bluuebunny/crossref_metadata_2025_split huggingface dataset:
A discussion to promote global sustainability techniques for motivating plastic waste to minimize carbon footprints
Authors: Kalita Ananya , Singh Pranveer , Baruah Sunandan , Barman Utpal , Saikia Ankur Pan 
Published: July 2023

AbstractThis paper emphasizes the significant challenges facing the sustainable environment, including managing and handling plastic waste and reducing carbon footprints. To tackle these challenges, it is essential to identify people's awareness levels of waste handling techniques and their pro‐environmental behaviors. The study focuses on Guwahati, one of the most important cities in Northeast India, which generates increasing plastic waste daily. The paper aims to identify the factors contributing to the reduction of carbon footprints resulting from plastic waste management activities. The data collected from 1326 respondents was analyzed using factor analysis, and the reliability of the dataset was confirmed using Cronbach's alpha (0.84 for the awareness level of waste management techniques and 0.780 for the prevalent mode of plastic waste management techniques). KMO (0.796), Bartlett's test of sphericity (p < 0.001), and determinant score (0.019) were used to assess the data adequacy and factorability of the dataset, and the results were found to be satisfactory. Principal component analysis, exploratory factor analysis, and varimax orthogonal rotation method were used to identify high‐loaded factors by reducing the number of variables. The results showed that two highly loaded components, namely awareness level of waste management techniques (AWMT) and prevalent mode of plastic waste management techniques (PWMT), explained 27.53% and 24.34% of the total variance, respectively, with eigenvalues of 3.35 and 2.88. The regression model confirmed the statistical significance of these factors (p < 0.001) and their relationship with the dependent variable, greenhouse reduction (GHGR). The study proposes that minimizing carbon footprints in the environment can be achieved by focusing on a limited number of controllable factors such as AWMT and PWMT. This study provides valuable insights to the authorities in controlling waste generation and achieving a pollution‐free environment.
Living Earth—A Methodology for Modeling the Environment of Construction Sites Via Digital Twins
Authors: Bliznyuk Artem , Schluse Michael , Roßmann Jürgen 
Published: July 2023

AbstractThe architecture, engineering and construction (AEC) industry appears hesitant to embrace new digital innovations. One of the few recent successful examples is the introduction of the building information modeling (BIM) paradigm. However, the focus here lies mainly on the building itself and does not support the construction environment. This paper presents a methodology for the development and application of Digital Twins representing and supporting the working environment of a construction site. By combining available geodata with real-time sensor data from mobile construction machines, it is possible to create always-up-to-date Digital Twins of the relevant objects and processes in the field in order to facilitate supervision, additional planning steps, management, control and security activities. The proposed concept is currently being tested on a local test site to generate, update and adapt the Digital Twins as well as to incorporate additional semantic information about e.g. the soil and various working processes.
Analyzing Natural Resting Aspects of Arbitrary Components Using a Physics Engine
Authors: Kolditz Torge , Hentschel Jakob , Raatz Annika 
Published: July 2023

AbstractPart Feeding Systems play a vital role in automated assembly, linking in-house logistics with individual assembly stations. One of the main tasks of part feeding systems is to transfer components from a disordered state (e.g. bulk material) to an ordered state (defined position and orientation) so that they can be further processed by automated handling equipment. Knowledge of the natural resting aspects (probability that a geometrical body rests in a certain orientation) of the components is essential for the development and design of part feeding systems. The experimental determination of natural resting aspects is time consuming and expensive since extensive drop tests have to be carried out. Therefore, many approaches have been taken to derive the natural resting aspects mathematically based on the component geometry or by direct dynamic simulation. In this work, the open-source physics engine Blender is used to determine natural resting aspects of arbitrary components without the need for experimental drop tests. In virtual drop tests, components are imported in the common STL format and are dropped on a surface from random initial orientations. The resting orientations of the components are exported and automatically evaluated using MATLAB. The functionality and accuracy of the approach is evaluated by conducting experimental drop tests with five exemplary components. The evaluation shows good agreement between simulated and experimental results.
Investigation and Compensation of Hysteresis in Robot Joints with Cycloidal Drives
Authors: Mesmer Patrick , Riedel Patrick , Lechler Armin , Verl Alexander 
Published: July 2023

