TY - GEN A1 - Schmitt, Randolf A1 - Borck, Christian A1 - Behm, Martin A1 - Böhnke, Jacob T1 - Approach of an asset combination based on RAMI4.0 for the digital transformation and operation of a Digital Twin T2 - Procedia CIRP Y1 - 2024 U6 - https://doi.org/10.1016/j.procir.2024.10.155 SN - 2212-8271 VL - 130 SP - 724 EP - 729 PB - Elsevier BV ER - TY - JOUR A1 - Bartsch, Devis A1 - Borck, Christian A1 - Behm, Martin A1 - Böhnke, Jacob T1 - Development of a Multi-layered Quality Assurance Framework for Manual Assembly Processes in the Aviation Industry JF - Procedia CIRP Y1 - 2024 U6 - https://doi.org/10.1016/j.procir.2024.10.232 SN - 2212-8271 VL - 130 SP - 1227 EP - 1233 PB - Elsevier BV ER - TY - GEN A1 - Baier, Daniel A1 - Vökler, Sascha T1 - One-stage product-line design heuristics: an empirical comparison T2 - OR Spectrum N2 - Selecting or adjusting attribute-levels (e.g. components, equipments, flavors, ingredients, prices, tastes) for multiple new and/or status quo products is an important task for a focal firm in a dynamic market. Usually, the goal is to maximize expected overall buyers’ welfare based on consumers’ partworths or expected revenue, market share, and profit under given assumptions. However, in general, these so-called product-line design problems cannot be solved exactly in acceptable computing time. Therefore, heuristics have been proposed: Two-stage heuristics select promising candidates for single products and evaluate sets of them as product-lines. One-stage heuristics directly search for multiple attribute-level combinations. In this paper, Ant Colony Optimization, Genetic Algorithms, Particle Swarm Optimization, Simulated Annealing and, firstly, Cluster-based Genetic Algorithm and Max-Min Ant Systems are applied to 78 small- to large-size product-line design problem instances. In contrast to former comparisons, data is generated according to a large sample of commercial conjoint analysis applications ( n = 2,089). The results are promising: The firstly applied heuristics outperform the established ones. KW - Product-line design KW - Conjoint analysis KW - Combinatorial optimization KW - Heuristics Y1 - 2024 U6 - https://doi.org/10.1007/s00291-023-00716-0 SN - 0171-6468 SN - 1436-6304 VL - 46 IS - 1 SP - 73 EP - 107 PB - Springer Berlin Heidelberg ER - TY - GEN A1 - Walter, Elias Fabian A1 - Günther, Norman A1 - Prell, Bastian A1 - Wilbers, Simon A1 - Reiter, Philipp A1 - Reiff-Stephan, Jörg A1 - Berger, Ulrich T1 - Optimierung visueller Benutzeroberflächen zur Stressreduzierung T2 - Tagungsband AALE 2023 N2 - Durch die Menschzentrierung in der Industrie 5.0 [1] sollten bestehende Ansätze hinterfragt und geprüft werden [2]. Gerade der, durch die Digitalisierung hervorgerufene, Technostress sollte neben dem Fachkräftemangel einen zunehmenden Betrachtungsfaktor im Produktionsumfeld erhalten. Da trotz bisheriger Maßnahmen eine stetige Zunahme von Stress zu verzeichnen ist [3]. Auffällig sind dabei die Arbeitsunfähigkeits-Fehltage, welche im letzten Jahr um weitere 6 % bzw. um 18,2 Fehltagegestiegen sind. Womit durchschnittlich jede Erwerbsperson 3,17 Tage unter der Diagnose „psychische Störung“ krankgeschrieben wurde [4]. Um diesen Trend entgegenzuwirken, betrachtet der Beitrag die Möglichkeiten der Software-Ergonomie, womit die Gestaltung von HMIs (Mensch-Maschinen-Interfaces) den Menschen gezielter berücksichtigt um etwaige Belastungen zu reduzieren [5]. Im Rahmen der komplementären Industrie 4.0 und der einhergehenden Informationsflut, bestimmen immer komplexer werdende Schnittstellen und Bedienoberflächen einen Großteil des Arbeitsalltags. Diese ermöglichen den Anwenderinnen und Anwendern neben einem schnellen Überblick über Maschinendaten, Prozessabläufe und Handlungsempfehlungen die Möglichkeit zur einfachen Bedienung der technischen Anlagen. Der hier vorgestellte Ansatz betrachtet am Beispiel einer Bestandsanlage, wo sich Potenziale in der Stressreduzierung im Bereich der visuellen Benutzerschnittstellen befinden und welche Auswirkungen eine Veränderung der Leitführung ermöglicht. Hierfür wurde eine mehrphasige Studie durchgeführt dessen Ergebnisse