Augmented Reality (AR) has been a focus of research in the field of production for many years with the goal to improve e.g. monitoring and maintenance processes. Although the benefits have been well researched, the AR...
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To optimize the workpiece removal process and maximize the fraction of reusable abrasive particles, it is necessary to ascertain the characteristics of the high-pressure suspension jet process, including the kinetic e...
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The use of carbon fibre reinforced plastic (CFRP) structures in rotationally symmetrical components opens up a new field of lightweight construction with great potential for reducing the mass of moving components. Due...
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Assembly simulations in virtual reality were used increasingly in recent years. Even though a multitude of solutions exists in the commercial market, research is focusing on improving soft factors like usability and f...
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The use of digital technologies in industrial manufacturing reduces operational costs and improves production quality. The “Framework for Spatiotemporal Production Data Acquisition” (PathSense) aims to improve acces...
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The use of digital technologies in industrial manufacturing reduces operational costs and improves production quality. The “Framework for Spatiotemporal Production Data Acquisition” (PathSense) aims to improve access and usability of production data by applying a common data ecosystem. Through integrating operational technology (OT) and information technology (IT), PathSense supports decision-making and process optimization. The framework uses the concept of digital shadows to collect critical information from sensors within the continuous manufacturing processes, e.g., welding or gluing lines. Spatial and temporal digital shadows are developed in accordance with human spatial cognition to support sophisticated–yet intuitive–human-computer interactions without the need for advanced data science skills. The backbone of the framework consists of robust data pipelines with a setup incorporating modern IT protocols, such as OPC UA and MQTT, to support the efficient acquisition and management of data. The paper addresses the challenges associated with the combination of IT and OT in cyber-physical systems, stressing modern complex data-intensive manufacturing as one exemplary domain to be tackled by scalable and secure data architectures. The paper identifies two major future directions: refining data integration processes and embedding advanced machine learning algorithms to enable automated data analysis and improve process quality monitoring. In summary, PathSense proposes a data-driven approach for quality inspection in manufacturing, which may eventually enhance industry practices and move towards data-driven decisions and increased operational flexibility.
Due to the high abrasive wear and the tendency to workpiece damages, the manufacturing of high-quality bores in carbon fibre reinforced plastics (CFRP) is still one of the major goals in tool development. In this work...
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Due to the high abrasive wear and the tendency to workpiece damages, the manufacturing of high-quality bores in carbon fibre reinforced plastics (CFRP) is still one of the major goals in tool development. In this work, reaming tests are performed on CFRP in order to characterise the relationship between tool geometry, process forces and tool wear. After a preliminary investigation of a taper reamer, diverse carbide tools have been tested which exhibit different values of rake and clearance angle. The forces measurement took place using a rotating dynamometer, while the evaluation of the tool wear has been realised by microscopic images via structured light projection. Different forms of wear appear, while hardly any differences in the force curves can be detected when applying different angles of the cutting wedge.
When conducting biomechanical testing or clinical training using embalmed human soft tissues, it is essential to understand their impact on biomechanical properties and their time dependence. Previous studies have inv...
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Recent publications have put a focus on metal vaporization during the PBF-LB/M process. It is intimately connected with component defects and process by-products such as plume. Our study purposes an in-situ image proc...
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Robots are no longer stand-alone systems on the factory floor. The demand for industrial robots (market) is anticipated to be growing to 65 billion euros by the year 2023. Within all areas of robotics, the demand for ...
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Robots are no longer stand-alone systems on the factory floor. The demand for industrial robots (market) is anticipated to be growing to 65 billion euros by the year 2023. Within all areas of robotics, the demand for collaborative and more flexible systems is rising as well. The level of desired collaboration and increased flexibility will only be reached if the systems are developed as a whole, e.g. perception, reasoning and physical manipulation. The rising need for collaborative robots in the automation industry is acting as a driver for this market and is expected to serve as a market opportunity for future growth. However, at the same time especially smaller companies have difficulties to formulate a concrete vision and strategies for the uptake of robotics, finding skilled workforce to develop and deploy the robot systems and/or work in the manufacturing industry. A number of Digital Innovation Hubs (DIHs) have been developed to enhance the knowledge and technology transfer from laboratories to factory floors, mitigating the skills gap and supporting the formulation of innovation ecosystems with the specific focus on small and medium-sized companies around Europe. The main aim of this paper is to introduce the concept and approach taken in H2020 TRINITY-project that aims to develop a Robotics Innovation Hub focused on Agile Production. The paper will introduce the concept and technical approach of the project, and discusses the preliminary results, challenges and opportunities of these kind of DIHs.
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