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Adapting augmented reality systems to the users’ needs using gamification and error solving methods
(2021)
Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
In the study, the process chain of additive manufacturing by means of powder bed fusion will be presented based on the material glass. In order to reliably process components additively, new concepts with different solutions were developed and investigated.
Compared to established metallic materials, the properties of glass materials differ significantly. Therefore, the process control was adapted to the material glass in the investigations. With extensive parameter studies based on various glass powders such as borosilicate glass and quartz glass, scientifically proven results on powder bed fusion of glass are presented. Based on the determination of the particle properties with different methods, extensive investigations are made regarding the melting behavior of glass by means of laser beams. Furthermore, the experimental setup was steadily expanded. In addition to the integration of coaxial temperature measurement and regulation, preheating of the building platform is of major importance. This offers the possibility to perform 3D printing at the transformation temperatures of the glass materials. To improve the component’s properties, the influence of a subsequent heat treatment was also investigated.
The experience gained was incorporated into a new experimental system, which allows a much better exploration of the 3D printing of glass. Currently, studies are being conducted to improve surface texture, building accuracy, and geometrical capabilities using three-dimensional specimen.
The contribution shows the development of research in the field of 3D printing of glass, gives an insight into the machine and process engineering as well as an outlook on the possibilities and applications.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed.
The implementation of IO-Link in the automation industry has increased over the years. Its main advantage is it offers a digital point-to-point plugand-play interface for any type of device or application. This simplifies the communication between devices and increases productivity with its different features like self-parametrization and maintenance. However, its complete potential is not always used.
The aim of this paper is to create an Arduino based framework for the development of generic IO-Link devices and increase its implementation for rapid prototyping. By generating the IO device description file (IODD) from a graphical user interface, and further customizable options for the device application, the end-user can intuitively develop generic IO-Link devices. The peculiarity of this framework relies on its simplicity and abstraction which allows to implement any sensor functionality and virtually connect any type of device to an IO-Link master. This work consists of the general overview of the framework, the technical background of its development and a proof of concept which demonstrates the workflow for its implementation.
Rapid Tooling
(2019)
The manufacturing share of laser powder bed fusion (L-PBF) increases in industrial application, but still many process steps are manually operated. Additionally, it is not possible to achieve tight dimensional tolerances or low surfaces roughness. Hence, a process chain has to be set up to combine additive manufacturing (AM) with further machining technologies. To achieve a continuous workpiece flow as basis for further industrialization of L-PBF, the paper presents a novel substrate system and its application on L-PBF machines and post-processing. The substrate system consists of a zero-point clamping system and a matrix-like interface of contact pins to be substantially connected to the workpiece within the L-PBF process.
While bringing new opportunities, the Industry 4.0 movement also imposes new challenges to the manufacturing industry and all its stakeholders. In this competitive environment, a skilled and engaged workforce is a key to success. Gamification can generate valuable feedbacks for improving employees’ engagement and performance. Currently, Gamification in workspaces focuses on computer-based assignments and training, while tasks that require manual labor are rarely considered. This research provides an overview of Enterprise Gamification approaches and evaluates the challenges. Based on that, a skill-based Gamification framework for manual tasks is proposed, and a case study in the Industry 4.0 model factory is shown.
As researchers continue to seek the expansion of the material base for additive manufacturing, there is a need to focus attention on the Ni–Cu group of alloys which conventionally has wide industrial applications. In this work, the G-NiCu30Nb casting alloy, a variant of the Monel family of alloys with Nb and high Si content is, for the first time, processed via the laser powder bed fusion process (LPBF). Being novel to the LPBF processes, optimum LPBF parameters were determined, and hardness and tensile tests were performed in as-built conditions and after heat treatment at 1000 °C. Microstructures of the as-cast and the as-built condition were compared. Highly dense samples (99.8% density) were achieved after varying hatch distance (80 µm and 140 µm) with scanning speed (550 mm/s–1500 mm/s). There was no significant difference in microhardness between varied hatch distance print sets. Microhardness of the as-built condition (247 HV0.2) exceeded the as-cast microhardness (179 HV0.2.). Tensile specimens built in vertical (V) and horizontal (H) orientations revealed degrees of anisotropy and were superior to conventionally reported figures. Post heat treatment increased ductility from 20% to 31% (V), as well as from 16% to 25% (H), while ultimate tensile strength (UTS) and yield strength (YS) were considerably reduced.
The increasing digitalization brings new opportunities but also puts new challenges to modern industrial systems. Software agents are one of the key technologies towards self-optimizing factories and are currently used to address the needs of cyber-physical production systems (CPPS). However their interplay in industrial settings needs to be understood better.This paper focusses on securing a cloud infrastructure for multi-agent systems for industrial sites. An industrial site contains multiple production processes that need to communicate with each other and each physical resource is abstracted with a software agent. This volatile architecture needs to be managed and protected from manipulation. The proposed infrastructure presents a security concept for TCP/IP communication between agents, machines, and external networks. It is based on open-source software and tested on a three-node edge cloud controlling a model-plant.
