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PublicationDeutsche Normungsroadmap Künstliche Intelligenz(DIN, 2020)
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PublicationDeep learning for part identification based on inherent features( 2019)The identification of parts is essential for the efficient automation of logistic processes such as part supply in assembly and disassembly. This paper describes a new method for the optical identification of parts without explicit codes but based on inherent geometrical features with Deep Learning. The paper focusses on the improvement of training of Deep Learning systems taking into account conflicting factors such as limited training data and high variety of parts. Based on a case study in turbine industry the effects of steadily growing training data on the robustness of part classification are evaluated.
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PublicationDevelopment and operation of Digital Twins for technical systems and services( 2019)Digital Twins are new solution elements to enable ongoing digital monitoring and active functional improvement of interconnected products, devices and machines. In addition, benefits of horizontal and vertical integration in manufacturing are targeted by the introduction of Digital Twins. Using the test environment of smart factory cells, this paper investigates methodological, technological, operative, and business aspects of developing and operating Digital Twins. The following Digital Twin dimensions are considered in scientific and application oriented analysis: (1) integration breadth, (2) connectivity modes, (3) update frequency, (4) CPS intelligence, (5) simulation capabilities, (6) digital model richness, (7) human interaction, and (8) product lifecycle. From this, design elements for the development of Digital Twins are derived and presented.
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PublicationIncreasing resource efficiency with an engineering decision support system for comparison of product design variants( 2019)
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PublicationExecution and evaluation of enterprise models in IEM/MO2GO based on Petri net( 2018)Because the growth of internet of things (IOT) technology, stakeholders who come from different research areas (information modeling area, dynamic process modeling area, and so on) will very easily and simultaneously evaluate and control the manufacturing process from all over the world. Therefore, there is an urgent need for a comprehensive enterprise modeling methodology with the integration of information modeling and dynamic process modeling method. However, it is known that there is limited research on the realization of a modeling methodology that can simultaneously handle information modeling and dynamic process modeling. The method for object-oriented business process optimization (MO2GO) system performs modeling in terms of information and process. However, the process modeling part in this system is static. Meanwhile, the Petri net mathematical modeling language has strong dynamic simulation capability. Thus, our main contribution is to analyze the characteristics of Petri net, which would be helpful to the dynamic process modeling realization in the MO2GO system, and integrate Petri net engine into the MO2GO system to allow a static process model to become dynamic. In here, the system can not only display a simulated manufacturing process but also calculate actual information (time and cost) for a final manufactured product. Therefore, it is possible for the system to handle both information modeling and dynamic process modeling. Finally, the MO2GO system will be more competitive in the future industry.
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PublicationLearnstruments: Learning-conducive artefacts to foster learning productivity in production engineering( 2018)Learnstruments are artefacts, which automatically demonstrate their functionality to the learner. They can be used directly at the workplace and aim at increasing the learning and teaching productivity. The huge variety of design paths for Learnstruments requires a systematic approach for their development. A morphology for Learnstruments is introduced. Exemplary learning-conducive applications for manual assembly in international organizations like 3D-PDFs and a Smart-Assembly-Workplace are presented. They help avoiding assembly errors and improve productivity by providing interactive instructions to the learners. By implementing these along the morphology guideline, the consideration of important didactical and technical criteria is ensured.
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PublicationInnovative control of assembly systems and lines( 2017)The increasing demand for flexibility and reconfigurability of assembly lines generates new challenges for the control of these lines and their subsystems, such as robots, grippers, conveyors or automated guided vehicles. Also new requirements for their interaction between each other and the environment as well as with humans arise. On the other hand the rapid change of information and communication technology opens new potentials for innovative control. Due to the high degree of interconnection between controllers, actuators and sensors, the classical automation pyramid is replaced by networked structures with a higher degree of flexibility, but also higher complexity. This trend is supported by the ability to collect and process data within cloud environments, the rapid increase of computational power of decentralized and embedded controllers and the high potential of machine learning for automation. This keynote gives an overview of innovative approaches in ICT and robotics for flexible control and automation of assembly lines and systems.
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PublicationCooperation of human and machines in assembly lines( 2009)Flexibility and changeability of assembly processes require a close cooperation between the worker and the automated assembly system. The interaction between human and robots improves the efficiency of individual complex assembly processes, particularly when a robot serves as an intelligent assistant. The paper gives a survey about forms of human-machine cooperation in assembly and available technologies that support the cooperation. Organizational and economic aspects of cooperative assembly including efficient component supply and logistics are also discussed.
