In: A. Holzinger, P. Kieseberg, A M. Tjoa, E. Weippl (Eds.): Machine Learning and Knowledge Extraction. Springer International Publishing, Cham, Switzerland, pp. 239 - 247, Springer

A Multi-Device Assistive System for Industrial Maintenance Operations

Mario Heinz-Jakobs , Hitesh Dhiman and Carsten Röcker,

Aug 2018

Recent advances in the field of industrial digitization and automation lead to an increasing need for assistance systems to support workers in various fields of activity, such as assembly, logistics and maintenance. Current assistance systems for the maintenance area are usually based on a single visualization technology. However, in our view, this is not practicable in terms of real activities, as these operations involve various subtasks for which different interaction concepts would be advantageous. Therefore, in this paper, we propose a concept for a multi-device assistive system, which combines multiple devices to provide workers with relevant information over different subtasks of a maintenance operation and present our first prototype for such a system.

Literature procurement: A. Holzinger, P. Kieseberg, A M. Tjoa, E. Weippl (Eds.): Machine Learning and Knowledge Extraction. Springer International Publishing, Cham, Switzerland, pp. 239 - 247, Springer

Doi: https://doi.org/10.1007/978-3-319-99740-7_16

Bibtex: Download Bibtex

@book{120,

author	=	{Heinz-Jakobs, Mario and Dhiman, Hitesh and Röcker, Carsten},
title	=	{A Multi-Device Assistive System for Industrial Maintenance Operations},
publisher	=	{Springer},
year	=	{2018},
volume	=	{},
series	=	{},
address	=	{},
edition	=	{},
month	=	{Aug},
note	=	{},
isbn	=	{},

}