied oscillating magnetic field on the melt pool dynamics in high power laser beam and hybrid laser arc welding processes. An AC magnet was positioned under the workpiece which is generating an upward directed electromagnetic force to counteract the formation of the droplets. To visualise the melt flow characteristics, several experiments were carried out using a special technique with mild steel from S355J2 with a plate thickness of up to 20 mm and a quartz glass in butt configuration. The profile of the keyhole and the melt flow were recorded with a highspeed camera from the glass side. Additionally, the influence of the magnetic field orientation to the welding direction on the filler material dilution on laser hybrid welding was studied with variating oscillation frequency. The element distribution over the whole seam thickness was measured with X-ray fluorescence (XRF). The oscillation frequency demonstrated a great influence on the melt pool dynamics and the mixing of the elements of the filler wire. The highspeed recordings showed, under the influence of the magnetic field, that the melt is affected under strong vortex at the weld root, which also avoids the formation of droplets.

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