Authoring Tool for Automatic Generation of Augmented Reality Instruction Sequence for Manual Operations

Abstract

Despite the large-scale digitalization and automation of production lines, human operators still play a vital role in the shopfloor. Operators provide flexibility and agile responsiveness with their actions, as well as capability to react autonomously based on their technical knowledge and experience. Bridging the gap between modern digital systems of information creation and management and humans in the shopfloor is a current challenge for both the academia and the technology integrators. One emerging way for delivering instructions to the operators is Augmented Reality (AR). AR allows the visualization of the instructions in the operator's field of view, using digital designs, animations and text instructions. As this technology gains increasingly more ground in the shopfloor, there is a need for agile generation of content, automatizing most of the instructions' generation process. Towards that end, this paper presents an authoring tool for generating digital instructions for manual operations. The authoring tool allows the identification of the (dis-)assembly sequence of a product and also to include intermediate manual operations, such as surface treatment, and visualizations. In order to determine which assembly tasks and instructions are the most commonly needed, contextual inquiries were conducted in collaboration with the industry. These findings, together with the existing literature on manual processes on the shopfloor, served as a starting point for a taxonomy of assembly task types that are also presented in this paper. The taxonomy serves as a guide to define the processes on which digital instructions and visualizations can be provided. The result can be delivered as digital on-screen instructions or as an Augmented Reality application that may target mobile devices and headsets. The proposed approach is validated in an industrial use case of a compressor assembly.