The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
Improving the Mechanical Strength of Dental Applications and Lattice Structures SLM Processed
(2020)
To manufacture custom medical parts or scaffolds with reduced defects and high mechanical characteristics, new research on optimizing the selective laser melting (SLM) parameters are needed. In this work, a biocompatible powder, 316L stainless steel, is characterized to understand the particle size, distribution, shape and flowability. Examination revealed that the 316L particles are smooth, nearly spherical, their mean diameter is 39.09 μm and just 10% of them hold a diameter less than 21.18 μm. SLM parameters under consideration include laser power up to 200 W, 250–1500 mm/s scanning speed, 80 μm hatch spacing, 35 μm layer thickness and a preheated platform. The effect of these on processability is evaluated. More than 100 samples are SLM-manufactured with different process parameters. The tensile results show that is possible to raise the ultimate tensile strength up to 840 MPa, adapting the SLM parameters for a stable processability, avoiding the technological defects caused by residual stress. Correlating with other recent studies on SLM technology, the tensile strength is 20% improved. To validate the SLM parameters and conditions established, complex bioengineering applications such as dental bridges and macro-porous grafts are SLM-processed, demonstrating the potential to manufacture medical products with increased mechanical resistance made of 316L.
Laser-based Additive Manufacturing (AM) processes for the use of metals out of the powder bed have been investigated profusely and are prevalent in industry. Although there is a broad field of application, Laser Powder Bed Fusion (LPBF), also known as Selective Laser Melting (SLM) of glass is not fully developed yet. The material properties of glass are significantly different from the investigated metallic material for LPBF so far. As such, the process cannot be transferred, and the parameter limits and the process sequence must be redefined for glass. Starting with the characterization of glass powders, a parameter field is initially confined to investigate the process parameter of different glass powder using LPBFprocess. A feasibility study is carried out to process borosilicate glass powder. The effects of process parameters on the dimensional accuracy of fabricated parts out of borosilicate and hints for the post-processing are analysed and presented in this paper.
Tribological performance of biodegradable lubricants under different surface roughness of tools
(2019)
In competition with other modes of transport, rail freight transport is looking for solutions to become more attractive. Short-term success can be achieved through the data-driven optimization of operations and maintenance as well as the application of novel strategies such as prescriptive maintenance. After introducing the concept of prescriptive maintenance, this paper aims to prove that vehicle-focused applications of this approach indeed have the potential to increase attractiveness. However, even greater advantages can be activated if data from the horizontal network of the vehicle is available. Drawing on the state of the art in research and technology in the field of cyber-physical systems (CPS) as well as digital twins and shadows, our work serves to design a system of systems for the horizontal interconnection of a rail vehicle and to conceptualize a draft for a digital twin of a locomotive.
Rare event simulation to optimise maintenance intervals of safety critical redundant subsystems
(2018)
For smaller railway operators or those with a diverse fleet, it can be difficult to collect sufficient data to improve maintenance programs. At the same time, new rules such as entity in charge of maintenance – ECM – regulations impose an additional workload by requiring a dedicated maintenance management system and specific reports. The RailCrowd platform sets out to facilitate compliance with ECM and similar regulations while at the same time pooling anonymised fleet data across operators to form virtual fleets, providing greater data insights.
Sensor positioning and thermal model for condition monitoring of pressure gas reservoirs in vehicles
(2018)
This work demonstrates how the interaction between particle image velocimetry (PIV) and robotics can massively increase measurement efficiency. The interdisciplinary approach is shown using the complex example of an automated, large scale, industrial environment: a typical automotive wind tunnel application. Both the high degree of flexibility in choosing the measurement region and the complete automation of stereo PIV measurements are presented. The setup consists of a combination of three robots, individually used as a 6D traversing unit for the laser illumination system as well as for each of the two cameras. Synchronised movements in the same reference frame are realised through a master-slave setup with a single interface to the user. By integrating the interface into the standard wind tunnel management system, a single measurement plane or a predefined sequence of several planes can be requested through a single trigger event, providing the resulting vector fields within minutes.
In this paper, a brief overview on the demands of large scale industrial PIV and the existing solutions is given. Afterwards, the concept of RoboPIV is introduced as a new approach. In a first step, the usability of a selection of commercially available robot arms is analysed. The challenges of pose uncertainty and importance of absolute accuracy are demonstrated through comparative measurements, explaining the individual pros and cons of the analysed systems. Subsequently, the advantage of integrating RoboPIV directly into the existing wind tunnel management system is shown on basis of a typical measurement sequence. In a final step, a practical measurement procedure, including post-processing, is given by using real data and results. Ultimately, the benefits of high automation are demonstrated, leading to a drastic reduction in necessary measurement time compared to non-automated systems, thus massively increasing the efficiency of PIV measurements.
