Combining Simulation and Augmented Reality Methods for Enhanced Worker Assistance in Manual Assembly

Due to mass customization product variety increased steeply in the automotive industry, entailing the increment of worker's cognitive load during manual assembly tasks. Although worker assistance methods for cognitive automation already exist, they proof insufficient in terms of usability and achieved time saving. Given the rising importance of simulation towards autonomous production planning, a novel approach is proposed using human simulation data in context of worker assistance methods to alleviate cognitive load during manual assembly tasks. Within this paper, a new concept for augmented reality-based worker assistance is presented. Additionally, a comparative user study (N=24) was conducted with conventional worker assistance methods to evaluate a prototypical implementation of the concept. The results illustrate the enhancing opportunity of the novel approach to save cognitive abilities and to induce performance improvements. The implementation provided stable information presentation during the entire experiment. However, with regard to the recentness, there has to be carried out further developments and research, concerning performance adaptions and investigations of the effectiveness. (C) 2019 The Authors. Published by Elsevier Ltd.