TY - CHAP A1 - Pütz, Sebastian A1 - Baier, Ralph A1 - Brauner, Philipp A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - Liehner, Luca A1 - Mertens, Alexander A1 - Rodemann, Niklas A1 - Schneider, Sebastian A1 - Schollemann, Alexander A1 - Steuer-Dankert, Linda A1 - Vervier, Luisa A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Nagel, Saskia K. A1 - Piller, Frank T. A1 - Schuh, Günther A1 - Ziefle, Martina A1 - Nitsch, Verena T1 - An interdisciplinary view on humane interfaces for digital shadows in the internet of production T2 - 2022 15th International Conference on Human System Interaction (HSI) N2 - Digital shadows play a central role for the next generation industrial internet, also known as Internet of Production (IoP). However, prior research has not considered systematically how human actors interact with digital shadows, shaping their potential for success. To address this research gap, we assembled an interdisciplinary team of authors from diverse areas of human-centered research to propose and discuss design and research recommendations for the implementation of industrial user interfaces for digital shadows, as they are currently conceptualized for the IoP. Based on the four use cases of decision support systems, knowledge sharing in global production networks, human-robot collaboration, and monitoring employee workload, we derive recommendations for interface design and enhancing workers’ capabilities. This analysis is extended by introducing requirements from the higher-level perspectives of governance and organization. KW - digital twin KW - digital shadow KW - cyber-physical production system KW - human-machine interface Y1 - 2022 SN - 978-1-6654-6823-7 (Print) SN - 978-1-6654-6822-0 (Online) U6 - http://dx.doi.org/10.1109/HSI55341.2022.9869467 SN - 2158-2246 (Print) SN - 2158-2254 (Online) N1 - 15th International Conference on Human System Interaction (HSI), 28-31 July 2022, Melbourne, Australia. PB - IEEE ER - TY - CHAP A1 - Hinke, Christian A1 - Vervier, Luisa A1 - Brauner, Philipp A1 - Schneider, Sebastian A1 - Steuer-Dankert, Linda A1 - Ziefle, Martina A1 - Leicht-Scholten, Carmen T1 - Capability configuration in next generation manufacturing T2 - Forecasting next generation manufacturing : digital shadows, human-machine collaboration, and data-driven business models N2 - Industrial production systems are facing radical change in multiple dimensions. This change is caused by technological developments and the digital transformation of production, as well as the call for political and social change to facilitate a transformation toward sustainability. These changes affect both the capabilities of production systems and companies and the design of higher education and educational programs. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these concepts, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the capabilities dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we discuss the benefits of capturing expert knowledge and making it accessible to newcomers, especially in highly specialized industries. The experts argue that in order to cope with the challenges and circumstances of today’s world, students must already during their education at university learn how to work with AI and other technologies. This means that study programs must change and that universities must adapt their structural aspects to meet the needs of the students. Y1 - 2022 SN - 978-3-031-07733-3 U6 - http://dx.doi.org/10.1007/978-3-031-07734-0_6 SP - 95 EP - 106 PB - Springer CY - Cham ER - TY - GEN A1 - Steuer-Dankert, Linda A1 - Bernhard, Sebastian A1 - Langolf, Jessica A1 - Leicht-Scholten, Carmen T1 - Managing change and acceptance of digitalization strategies - Implementing the vision of „Internet of Production“ (IoP) in existing corporate structures T2 - Textile Impulse für die Zukunft: Aachen-Dresden-Denkendorf International Textile Conference 2022 : 1. – 2. Dezember 2022, Eurogress Aachen N2 - The vision of the Internet of Production is to enable a new level of crossdomain collaboration by providing semantically adequate and context-aware data from production, development & usage in real-time. Y1 - 2022 SP - 153 EP - 153 ER - TY - CHAP A1 - Mertens, Alexander A1 - Brauner, Philipp A1 - Baier, Ralph A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - van Dyck, Marc A1 - Kong, Iris A1 - Königs, Peter A1 - Kordtomeikel, Frauke A1 - Liehner, Gian Luca A1 - Pütz, Sebastian A1 - Rodermann, Niklas A1 - Schaar, Anne Kathrin A1 - Steuer-Dankert, Linda A1 - Vervier, Luisa A1 - Wlecke, Shari A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Nagel, Saskia K. A1 - Piller, Frank