The working environment is constantly changing and companies face the challenge of adapting to new and constantly changing customer requirements. Employees are faced with the challenge of identifying and learning new, helpful technologies and using them in order to achieve efficiency gains and increase productivity. This article addresses the three technologies Artificial Intelligence, Robotic Process Automation and Virtual Reality, which will play an important role in the future of work and will influence the Work Environment 4.0. Artificial Intelligence and Robotic Process Automation relieve employees of repetitive and manual tasks which thus accelerate and simplify business processes. Virtual Reality offers employees new opportunities to collaborate in virtual environments. Instead of performing routine tasks, employees will increasingly promote the use of such technologies in future and orchestrate their application. In addition, it is important for employees to continuously look for new use cases within their own organization and to collaborate with external partners. The article aims to describe the opportunities that arise from the application of the technologies and to explain their effects on the Work Environment 4.0 and the employee.

Der Trend zu mehr sozialem Wohlbefinden im Einklang mit der Wohlstandssteigerung und die verstärkte Rolle der sozialen Vernetzung birgt deutlich die Anzeichen einer tiefgreifenden gesellschaftlichen Veränderung. Dabei handelt es sich nicht mehr nur darum, die Weltwirtschaft für die großen Herausforderungen zu stärken. Menschen mit der Fähigkeit des vernetzten Denkens und Handelns und mit dem Blick für das große Ganze sind gefragt. Bisher wird der Mensch mit seinem Potential, trotz aller Beteuerungen, jedoch noch als „Human Ressource“ aber nicht wirklich als „Resourceful Human“ (in Anlehnung an Fischer, 2012) betrachtet. Der Übergang zum „Mensch im Mittelpunkt der Betrachtung“ setzt eine zukunftsfähige Innnovationskultur voraus, die ein grundlegend verändertes Verständnis der menschlichen Möglichkeiten und Bedürfnisse im Umgang mit Technologien, Arbeitssystemen und natürlichen Ressourcen aber auch den Menschen selbst benötigt. Weiterhin sind neue Modellierungs- und Interaktionsparadigmen, Technologielösungen sowie Arbeitskulturen gefragt, die den Wechsel der Blickrichtung zu Innovation durch „Resourceful Humans“ ermöglichen und somit maßgeblich zur effektiven und effizienten Teamarbeit in unternehmensübergreifenden und interkulturellen Unternehmenspartnerschaften beitragen.

Virtual environments are more and more used for educational and training purposes. In order to design virtual environments for these applications in particular, it is very important to get a deep understanding of the relevant design features supporting the user's process of learning and comprehension. Relevance and implementation of these features as well as the benefits of virtual learning environments over traditional educational approaches in general are rarely explored. Focusing on modes of interaction in this work, we examined the effect of different motion types on the knowledge acquisition of users in various virtual environments. For our study we chose a simple memorization task as approximation of low cognitive knowledge acquirement. We hypothesized motion types and immersion levels influence memorization performance in virtual environments. The memorization task was conducted in two virtual environments with different levels of immersion: A high-immersive Cave Automatic Virtual Environment (CAVE) and a low-immersive desktop virtual environment. Two motion types in virtual environments were explored: Physical and virtual walking. In the CAVE physical walking was implemented by using motion capturing and virtual walking was realized using a joystick-like input device. The results indicate neither motion types nor immersion levels in virtual environments affect memorization performance significantly.

Virtual engineering as a new working method in product development should make it much easier to validate the development progress and facilitate team communication. Work steps are brought forward and start with the virtual components instead of real ones. To validate mechanical and electrical CAD as well as programming, automated virtualization systems should create the virtual twin of the machine at the push of a button. For this purpose, generic intelligence is added to enable complex interactive virtual models that can be used for training, monitoring and many other applications. Advanced applications are for example training and support applications, especially in combination with augmented reality and remote collaboration. We propose a system that combines virtual reality, virtual engineering and artificial intelligence methods for the product development process. Geometry analysis algorithms are used to process mechanical CAD data and thus, for example, to automatically parameterize kinematic simulations. In combination with electrical CAD data and the simulations of electric circuits as well as the original machine program allow simulating the behavior of the machine and the user interaction with it. This article will describe the virtualization method in detail and present various use-cases in special machine construction. It will also propose a novel method to use causal discovery in complex machine simulations.