A Low-Cost AR Training System for Manual Assembly Operations

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 low-cost 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 conduct-ing 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) computer-aided 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 deliver-ing 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, eventu-ally leading to higher error rates (+38% during the WEC). The overall decrease of the instructions reading time by 47% and by 35% in the 2^nd and 3^rd assembly cy-cles, 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.