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Inhaltsverzeichnis:
I. Lern- und Arbeitstechniken im 1. und im 10. Semester
II. Lern- und Arbeitstechniken als persönliches Selbstmanagement
III. Diskussionsfragen und -thesen
IV. Was heißt: Eigenverantwortung im Studium?
V. Eigenverantwortung als gelebte Freiheit von Studierenden
VI. Warum es unmöglich ist, Verantwortung an Studierende zu delegieren VII. Erziehungsauftrag: Studierende in ihrer Eigenverantwortung belassen VIII. Folgerungen für Lehrende IX. Folgerungen für Studierende
Plasma-Auftragschweißen mit Wolframschmelzkarbid-haltigen Metallpulvern und ihre Einsatzgebiete
(1996)
Peyre, Marie-Josephe
(2017)
Peyre, Antoine-Francois
(2017)
Die urbane Mobilität ist im Wandel und insbesondere neue innovative Geschäftsmodelle werden einen wesentlichen Teil zur Lösung von künftigen Mobilitätsbedürfnissen beitragen. Die sogenannte „Shared Mobility“ gilt aktuell neben der Elektrifizierung des Antriebes und autonomem Fahrzeugtechnologien als einer der wichtigsten Trendthemen in der Automobilindustrie. Neue Mobilitätsdienstleistungen verlangen dabei verstärkt auch neue Fahrzeugkonzepte.
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.
Patte, Pierre
(2017)
Partikelmesstechnik
(2012)
Der Schutz von Produkten vor der Kontamination durch Partikel gilt als eine zentrale Aufgabe der Reinraumtechnik. Da es dabei um Kontaminationseffekte weit unterhalb der visuellen Wahrnehmbarkeit geht, braucht es leistungsfähige Verfahren, um die Messgröße „Partikelkontamination“ über den gesamten Bereich, den Anwender fordern, präzise zu bestimmen. Neben der Partikelhäufigkeit ist dabei die Größe der Partikel, die sowohl das Transportverhalten wie auch die mögliche Wirkung auf das Produkt beeinflusst, von entscheidender Bedeutung. Ferner kann es für die Ermittlung von Kontaminationsquellen von Interesse sein, die Form und die chemische Natur der Partikel zu bestimmen (z. B. textile Fasern, Metallabrieb, flüssige Tröpfchen). Die Partikelhäufigkeit wird üblicherweise als Konzentration, d. h. bezogen auf das analysierte Gasvolumen angegeben. Bei den in reinen Technologien üblichen niedrigen Konzentrationen dient als Häufigkeitsmaß die Partikelanzahlkonzentration, also die Partikelanzahl pro Volumeneinheit des Trägermediums.
It has been observed that carcinogenic polycyclic aromatic hydrocarbons (PAH) are present in the atmosphere. Combustion processes are considered the most important sources for PAH. Among these, the burning of coal produces the highest emission, but in cities with high traffic density and low meteorological exchange activities, vehicle emissions determine the immission situation, especially in narrow streets. For estimating the potential health effects caused by PAH, it is sufficient to characterize the emission of PAH with respect to their physical state, concentrations, and, as far as the particulate phase is concerned, size distribution. The size distribution is important for transport phenomena, inhalation, and deposition in the respiratory tract. These parameters mainly depend on the combustion system, on system operating conditions, on the exhaust system, and on exhaust cooling conditions. At exhaust-gas temperatures in the range of ambient air temperatures, almost the whole emission of PAH is made up of particulate matter.
Parasitäre Strategien
(2008)
Pandemische Momente
(2022)
Organizzare l’addizione
(2014)
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.