T. A1 - Schuh, Günther A1 - Ziefle, Martina A1 - Nitsch, Verena ED - Michael, Judith ED - Pfeiffer, Jérôme ED - Wortmann, Andreas T1 - Modelling Human Factors in Cyber Physical Production Systems by the Integration of Human Digital Shadows T2 - Modellierung 2022 Satellite Events N2 - The future of industrial manufacturing and production will increasingly manifest in the form of cyber-physical production systems. Here, Digital Shadows will act as mediators between the physical and digital world to model and operationalize the interactions and relationships between different entities in production systems. Until now, the associated concepts have been primarily pursued and implemented from a technocentric perspective, in which human actors play a subordinate role, if they are considered at all. This paper outlines an anthropocentric approach that explicitly considers the characteristics, behavior, and traits and states of human actors in socio-technical production systems. For this purpose, we discuss the potentials and the expected challenges and threats of creating and using Human Digital Shadows in production. KW - human digital shadow KW - cyber physical production system KW - human factors Y1 - 2022 U6 - http://dx.doi.org/10.18420/modellierung2022ws-018 SP - 147 EP - 149 PB - GI Gesellschaft für Informatik CY - Bonn ER - TY - CHAP A1 - Brauner, Philipp A1 - Vervier, Luisa A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - Steuer-Dankert, Linda A1 - Schneider, Sebastian A1 - Baier, Ralph A1 - Ziefle, Martina A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Mertens, Alexander A1 - Nagel, Saskia K. T1 - Organization Routines in Next Generation Manufacturing T2 - Forecasting Next Generation Manufacturing N2 - Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030. Y1 - 2022 SN - 978-3-031-07734-0 U6 - http://dx.doi.org/10.1007/978-3-031-07734-0_5 SP - 75 EP - 94 PB - Springer CY - Cham ER - TY - CHAP A1 - Steuer-Dankert, Linda A1 - Leicht-Scholten, Carmen T1 - Perceiving diversity : an explorative approach in a complex research organization. T2 - Diversity and discrimination in research organizations N2 - Diversity management is seen as a decisive factor for ensuring the development of socially responsible innovations (Beacham and Shambaugh, 2011; Sonntag, 2014; López, 2015; Uebernickel et al., 2015). However, many diversity management approaches fail due to a one-sided consideration of diversity (Thomas and Ely, 2019) and a lacking linkage between the prevailing organizational culture and the perception of diversity in the respective organization. Reflecting the importance of diverse perspectives, research institutions have a special responsibility to actively deal with diversity, as they are publicly funded institutions that drive socially relevant development and educate future generations of developers, leaders and decision-makers. Nevertheless, only a few studies have so far dealt with the influence of the special framework conditions of the science system on diversity management. Focusing on the interdependency of the organizational culture and diversity management especially in a university research environment, this chapter aims in a first step to provide a theoretical perspective on the framework conditions of a complex research organization in Germany in order to understand the system-specific factors influencing diversity management. In a second step, an exploratory cluster analysis is presented, investigating the perception of diversity and possible influencing factors moderating this perception in a scientific organization. Combining both steps, the results show specific mechanisms and structures of the university research environment that have an impact on diversity management and rigidify structural barriers preventing an increase of diversity. The quantitative study also points out that the management level takes on a special role model function in the scientific system and thus has an influence on the perception of diversity. Consequently, when developing diversity management approaches in research organizations, it is necessary to consider the top-down direction of action, the special nature of organizational structures in the university research environment as well as the special role of the professorial level as role model for the scientific staff. KW - Diversity management KW - Organizational culture KW - Change management KW - Psychological concepts KW - Perception Y1 - 2022 SN - 978-1-80117-959-1 (Print) SN - 978-1-80117-956-0 (Online) U6 - http://dx.doi.org/10.1108/978-1-80117-956-020221010 SP - 365 EP - 392 PB - Emerald Publishing Limited CY - Bingley ER -