The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements.
The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance
(2016)
Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
(2017)
Towards inclusion of the freight rail system in the industrial internet of things - Wagon 4.0
(2017)
This paper presents the results of an eigenvalue analysis of the Fatih Sultan Mehmet Bridge. A high-resolution finite element model was created directly from the available design documents. All physical properties of the structural components were included in detail, so no calibration to the measured data was necessary. The deck and towers were modeled with shell elements. A nonlinear static analysis was performed before the eigenvalue calculation. The calculated natural frequencies and corresponding mode shapes showed good agreement with the available measured ambient vibration data. The calculation of the effective modal mass showed that nine modes had single contributions higher than 5 % of the total mass. They were in a frequency range up to 1.2 Hz. The comparison of the results for the torsional modes especially demonstrated the advantage of using thin shell finite elements over the beam modeling approach.
We present a new Min-Max theorem for an optimization problem closely connected to matchings and vertex covers in balanced hypergraphs. The result generalizes Kőnig’s Theorem (Berge and Las Vergnas in Ann N Y Acad Sci 175:32–40, 1970; Fulkerson et al. in Math Progr Study 1:120–132, 1974) and Hall’s Theorem (Conforti et al. in Combinatorica 16:325–329, 1996) for balanced hypergraphs.
We prove characterizations of the existence of perfect ƒ-matchings in uniform mengerian and perfect hypergraphs. Moreover, we investigate the ƒ-factor problem in balanced hypergraphs. For uniform balanced hypergraphs we prove two existence theorems with purely combinatorial arguments, whereas for non-uniform balanced hypergraphs we show that the ƒ-factor problem is NP-hard.
An equitable graph coloring is a proper vertex coloring of a graph G where the sizes of the color classes differ by at most one. The equitable chromatic number is the smallest number k such that G admits such equitable k-coloring. We focus on enumerative algorithms for the computation of the equitable coloring number and propose a general scheme to derive pruning rules for them: We show how the extendability of a partial coloring into an equitable coloring can be modeled via network flows. Thus, we obtain pruning rules which can be checked via flow algorithms. Computational experiments show that the search tree of enumerative algorithms can be significantly reduced in size by these rules and, in most instances, such naive approach even yields a faster algorithm. Moreover, the stability, i.e., the number of solved instances within a given time limit, is greatly improved.
Since the execution of flow algorithms at each node of a search tree is time consuming, we derive arithmetic pruning rules (generalized Hall-conditions) from the network model. Adding these rules to an enumerative algorithm yields an even larger runtime improvement.
The aim of this work was to perform a detailed investigation of the use of Selective Laser Melting (SLM) technology to process eutectic silver-copper alloy Ag 28 wt. % Cu (also called AgCu28). The processing occurred with a Realizer SLM 50 desktop machine. The powder analysis (SEM-topography, EDX, particle distribution) was reported as well as the absorption rates for the near-infrared (NIR) spectrum. Microscope imaging showed the surface topography of the manufactured parts. Furthermore, microsections were conducted for the analysis of porosity. The Design of Experiments approach used the response surface method in order to model the statistical relationship between laser power, spot distance and pulse time.
Today, the assembly of laser systems requires a large share of manual operations due to its complexity regarding the optimal alignment of optics. Although the feasibility of automated alignment of laser optics has been shown in research labs, the development effort for the automation of assembly does not meet economic requirements – especially for low-volume laser production. This paper presents a model-based and sensor-integrated assembly execution approach for flexible assembly cells consisting of a macro-positioner covering a large workspace and a compact micromanipulator with camera attached to the positioner. In order to make full use of available models from computer-aided design (CAD) and optical simulation, sensor systems at different levels of accuracy are used for matching perceived information with model data. This approach is named "chain of refined perception", and it allows for automated planning of complex assembly tasks along all major phases of assembly such as collision-free path planning, part feeding, and active and passive alignment. The focus of the paper is put on the in-process image-based metrology and information extraction used for identifying and calibrating local coordinate systems as well as the exploitation of that information for a part feeding process for micro-optics. Results will be presented regarding the processes of automated calibration of the robot camera as well as the local coordinate systems of part feeding area and robot base.