AbstractImproving the dynamic path accuracy has been a major research topic in industrial robotics for decades. It is known that the drivetrains installed in the robot joints limit further improvements. There is a lot more literature on the dynamic behavior of harmonic drives (HDs) than for cycloidal drives (CDs), that are usually installed in industrial robots (IRs) with heavy payload. However, a more profound knowledge of the occurring effects offers the potential for both, design- and control-based enhancements. Therefore, this paper presents an experimental study of the friction and hysteresis behavior with explicit consideration of further dependencies, such as temperature and load. Based on these investigations, a model as well as a control-based compensation approach, that does not require additional gearbox output sensors, is proposed. The investigation and validation are carried out with an experimental setup equivalent to the drivetrain of an IR with heavy payload.
Generalized Model for the Optimization of a LIFO Topology Storage Using a Metaheuristic Algorithm
Authors: Kuhn Dominik , Adelsbach Jan , Karkowski Martin , Müller Rainer 
Published: July 2023

AbstractLIFO topologies, due to their simplicity and high degree of space usage efficiency are common in applications for which a flexible and cost effective storage solution is required. This topology however represent an optimization challenge due to insertion and removal constraints. A scalable generalized model for the optimization of this topology using a population based metaheuristic algorithm is presented in this paper. The model to represent this storage topology, in a way suitable for population based metaheuristics and the implementation thereof are being discussed. It is being validated using practical usage scenarios from logistics and assembly such as non-stacking condensed pallet storage.
Digital Geometry Recording for Automation of the One-Off Production of Pipes
Authors: Biltgen Jacques , Lauer Sascha , Wanner Martin-Christoph , Flügge Wilko 
Published: July 2023

AbstractThe manual production in pipeline construction is often related to the fact that either the capacities for automation are lacking or the production is too individual for a simple automation solution. However, automated production would increase productivity and quality, especially in metal processing. The challenge in the manufacturing process of fitting tubes is the batch sizes of one. Nevertheless, a non-time-consuming programming solution must be found to integrate a robot-based solution economically into the production chain. Offline path planning based on CAD models would be a suitable solution. To ensure that the robot-welded seams comply with the standards, there has to be consistent quality in the seam preparations. For the final quality the direct integration of the CAD flow would be important. Due to transport and limited space, it is often impossible to use sensors to scan the piping. In case of lacking technical documentation, the pipes are still measured by hand, especially when replacing or modifying pipelines.The geometry survey is done in several steps, first a rough drawing is made on the vessel, this is then converted into a technical sketch and only later transferred to a CAD programme. There can be several days between these steps and different operators. A method will now be presented to combine these steps with the support of a tablet. For this purpose, software is used on the tablet to digitise the geometries and prepare them for further offline path planning.
Detection and Handling of Dynamic Scenes During an Active Vision Process for Object Recognition Using a Boundary Representation
Authors: Rohner Dorian , Hartwig Johannes , Henrich Dominik 
Published: July 2023

AbstractFor robot manipulators, it is nowadays necessary to know their surroundings. This knowledge consists at least of a world representation with recognized objects. During the reconstruction of scene objects from multiple views, changes, like positioning of the objects, or additional unwanted signals, like parts of a human co-worker, may occur. In this paper, we classify the possible changes for a specific type of representation (boundary representation models). Afterwards, we present an approach to detect and handle these changes to maintain a valid world model. To achieve this, we compare what should be visible in the world model reconstructed thus far with the actual information from the current view. The detected change is handled by using object hypotheses as well as geometric information from the world representation. Based on an evaluation, we show a proof of concept and the usefulness of our approach and suggest future work.
Flow Modeling for Vacuum Pressure-Based Handling of Porous Electrodes of Lithium-Ion Batteries
Authors: Schimanek Robert , Aydemir Muhammed , Müller Alexander , Dietrich Franz 
Published: July 2023

