A low-cost AR training system for manual assembly operations
Traian Lavric, Emmanuel Bricard, Marius Preda, Titus Zaharia
Abstract
This research work proposes an AR training system adapted to industry, designed by considering key challenges identified during a long-term case study conducted in a boiler-manufacturing factory. The proposed system relies on lowcost visual assets (i.e., text, image, video, and predefined auxiliary content) and requires solely a head-mounted display (HMD) device (i.e., Hololens 2) for both authoring and training. We evaluate our proposal in a real-world use case by conducting a field study and two field experiments, involving 5 assembly workstations and 30 participants divided into 2 groups: (i) low-cost group (G-LA) and (ii) computeraided design (CAD)-based group (G-CAD). The most significant findings are as follows. The error rate of 2.2% reported by G-LA during the first assembly cycle (WEC) suggests that low-cost visual assets are sufficient for effectively delivering manual assembly expertise via AR to novice workers. Our comparative evaluation shows that CAD-based AR instructions lead to faster assembly (-7%, -18% and -24% over 3 assembly cycles) but persuade lower user attentiveness, eventually leading to higher error rates (+38% during the WEC). The overall decrease of the instructions reading time by 47% and by 35% in the 2nd and 3rd assembly cycles, respectively, suggest that participants become less dependent on the AR work instructions rapidly. By considering these findings, we question the worthiness of authoring CAD-based AR work instructions in similar industrial use cases.