Daniel Schoepflin

Daniel Schoepflin
Technische Universität Hamburg | TUHH · Institute of Aircraft Production Technology

Master of Science

About

9
Publications
3,984
Reads
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35
Citations

Publications

Publications (9)
Conference Paper
Structural components in fuselage barrels are joined with the help of riveting processes. Concerning the key feature of rivet drill hole size and drilling quality, a poorly executed drilling operation can lead to serious riveting defects such as rivet play or fracture due to non-uniform load distribution. Consequently, the drilling process of a riv...
Conference Paper
As actors in an IoT production environment, smart delivery units are tasked with identifying loaded components and acquiring shopfloor events such as consumption of material. Conventional identification procedures rely heavily on tags and markers that are applied on components. For processes that require marker-less identification procedures, AI-ba...
Chapter
Full-text available
Obtaining annotated data for proper training of AI image classifiers remains a challenge for successful deployment in industrial settings. As a promising alternative to handcrafted annotations, synthetic training data generation has grown in popularity. However, in most cases the pipelines used to generate this data are not of universal nature and...
Chapter
Full-text available
Machine vision solutions can perform within a wide range of applications and are commonly used to verify the operation of production systems. They offer the potential to automatically record assembly states and derive information, but simultaneously require a high effort of planning, configuration and implementation. This generally leads to an iter...
Article
Full-text available
Supervised machine learning methods are increasingly used for detecting defects in automated visual inspection systems. However, these methods require large quantities of annotated image data of the surface being inspected, including images of defective surfaces. In industrial contexts, it is difficult to collect the latter since acquiring sufficie...
Article
Full-text available
Despite significant advances in modeling of friction-induced vibrations and brake squeal, the majority of industrial research and design is still conducted experimentally, since many aspects of squeal and its mechanisms involved remain unknown. In practice, measurement data is available in large amounts. We report here for the first time on novel s...
Article
Full-text available
Despite recent advantages, internal logistics for aircraft production is mainly performed manually. Missing or wrongfully loaded components can cause costly delays. Transforming delivery units into smart participants of a digitalized logistic chain has the potential to avoid such delays. In the scope of this work, we present a concept of a smart de...
Article
Full-text available
With visual AI processes relying on individual and context accurate training data, the existing common object datasets and randomization based synthetic data pipelines can only hardly be transferred or applied on specific and narrow industrial tasks. To enable visual AI applications for intralogistics processes, such as supervision or localization...
Preprint
Full-text available
Despite significant advances in numerical modeling of brake squeal, the majority of industrial research and design is still conducted experimentally. In this work we report on novel strategies for handling data-intensive vibration testings and gaining better insights into brake system vibrations. To this end, we propose machine learning-based metho...

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Projects

Projects (6)
Project
Veröffentlichungen Flugzeugproduktion
Project
Veröffentlichungen Datenerfassung und –analyse
Project
Veröffentlichungen Künstliche Intelligenz (KI)