Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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How Pedestrians Perceive Autonomous Buses: Evaluating Visual Signals

2021 , Brandenburg, Elisabeth , Kozachek, Diana , Konkol, Kathrin , Woelfel, Christiane , Geiger, Andreas , Stark, Rainer

With the deployment of autonomous buses, sophisticated technological systems are entering our daily lives and their signals are becoming a crucial factor in human-machine interaction. The successful implementation of visual signals requires a well-researched human-centred design as a key component for the new transportation system. The autonomous vehicle we investigated in this study uses a variety of these: Icons, LED panels and text. We conducted a user study with 45 participants in a virtual reality environment in which four recurring communication scenarios between an autonomous driving bus and its potential passengers had to be correctly interpreted. For our four scenarios, efficiency and comprehension of each visual signal combination was measured to evaluate performance on different types of visual information. The results show that new visualization concepts such as LED panels lead to highly variable efficiency and comprehension, while text or icons were well ac cepted. In summary, the authors of this paper present the most efficient combinations of visual signals for four reality scenarios.

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Impact of Platform Openness on Ecosystems and Value Streams in Platform-Based PSS Exemplified Using RAMI 4.0

2020 , Zambetti, Michaela , Blüher, Till , Pezzotta, Giuditta , Exner, Konrad , Pinto, Robert , Stark, Rainer

With the digital revolution, the IoT (Internet of Things) platform approach emerges as a supportive way for the implementation of IoT platform-based Product-Service System (PSS) offerings. To exploit the full potential of the platform economy and considering the complexity of the multitude of different actors in all the lifecycle stages, value creation architectures for digital and service platforms are one of the critical points to develop. In this work, the concept of Platform-based PSS is presented, and for representation purposes, an extension of the RAMI 4.0 reference model has been proposed. Specifically, the ecosystem perspective has been added to RAMI 4.0, to approach Platform-based PSS with a multi-actor lens. Moreover, the different contributions and benefits of the main participants in Platform-based PSS are illustrated. Therefore, three different scenarios have been exemplified with the proposed RAMI 4.0 extension relating the actors' possibilities to contribute to Platform-based PSS to the level of openness of a platform.

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Modular virtual reality to enable efficient user studies for autonomous driving

2020 , Konkol, Kathrin , Brandenburg, Elisabeth , Stark, Rainer

Autonomous driving vehicles use a variety of means to communicate with pedestrians, e.g. information displays, LED panels and sound. In order to evaluate some of those information displays with regard to their efficiency of understanding, the authors examined a set of external information types, such as images, text and animated LED panels. The use of Virtual Reality to create user studies offers a flexible and cost-effective approach for evaluation and improvement, therefore the authors chose to develop the user study as a VR application. This paper describes the ongoing work in which the study is designed and the application has been implemented but the study has not yet been carried out. The emphasis on this paper lies on the approach of planning a modular VR application that fits the needs of a multifactorial experimental layout that can adapt to changes in the study for further evaluation.

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Qualitätskriterien für den Datenfluss im Advanced System Engineering

2019 , Müller, Helena , Riedelsheimer, Theresa , Lünnemann, Pascal , Blüher, Till , Stark, Rainer

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Interaction between capabilities of Model Based Systems Engineering on sensor models

2021 , Manoury, Marvin Michael , Schmidt, Simon , Stark, Rainer

In modern product development, models are often used for different purposes, e.g., system synthesis, trade-off analysis of system parameters or visualization and creation of design concepts. For some models, this purpose as well as the model itself might change over time. New interactions with the target system can occur and new details are added over time. Both have to be integrated immediately into the development procedure. When models are not maintained up to date and not used by different stakeholders, the benefits of the model-based approach are lessened due to the effort for generation and maintenance. The five development capabilities of MBSE, comprising Systems Environment Analytics (SEA), Systems Definition and Derivation (SDD), Systems Interaction Modeling (SIM), Systems Lifecycle Engineering (SLE) and the MBSE Capability and Maturation Matrix (CMM) address this topic on a capability level.In this article, the authors point out the interaction between these d evelopment capabilities on the example of a Pedestrian Emergency Braking System (PEBS) development in automotive industry, with a focus on sensor models. It will be shown exemplary how one development capability might influence another and how this interaction supports the development of complex systems.