AbstractIn lithium-ion battery (LIB) production, limp electrodes are handled gently by vacuum-pressure based handling and transport systems, which generate a fluid flow that propagates through the porous electrode coating during handling. To investigate the limits and material-damaging behavior of vacuum pressure-based handling, it is required to understand how process parameters and electrode qualities affect fluid flow. Questions on how fluid flow reduces electrode quality are insufficiently addressed or modeled. Modeling the electrode and handling system interaction requires knowledge of the effective surface geometry and the volumetric flow rate caused by the pressure difference. In this article, flow through porous electrode coatings during handling is modeled. Experiments demonstrate a flow behavior according to the generalized Darcy’s law. Thus, using Darcy’s law, modeling fluid flow through the electrode improves the exploration of the limits and design of vacuum pressure-based handling and transport of electrodes in LIB production.
Integration of an IoT Communication Infrastructure in Distributed Production Systems in Industry 4.0
Authors: Chen Jiahang , Roßmann Jürgen 
Published: July 2023

AbstractThe term Internet of Things (IoT) denotes a communication network, where various Things are interconnected using novel scenario-specific Internet technologies and predefined customizable semantics. Industry 4.0 aims at enabling a globally networked production, with the use of IoT as a crucial concept. Since production systems tend to be technically and organizationally heterogeneous, distributed at different locations, and associated with large amounts of data, communication and information processing platforms that provide confidentiality, integrity, availability (CIA rules), access control, and privacy are needed. In this contribution, we introduce a concept for designing and operating heterogeneous and spatially distributed industrial systems with Digital Twins, connected via an IoT communication infrastructure, the Smart Systems Service Infrastructure (S3I). By demonstrating an industrial use case with our concept, it is proven that the S3I can be used as a cross-domain solution for the interconnection of devices in a distributed production scenario.
Ontology-Based Task Allocation for Heterogeneous Resources in Line-Less Mobile Assembly Systems
Authors: Kluge-Wilkes Aline , Gunaseelan Balaji , Schmitt Robert H. 
Published: July 2023

AbstractVolatile markets and production request for assembly systems adaptable to changes of product types, production capacity, and product order. Computer-aided decision support systems facilitate scheduling, planning, and controlling adaptive and flexible assembly systems. Formal description models of resources and their capabilities, assembly tasks and their requirements are necessary for automated decision-making. This paper contributes a conceptual CAPabILity-based resource AllocatioN Ontology (CAPILANO). The ontology is tailored as a uniform description of heterogeneous assembly resources and their (combined) capabilities, connected to a capability-based task allocation approach. The intended application of the resulting framework is the identification of suitable assembly resources in Line-less Mobile Assembly Systems (LMAS) and their allocation to assembly tasks, based on a unified and formal description. To date, ontologies in assembly have been limited to querying resources and their capabilities; here, subsequent task allocation is presented as an integral component of a tailored framework. The resulting framework consists of a model of heterogeneous resources and their capabilities in an ontology created in Protégé in OWL, SPARQL-based querying, and a consecutive and availability-aware task allocation in Python. The development of the ontology-based task allocation framework, including ontology taxonomy, querying and task allocation, is discussed. Its applicability in LMAS is demonstrated through linear scalability of task allocation and future advances are discussed.
Usability of Augmented Reality Assisted Commissioning of Industrial Robot Programs
Authors: Wulff Lukas Antonio , Brand Michael , Schüppstuhl Thorsten 
Published: July 2023

