Eye-Tracking supported design of digital assistance systems for smart factories

Cognitive assistance systems enable people to receive valuable support in their industrial work tasks and can offer the highest flexibility and individualization possibilities. The increasing need for knowledge and its growing importance lead to a great demand for user-centric cognitive assistance systems. In this sense, eye-tracking is a potential technology to provide better insights in Use behavior in the task fulfillment process. The analysis of the data contributes to understand where the person is directing their attention, how long they are looking at certain areas and whether potentially unnecessary distractions exist. In this way, data-based adjustments can be specifically identified to be able to increase reliability and efficiency in the process. Eye-Tracking is rarely used in the development of assistance systems for the manufacturing industry. The expected benefit and the effort remain unclear. We show what potential it can offer in the development of cognitive assistance systems and present recommendations for its integration in the design process. The results are based on the empirical findings of a manual industrial application of complex quality measurement of battery module housings for electric vehicles.