im Bereich des Eye-Trackings sowie anhand von Vitalwerten im vorliegenden Beitrag diskutiert werden. Y1 - 2023 SN - 978-3-910103-01-6 U6 - https://doi.org/10.33968/2023.13 SP - 119 EP - 129 PB - Hochschule für Technik, Wirtschaft und Kultur Leipzig CY - Luxemburg ER - TY - GEN A1 - Gebauer, Marc A1 - Tangour, Cyrine T1 - Resilience to Pandemics through Flexibility in Sourcing, in Order Fulfillment and in Production Capacity of the Automotive Supply Chain T2 - Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains KW - Resilience KW - Supply Chain KW - Automotive Y1 - 2023 SN - 978-3-031-27932-4 SN - 978-3-031-27933-1 U6 - https://doi.org/10.1007/978-3-031-27933-1_34 PB - Springer Cham ER - TY - CHAP A1 - Porsch, Ronny A1 - Lehmann, Marlon Antonin T1 - Evaluation of Marker-Based AR-Tracking with Vuforia in the Context of Rail Vehicle Maintenance T2 - Advances in Information and Communication - Proceedings of the 2023 Future of Information and Communication Conference (FICC) N2 - Maintenance and repair jobs present a multitude of challenges. Digital assistance systems (DAS) can be used to support workers in tackling these challenges. One way of achieving this is by using a tablet with AR-technology to display necessary information seemingly in the real world. In order to place information at the correct positions, the DAS needs to know exactly where it is currently located. Multiple approaches are available to achieve this. One of those approaches is to use a marker which is placed somewhere in the real world as an anchor point for the system. In the context of rail vehicle maintenance, the workspace is inherently large with rail wagons having lengths of more than 10 m. This means that a marker that is placed somewhere on the wagon will not always be in the field of view of the DAS’s camera, resulting in a possible reduction of the precision with which virtual objects can be displayed. This paper examines the viability of the marker-based approach under realistic circumstances. It was found that with a distance of multiple meters between marker and a spot that is to be highlighted, the precision will decrease significantly. Y1 - 2023 SN - 978-3-031-28076-4 SN - 978-3-031-28075-7 U6 - https://doi.org/10.1007/978-3-031-28076-4_7 SN - 2367-3370 SN - 2367-3389 SP - 65 EP - 71 PB - Springer, Cham CY - San Francisco, CA, USA ER - TY - GEN A1 - Assafo, Maryam A1 - Städter, Jost Philipp A1 - Meisel, Tenia A1 - Langendörfer, Peter T1 - On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application for Tool Condition Monitoring in Milling T2 - Sensors N2 - Feature selection (FS) represents an essential step for many machine learning-based predictive maintenance (PdM) applications, including various industrial processes, components, and monitoring tasks. The selected features not only serve as inputs to the learning models but also can influence further decisions and analysis, e.g., sensor selection and understandability of the PdM system. Hence, before deploying the PdM system, it is crucial to examine the reproducibility and robustness of the selected features under variations in the input data. This is particularly critical for real-world datasets with a low sample-to-dimension ratio (SDR). However, to the best of our knowledge, stability of the FS methods under data variations has not been considered yet in the field of PdM. This paper addresses this issue with an application to tool condition monitoring in milling, where classifiers based on support vector machines and random forest were employed. We used a five-fold cross-validation to evaluate three popular filter-based FS methods, namely Fisher score, minimum redundancy maximum relevance (mRMR), and ReliefF, in terms of both stability and macro-F1. Further, for each method, we investigated the impact of the homogeneous FS ensemble on both performance indicators. To gain broad insights, we used four (2:2) milling datasets obtained from our experiments and NASA’s repository, which differ in the operating conditions, sensors, SDR, number of classes, etc. For each dataset, the study was conducted for two individual sensors and their