AbstractThis paper analyses the usability of Augmented Reality (AR) in the commissioning and programming of industrial robots. Conducting two individual studies with a total of 31 participants we analysed the three dimensions of usability: effectiveness, efficiency, and user satisfaction by comparing our developed AR system with the conventional Teach-In programming method during the commissioning and modification of offline created robot programs. The results indicate that, while less accurate and hence effective, the AR system is more efficient and has a higher user satisfaction. Beyond that a posture analysis indicates that during a timeframe of 30 min the additional weight of the AR device does not significantly worsen the posture of a worker. Complemented by the positive result of the System Usability Score (SUS) that rates the analysed AR system with a good usability, the overall results indicate that while still limited by its achievable accuracy AR is an intuitive medium to conduct robot programming and commissioning.
Discrete Filter and Non-Gaussian Noise for Fast Roughness Simulations with Gaussian Processes
Authors: Jawaid A. , Seewig J. 
Published: July 2023

AbstractRough surface simulations result in tight feedback loops in research procedures, such that they speed up studies for example about roughness’ impact on tribology or fluid dynamics. To model and simulate a broad spectrum of rough surfaces, Gaussian processes (GP) have been suggested recently. However, these models are limited on surfaces with small sizes since computational time-costs and memory-costs of simulations with standard procedures scale cubically and quadratically, respectively. In this paper, we apply the discrete filter approach which is a special case of GPs. We use the discrete filter with the fast Fourier transform (FFT) algorithm to efficiently sample from a high-dimensional Gaussian distribution and we compare its computational costs with the contour integral quadrature algorithm. Our experiments show that GPs benefit from FFT and allow stationary rough surfaces with sizes as large as 30, 000 × 30, 000 to be efficiently sampled. Since this approach is complementary to the GP and noise model approach, we also show simulations of rough surfaces with underlying non-Gaussian noise models that can reduce computational complexity.
Framework to Improve the Energy Performance During Design for Additive Manufacturing
Authors: Yi L. , Wu X. , Glatt M. , Ravani B. , Aurich J. C. 
Published: July 2023

AbstractAdditive manufacturing (AM) is suitable for designing and producing complex components that are difficult or impossible to manufacture with conventional manufacturing processes. To ensure the design benefits of AM, novel design approaches such as structural topology optimization and cellular structure design are widely used and bring up the research domain of design for AM (DfAM). However, conventional DfAM approaches mainly focus on the geometry and manufacturability of AM components and rarely consider energy performance as an improvement objective. Given that the energy consumption in AM processes can be a great contributor to the overall environmental impact in the production stage with AM, the evaluation and improvement of the energy performance of AM should be considered in the DfAM approaches; otherwise, opportunities to improve the energy performance by changing product features are missed. To address this research question, we are proposing a framework that enables the evaluation and improvement of the energy performance of AM in the design stage resulting in a new method for DfAM. To validate the framework, two use cases are presented to illustrate the feasibility of developed methods and tools.
Investigation of Micro Grinding via Kinematic Simulations
Authors: Altherr N. , Kirsch B. , Aurich J. C. 
Published: July 2023

AbstractWith increasing demand for micro structured surfaces in hard and brittle materials, the importance of micro grinding increases. The application of micro pencil grinding tools (MPGTs) in combination with ultra precision multi axes machine tools allow an increased freedom of shaping. However, small dimensions of the grinding tools below 500 µm substantiate high rotational speeds and low feed rates to enable the machining process. Besides, the abrasive grits of the tool can be large in comparison to the tool dimensions. All factors will influence the resulting surface topography of the workpiece. But some of the topography properties are no longer accessible for optical measurements, making process evaluations and improvements difficult.In the present contribution the measurement results are supplemented by the results of a kinematic simulation model. The built up of such a kinematic simulation is described, which considers real process and tool properties. The results received by the simulation are compared to measurements to validate the model and point out the advantages of the simulations. In a further step, a principle is shown how the simulation can be used to make the undeformed chip thickness accessible, a process result which cannot be measured within the real machining process.
Visual Analysis and Anomaly Detection of Material Flow in Manufacturing
Authors: Kinner E. , Glatt M. , Aurich J. C. , Garth C. 
Published: July 2023

