Erfassung dynamischer menschlicher Parameter in kollaborativen Arbeitsprozessen mit Augmented Reality

Der Begriff "Industrie 4.0" fasst Technologien und Methoden zusammen, mit denen Produktionssysteme sich durch eine systematische Erfassung und Analyse von Daten selbstständig steuern und optimieren können. Insbesondere dort, wo Tätigkeiten innerhalb des Produktionsprozesses von Menschen ausgeführt werden, entsteht die Herausforderung, dass für die Erfassung menschlicher Daten in der Regel eine komplexe technische Infrastruktur notwendig ist. Die vorliegende Arbeit befasst sich mit der Fragestellung, ob der Prozess, menschliche Daten zu erfassen, durch die Anwendung eines AR-Headsets vereinfacht werden kann und auf ortsfeste Infrastruktur verzichtet werden kann. Zur Überprüfung des Ansatzes wird eine AR-Anwendung entwickelt, die kontinuierlich die Position eines Arbeiters in der Produktionsanlage bestimmt. Grundlage hierfür ist das dauerhaft vom AR-Headset durchgeführte SLAM-Tracking in Verbindung mit einem optischen, markerbasierten Kalibrierungsverfahren. Im Rahmen einer Messreihe wird die Präzision der Positionsbestimmung überprüft und mit anderen Verfahren zur Lokalisierung in Innenräumen verglichen. Für die Analyse der Positionsdaten wird zusätzlich eine Serveranwendung entwickelt, welche die Positionsdaten empfängt, speichert und mit Hilfe einer vorher festgelegten Prozessbeschreibung automatisiert Prozesszeiten aus den ermittelten Positionsdaten berechnet. Anhand eines praktischen Anwendungsfalls wird aufgezeigt, wie die ermittelten Prozesszeiten genutzt werden können, um die Reihenfolge des Prozesses zu optimieren

How to Put Usability into Focus: Using Focus Groups to Evaluate the Usability of Interactive Theorem Provers

In recent years the effectiveness of interactive theorem provers has increased to an extent that the bottleneck in the interactive process shifted to efficiency: while in principle large and complex theorems are provable (effectiveness), it takes a lot of effort for the user interacting with the system (lack of efficiency). We conducted focus groups to evaluate the usability of Isabelle/HOL and the KeY system with two goals: (a) detect usability issues in the interaction between interactive theorem provers and their user, and (b) analyze how evaluation and survey methods commonly used in the area of human-computer interaction, such as focus groups and co-operative evaluation, are applicable to the specific field of interactive theorem proving (ITP). In this paper, we report on our experience using the evaluation method focus groups and how we adapted this method to ITP. We describe our results and conclusions mainly on the ``meta-level,'' i.e., we focus on the impact that specific characteristics of ITPs have on the setup and the results of focus groups. On the concrete level, we briefly summarise insights into the usability of the ITPs used in our case study

A collaborative knowledge-based method for the interactive development of cabin systems in virtual reality

Progressive digitization in the development phase of systems is leading to shorter development times and lower costs. At the same time, the interactions in more complex systems are increasing and become more nested, which affects the understanding of system dependencies for humans as well as modeling these. This results in the challenge of digitizing the knowledge (rules, regulations, requirements, etc.) required to describe the system and its interrelationships. An example of such a system is the aircraft. In practice, usually, the technical design of the cabin and its systems is done separately from the preliminary aircraft design and the cabin results will be integrated late in the aircraft development process. In this paper, a proposal is given for a conceptual design method that enables a cabin systems layout based on preliminary aircraft design data (parameter set). Therefore, a central data model is developed that links cabin components to several disciplines to enable an automated layout. Here, knowledge is stored in an ontology. Linking the ontology with design rules and importing external parameters, missing information needed for preliminary design of cabin systems can be generated. The design rules are based on requirements, safety regulations as well as expert knowledge for design interpretation that has been collected and formalized. Using the ontology, an XML data structure can be instantiated which contains all information about properties, system relationships and requirements. So, the metadata and results of heterogenous domain-specific models and software tools are accessible for all experts of the layout process in a holistic manner and ensure data consistency. Using this XML data structure, a 3D virtual cabin mockup is created in which users have the possibility to interact with cabin modules and system components via controllers. This virtual development platform enables an interaction with complex product data sets like the XML file by visualizing metadata and analysis results along with the cabin geometry, making it even better comprehensible and processable for humans. So, various new cabin system designs can be iterated, evaluated, and optimized at low cost before the concepts are validated in a real prototype. For this, the virtual environment provides a platform that integrates all related disciplines, experts, research partners or the entire supply chain to improve communication among all stakeholders by directly participating and intervening in the evaluation and optimization process. Moreover, the use of VR is being investigated as a new technology in pre-design phase to exploit the potential of knowledge acquisition in immersive environments early in the development stage

