Exploring the Potential of Head Worn Displays for Manual Work Tasks in Industrial Environments

Abstract: In this thesis I explore the potential of modern Head-Worn Displays for aiding manual work tasks in the manufacturing industries. In such settings, workers are already supported by using mobile hand-held devices that show instructions and enable the worker to document work tasks. However, the most important disadvantage of hand-held devices is that users need to put them aside when performing tasks that require both of their hands. The current generation of Head-Worn Displays promises hands-free usage with little added complexity and also enables the augmentation of workers’ vision,thereby supporting the work task in a more effective and efficient way.For assessing the potential of Head-Worn Displays on factory floors, a series of studies has been conducted. The studies have been carried out directly on the production line of a German car manufacturer together with workers or in-lab, depending on the study goals. Together with workers and managers in the industrial settings we identified two work tasks whereby support for Head-Worn Displays showed good potential for increasing productivity, quality and worker comfort. The Head-Worn Display support was improved in an iterative manner within a Human-Centred Design approach.The thesis contributes with experiences on introducing Head-Worn Displays in real world settings and for long time periods. The recorded productivity increases attributed to the Head-Worn Displays are discussed, along with worker and manager feedback. For long-term use on a factory floor, extending battery operating time was found to be of central importance. CPU and Camera were identified as the most energy consuming devices and an approach to address that is presented. A benchmark suite is introduced to enable designers, developers, and project managers to make informed decisions when selecting Head-Worn Displays. Finally, a theoretical discussion of Head-Worn Displays is presented by situating them in a sense-based Augmented Reality taxonomy, I proposed.