Wireless systems for machinery safety : Requirements and solutions for wireless real time systems
(2015)
Unsteady flow measurements in the wake behind a wind-tunnel car model by using high-speed planar PIV
(2015)
This study investigates unsteady characteristics of the wake behind a 28%-scale car model in a wind tunnel using highspeed planar particle image velocimetry (PIV). The car model is based on a hatchback passenger car that is known to have relatively high fluctuations in its aerodynamic loads. This study primarily focuses on the lateral motion of the flow on the horizontal plane to determine the effect of the flow motion on the straight-line stability and the initial steering response of the actual car on a track. This paper first compares the flow fields in the wake behind the above mentioned model obtained using conventional and high-speed planar PIV, with sampling frequencies of 8 Hz and 1 kHz, respectively. Large asymmetrically coherent flow structures, which fluctuate at frequencies below 2 Hz, are observed in the results of highspeed PIV measurements, whereas conventional PIV is unable to capture these features of the flow owing to aliasing. This flow pattern with a laterally swaying motion is represented by opposite signs of cross-correlation coefficients of streamwise velocity fluctuations for the two sides of the car model. Effects of two aerodynamic devices that are known to reduce the
fluctuation levels of the aerodynamic loads are then extensively investigated. The correlation analyses reveal that these devices indeed reduce the fluctuation levels of the flow and the correlation values around the rear combination-lamp, but it is found that the effects of these devices are different around the c-pillar.
The cooling process in induction based crucible melting furnaces for Industrial applications is one of the important and challenging factors in production and safety engineering. Accordingly, proper implementation of the cooling system of the furnace using optimum cooling guides and fail-safe features are critical in order to improve the safety of the process. Regarding this, manufacturing of porous material with high electrical isolation for the drainage segments of the cooling channels is examined in this study. Consequently, various geometries with different porosities using glass and ceramic powder are fabricated using Selective Laser Sintering (SLS) process. The manufactured parts are examined in a prototype furnace testing and the feasibility of the SLS manufacturing of parts for this application is discussed.
The main objective of our ROS Summer School series is to introduce MA level students to program mobile robots with the Robot Operating System (ROS). ROS is a robot middleware that is used my many research institutions world-wide. Therefore, many state-of-the-art algorithms of mobile robotics are available in ROS and can be deployed very easily. As a basic robot platform we deploy a 1/10 RC cart that is wquipped with an Arduino micro-controller to control the servo motors, and an embedded PC that runs ROS. In two weeks, participants get to learn the basics of mobile robotics hands-on. We describe our teaching concepts and our curriculum and report on the learning success of our students.
The production and assembly of customized products increases the demand for flexible automation systems. One approach is to remove the safety fences that separate human and industrial robot to combine their skills. This collaboration possesses a certain risk for the human co-worker, leading to numerous safety concepts to protect him. The human needs to be monitored and tracked by a safety system using different sensors. The proposed system consists of a RGBD camera for surveillance of the common working area, an array of optical distance sensors to compensate shadowing effects of the RGBD camera and a laser range finder to detect the co-worker when approaching the work cell. The software for collision detection, path planning, robot control and predicting the behaviour of the co-worker is based on the Robot Operating System (ROS). A first prototype of the work cell shows that with advanced algorithms from the field of mobile robotics a very flexible safety concept can be realized: the robot not simply stops its movement when detecting a collision, but plans and executes an alternative path around the obstacle.
The radio-based wireless data communication has made the realization of new technical solutions possible in many fields of the automation technology (AT). For about ten years, a constant disproportionate growth of wireless technologies can be observed in the automation technology.
However, it shows that especially for the AT, conventional technologies of office automation are unsuitable and/or not manageable. The employment of mobile services in the industrial automation technology has the potential of significant cost and time savings. This leads to an increased productivity in various fields of the AT, for example in the factory and process automation or in production logistics. In this paper technologies and solutions for an automation-suited supply of mobile wireless services will be introduced under the criteria of real time suitability, IT-security and service orientation.
Emphasis will be put on the investigation and development of wireless convergence layers for different radio technologies, on the central provision of support services for an easy-to-use, central, backup enabled management of combined wired / wireless networks and on the study on integrability in a Profinet real-time Ethernet network.
Selective Laser Melting (SLM) is one of the Additive Manufacturing (AM) technologies applicable for producing complex geometries which are typically expensive or difficult to fabricate using conventional methods. This process has been extensively investigated experimentally for various metals and the fabrication process parameters have been established for different applications; however, fabricating 3D glass objects using SLM technology has remained a challenge so far although it could have many applications. This paper presents a summery on various experimental evaluations of a material database incorporating the build parameters of glass powder using the SLM process for jewelry applications.
We present an electromechanically coupled Finite Element model for cardiac tissue. It bases on the mechanical model for cardiac tissue of Hunter et al. that we couple to the McAllister-Noble-Tsien electrophysiological model of purkinje fibre cells. The corresponding system of ordinary differential equations is implemented on the level of the constitutive equations in a geometrically and physically nonlinear version of the so-called edge-based smoothed FEM for plates. Mechanical material parameters are determined from our own pressure-deflection experimental setup. The main purpose of the model is to further examine the experimental results not only on mechanical but also on electrophysiological level down to ion channel gates. Moreover, we present first drug treatment simulations and validate the model with respect to the experiments.