Search

With Industry 4.0 manufacturing facilities experience a dynamic change towards smart factories. Digitalization of processes accompanied by extensive data acquisition enables process planners to utilize innovative technologies like Augmented Reality (AR) to support employees in their tasks on the shop floor. Among others a visualization in the user's field of view allows hands-free work and avoids unnecessary head movements. To make use of the employee's expertise, we try to involve workers with the aid of Design Thinking at an early stage in the AR-interface design process. A pervasive method in app design is Paper Prototyping. Early sketches of user interfaces serve as common language in interdisciplinary teams. In this paper we develop a method based on Paper Prototyping especially for AR content needs, which is called Photo Prototyping. This method overlays the user's field of view with sketches of the future AR-content. Furthermore we elucidate our experience, we've gained during a workshop with 40 workers out of logistics in the automotive industry.

Recently, there has been increased interest in eye tracking and eye-based human-computer interaction research, as gaze reveals attention and intention information, making it highly interesting as an input modality for cognitive assistant systems. In this paper, we present how to apply gaze-awareness in an industrial environment to create such a cognitive assistant system. A prototypical system was built upon a mobile eye tracker, that analyses the user's field of view, to recognize possible objects of interest, while simultaneously checking for gaze fixations. A twenty-one participants user study was carried out, which builds upon established hypothesis of a correlation between eye fixations and the relevance of objects and additionally shows that this relationship changes over multiple tasks and runs, revealing learning improvements and task difficulty. Both features are vital for a reduction of amount of the support an assistance system provides towards its users, resulting in an overall better user experience.

With the advancing digitalization of industrial production, the need for new man-machine interaction techniques, that go beyond traditional input and output systems, is arising. In this paper, we investigate the potential of gaze-only machine controls and its implications. In order to achieve that, a prototypical system is built upon a mobile eye tracker, that allows users to trigger binary actions and manipulate object states. To evaluate our approach, two user studies with 35 participants in total were conducted in controlled laboratory environments. A detailed comparison between physical and gaze-only interaction highlights significant improvements of interaction efficiency up from a certain distance and we further found that the distance to the objects had no significant effect on the task completion times for gaze-only interactions within the scope of the study. Finally, two placements of selection areas for advanced interactions, that go beyond binary, were evaluated in detail.

Order picking is a difficult and cognitively demanding task. Traditionally textual instructions are helping new workers to learn different picking routines. However, the textual instructions are sometimes not written in the workers ' native languages. In the area of Industry 4.0, where digital functions are finding their way into manufacturing processes, language-independent instructions are possible. Through a user study with 15 participants, we compare textual feedback in the workers' native language, textual feedback that is written in an unknown foreign language, and visual Augmented Reality (AR) feedback. We found that AR feedback is significantly faster and leads to a lower perceived cognitive load.