AbstractThe automated tracking of objects in factories via real-time locating systems (RTLS) is gaining increased attention due to its improved availability, technical sophistication, and most of all, its plethora of applications. The tracking of workpieces through their production process, for example, unlocks a detailed understanding of timings, patterns, and bottlenecks. While research mostly focuses on technological advancements, the analysis of the generated data is often left unclear. We propose a visual analysis framework based on ultra-wide-band (UWB) RTLS tracking data of material flow for this purpose. With this, we present an analysis and define a practical approach for how factory-level data can be analyzed. Advanced algorithms adapted from non-adjacent research domains are used to process and detect anomalies in the data, which would otherwise be hidden behind oversimplified analysis methods. Our approach considers different levels of granularity for the analysis in its visualization and, therefore, scales with increasing data sizes effortlessly. We also generated a ground truth dataset of RTLS UWB data with labeled anomaly cases. Combined, we provide a full, end-to-end, efficient processing and multi-visualization analysis pipeline for self-contained yet generalizable UWB RTLS data.
Embedding-Space Explanations of Learned Mixture Behavior
Authors: Sohns J.-T. , Gond D. , Jirasek F. , Hasse H. , Weber G. H. , Leitte H. 
Published: July 2023

AbstractData-driven machine learning (ML) models are attracting increasing interest in chemical engineering and already partly outperform traditional physical simulations. Previous work in this field has mainly focused on improving the models’ statistical performance while the thereby imparted knowledge has been taken for granted. However, also the structures learned by the model during the training are fascinating yet non-trivial to assess as they are usually high-dimensional. As such, the interpretable communication of the relationship between the learned model and domain knowledge is vital for its evaluation by applying engineers. Specifically, visual analytics enables the interactive exploration of data sets and can thus reveal structures in otherwise too large-scale or too complex data. This chapter focuses on the thermodynamic modeling of mixtures of substances using the so-called activity coefficients as exemplary measures. We present and apply two visualization techniques that enable analyzing high-dimensional learned substance descriptors compared to chemical domain knowledge. We found explanations regarding chemical classes for most of the learned descriptor structures and striking correlations with physicochemical properties.
Vorgehensweise
Authors: Schlander Michael , Schäfer Ramon , Selberg Lorenz 
Published: July 2023

ZusammenfassungIn Kap. 3 wird der gewählte Zugang zum Thema skizziert, beginnend mit einer Beschreibung des Umfangs des Gegenstands „Laboratoriumsmedizin“. Ausgehend von einer Analyse der Krankheitslast der Bevölkerung wurde eine thematische Eingrenzung in der Weise vorgenommen, dass für diejenigen Krankheitsgebiete, die als wichtigste Verursacher von Morbidität und Mortalität in der Schweiz hervortreten, jeweils mindestens ein labormedizinisches Testverfahren ausgewählt und auf seinen Nutzen untersucht wurde. Dieser Abschnitt wird unterstützt von einer Beschreibung der Messung von Krankheitslast (oder „Burden of Disease“) mithilfe des Konstrukts der „Disability-Adjusted Life Years“ (DALYs).
Zukunftspotenziale der Labormedizin
Authors: Schlander Michael , Schäfer Ramon , Selberg Lorenz 
Published: July 2023

ZusammenfassungDas Kap. 5 gilt aktuellen wissenschaftlichen Entwicklungen und den sich daraus ergebenden vielversprechenden Chancen. Naturgemäss lässt sich deren Nutzen selbst bei erfolgreicher technischer Realisierung zum jetzigen Zeitpunkt noch nicht abschliessend beurteilen. Die bekannten Erfolgsrisiken, die mit der Durchführung medizinischer Forschungs- und Entwicklungsprojekte verknüpft sind, legen nahe, dass sich nicht alle mit ihnen verbundenen Hoffnungen erfüllen werden.