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Potentials and challenges of Smart Products and related business models

2020 , Wang, Wei Min , Lünnemann, Pascal , Klemichen, Antje , Blüher, Till , Stark, Rainer

Smart products are increasingly penetrating the market. They extend cyber-physical systems with Internet-based services and thus enable customer-specific adaptations and updates of products in the field. For industrial companies, smart product offering bear the potential to expand their product portfolios and increase their sales. In this article, the results of a survey among German engineers are presented that evaluated the actual state of adoption and future expectations regarding smart products in German industrial companies. The results show that the majority of German companies have recognized the potentials of smart products and also introduced such offerings in their portfolio. In this context, it is also expected that the product-related usage data will lead to a more individual communication with the customer. On the other hand, there is a high degree of uncertainty among companies regarding the adaptation of new business models, cooperation with an increasing number of partners, data management and the necessary technological infrastructure. These uncertainties can result in companies leaving potentials unexploited and opening up opportunities for new market participants. In summary, there seems to be a remaining gap between the willingness to abandon traditional business models and the expectations and strategies for future value creation.

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Assembly Issue Resolution System Using Machine Learning in Aero Engine Manufacturing

2020 , Brünnhäußer, Jörg , Gogineni, Sonika , Nickel, Jonas , Witte, Heiko , Stark, Rainer

Companies are progressively gathering data within the digitalization of production processes. By actively using these production data sets operational processes can be improved, hence empowering businesses to compete with other corporations. One way to achieve this is to use data from production processes to develop and offer smart services that enable companies to continuously improve and to become more efficient. In this paper, the authors present an industrial use case of how machine learning can be implemented into smart services in production processes to decrease the time for resolving upcoming issues in manufacturing. The implementation is carried out by using an assistance system that aids a team which attends to problems in the assembling of turbines. Therefore, the authors have analyzed the assembly problems from an issue management system that the team had to resolve. Subsequently three different approaches based upon natural language processing, regression and clustering were selected. This paper also presents the development and evaluation of the assistance system.

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Validation of Immersive Design Parameters in Driving Simulation Environments

2021 , Lyga, Yvonne , Lau, Merle , Brandenburg, Elisabeth , Stark, Rainer

Driving simulators are used for the prospective validation of technical systems in the automotive sector. The design of simulation environments can affect drivers and should be considered in investigations of driver-vehicle interactions. The aim of this research is to minimize the gap between driving simulators and real car studies by integrating immersive parameters into simulated driving environments. Stereoscopy, surround sound and motion feedback were analyzed with regard to driver behavior and experience and were then compared to data of a real drive from a previous investigation. The authors conducted a study with N = 48 participants performing a dual-task scenario in a driving simulator. Results reveal significant effects of immersive design parameters on gaze behavior and mental workload. Findings provide guidance for an efficient and cost-effective development of driving simulation environments.

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Towards a Reference Model for Knowledge Driven Data Provision Processes

2020 , Wang, Wei Min , Preidel, Maurice , Fachbach, Bernd , Stark, Rainer

Value creation in most business areas takes place in networks that involve a wide range of stakeholders from various disciplines within and beyond company borders. Collaboration in such networks require the exchange of knowledge that is manifested in digital artefacts and consequently in data. As the utilization of that ""hidden"" knowledge has become increasingly important, the provision of relevant data in sufficient quality has also become crucial. This article proposes a reference model for knowledge driven data provision processes that is developed within a research project at the Virtual Vehicle Research GmbH for a future networked engineering environment. It describes a systematic process to drive operationalization of data provision from knowledge requirements to identify, extract and provide raw data until the application of such data sets. Still, the model in its current state is only applicable by descriptive means and needs further development and validation in practical use cases.

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Applying Contextualization for Data-Driven Transformation in Manufacturing

2020 , Gogineni, Sonika , Lindow, Kai , Nickel, Jonas , Stark, Rainer

Manufacturing is highly distributed and involves a multitude of heterogeneous information sources. In addition, Production systems are increasingly interconnected, hence leading to an increase in heterogeneous data sources. At present, data available from these new type of systems are growing faster than the ability to productively integrate them into engineering and production value chains of companies. Known applications such as predictive maintenance and manufacturing equipment management are currently being continuously optimized. While these applications are designed to help companies manage their manufacturing and engineering data, they only use a fraction of the total potential that can be realized by linking manufacturing and engineering data with other enterprise data. In the future, the context in which the data can be set will play an essential role. A meaningful added value in manufacturing can be achieved only with context specific data. Against this background, this paper presents three main areas of application for contextualizing data (semantics, sensitivity and visualization) and explains these applications with the help of a contextualization architecture. The concept is also evaluated using an industrial example. Furthermore, the paper describes the theoretical background of contextualization and its application in industry. The major challenges of the ability of engineers to adapt their activities and the integration of process knowledge for semantic linking are addressed as well.

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