fusion. Among the conclusions: (1) Different FS methods can yield comparable macro-F1 yet considerably different FS stability values. (2) Fisher score (single and/or ensemble) is superior in most of the cases. (3) mRMR’s stability is overall the lowest, the most variable over different settings (e.g., sensor(s), subset cardinality), and the one that benefits the most from the ensemble. KW - classification KW - feature selection KW - homogeneous feature selection ensemble KW - predictive maintenance KW - milling KW - sensor fusion KW - stability of feature selection KW - tool condition monitoring Y1 - 2023 U6 - https://doi.org/10.3390/s23094461 SN - 1424-8220 VL - 23 IS - 9 ER - TY - GEN A1 - Bilous, Vadym A1 - Sarachuk, Kirill T1 - Are SMEs Ready for AI Embedded Mobile Robots? T2 - Human Interaction and Emerging Technologies N2 - The introduction of both mobile robots (MR) and AI-embedded mobile robots (AIMR) into the industry is very slow compared to other types of industrial robots (IR) and automation systems. Many scientific articles and studies are focused on the programming and design of MR. At the same time, integration issues, topical problems and related obstacles are almost entirely absent from the scientific literature. The authors of this paper acknowledge that the complete analysis of this area is a very challenging task. Therefore, for the purposes of this study, we focus on the local problem of analysing the introduction of MR and AIMR in small and medium-sized enterprises (SMEs). The authors offer the analysis of the current challenges and trends in the introduction of mobile robots into SMEs. They also propose solutions to these problems based on their own as well as external experience in the design, programming and implementation of mobile robots. Y1 - 2023 UR - https://openaccess.cms-conferences.org/publications/book/978-1-958651-87-2/article/978-1-958651-87-2_32 U6 - https://doi.org/10.54941/ahfe1004035 VL - 111 / 2023 SP - 285 EP - 296 PB - IHIET 2023 ER - TY - GEN A1 - Bilous, Vadym A1 - Sarachuk, Kirill T1 - Can small and medium enterprises benefit from AR technology? Current challenges and trends T2 - Human Interaction & Emerging Technologies N2 - Albeit augmented reality (AR) technologies first have been discovered in the third quarter of the 20th century, their widespread use began just two decades ago. Existing paper trails show that AR has a wide range of industrial application: it simplifies human-machine communication, improves human-machine interfaces (HMI) for quick information exchange in training (including feedback to study the workflow), correction of errors, machine maintenance, assembly assistance etc. However, broader industrial acceptance of AR, prior to all by small and medium-sized enterprises (SMEs), recently faced considerable problems and the expansion of AR solutions does not match the high potential it has demonstrated. That results in a limited practical use, mainly for demonstration and advertising purposes. This short review is to present the state of the art of the industry, challenges that SMEs face in adopting AR technologies, and several practical examples of a (commercial) adoption of AR. Some prospects for further development of AR and its ongoing integration into industry are briefly discussed in the summary. Y1 - 2023 UR - https://openaccess.cms-conferences.org/publications/book/978-1-958651-87-2/article/978-1-958651-87-2_37 U6 - https://doi.org/10.54941/ahfe1004040 VL - 111 / 2023 SP - 333 EP - 348 PB - IHIET 2023 ER - TY - CHAP A1 - Bilous, Vadym A1 - Städter, Philipp A1 - Gebauer, Marc A1 - Berger, Ulrich ED - Schüppstuhl, Thorsten ED - Tracht, Kirsten ED - Raatz, Annika T1 - Usage of Augmented Reality for Improved Human-Machine Interaction and Real-Time Error Correction of Laboratory Units T2 - Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021 KW - Augmented reality KW - Error correction KW - Human-machine interaction KW - Industry 4.0 KW - Technical assistance systems KW - Data transfer Y1 - 2022 SN - 978-3-030-74031-3 U6 - https://doi.org/10.1007/978-3-030-74032-0_22 SP - 263 EP - 274 PB - Springer CY - Cham ER -