Virtual reconfiguration and assessment of aircraft cabins using model-based systems engineering

In order to create a detailed digital cabin, virtual models are combined with the geometric data of physical cabin components. This digital cabin can be used to analyse maintenance times, find optimization potential or test the integration of new technologies (e.g. hydrogen powered systems). This requires different levels of detail of the virtual cabin model as well as an automated data (e.g. 3D models, parameters) transfer infrastructure between them. However, this model structure is challenged by the complexity of the system to be mapped due to subsystems and interconnections. In addition, it requires an integration and preparation of the transmitted data (3D models, process data). This paper presents a method that addresses these challenges and introduces an architecture for building a virtual cabin for reconfiguration and analysis of new cabin variants. Model-based systems engineering is used to create a digital model of the aircraft cabin and its systems. The model is used for an automated reconfiguration of the cabin and consists of formalized knowledge and requirements. In addition, a 3D scan process is applied that digitizes the physical cabin subcomponents (e.g. riser duct) to increase the level of detail and to consider uncertainties. Subsequently, all data and models are visualized in a virtual reality environment in which users can interact with it and make direct changes to the layout. These changes are automatically transferred to the conceptual cabin design process for an automated reconfiguration and examination of the layout regarding the requirements. As a result, a baseline architecture for the digital cabin has been created, which enables fast system reconfigurability, traceability of changes, identification of interdependencies, and investigation of new cabin variations (retrofit)

Comparative genomics of Mycobacterium africanum Lineage 5 and Lineage 6 from Ghana suggests distinct ecological niches.

Mycobacterium africanum (Maf) causes a substantial proportion of human tuberculosis in some countries of West Africa, but little is known on this pathogen. We compared the genomes of 253 Maf clinical isolates from Ghana, including N = 175 Lineage 5 (L5) and N = 78 Lineage 6 (L6). We found that the genomic diversity of L6 was higher than in L5 despite the smaller sample size. Regulatory proteins appeared to evolve neutrally in L5 but under purifying selection in L6. Even though over 90% of the human T cell epitopes were conserved in both lineages, L6 showed a higher ratio of non-synonymous to synonymous single nucleotide variation in these epitopes overall compared to L5. Of the 10% human T cell epitopes that were variable, most carried mutations that were lineage-specific. Our findings indicate that Maf L5 and L6 differ in some of their population genomic characteristics, possibly reflecting different selection pressures linked to distinct ecological niches

Phylogenomics of Mycobacterium africanum reveals a new lineage and a complex evolutionary history.

Human tuberculosis (TB) is caused by members of the Mycobacterium tuberculosis complex (MTBC). The MTBC comprises several human-adapted lineages known as M. tuberculosis sensu stricto, as well as two lineages (L5 and L6) traditionally referred to as Mycobacterium africanum. Strains of L5 and L6 are largely limited to West Africa for reasons unknown, and little is known of their genomic diversity, phylogeography and evolution. Here, we analysed the genomes of 350 L5 and 320 L6 strains, isolated from patients from 21 African countries, plus 5 related genomes that had not been classified into any of the known MTBC lineages. Our population genomic and phylogeographical analyses showed that the unclassified genomes belonged to a new group that we propose to name MTBC lineage 9 (L9). While the most likely ancestral distribution of L9 was predicted to be East Africa, the most likely ancestral distribution for both L5 and L6 was the Eastern part of West Africa. Moreover, we found important differences between L5 and L6 strains with respect to their phylogeographical substructure and genetic diversity. Finally, we could not confirm the previous association of drug-resistance markers with lineage and sublineages. Instead, our results indicate that the association of drug resistance with lineage is most likely driven by sample bias or geography. In conclusion, our study sheds new light onto the genomic diversity and evolutionary history of M. africanum, and highlights the need to consider the particularities of each MTBC lineage for understanding the ecology and epidemiology of TB in Africa and globally