Presently, digitalization is causing continuous transformation of industrial processes. However, it does pose challenges like spatially contextualizing data from industrial processes. There are various methods for calculating and delivering real-time location data. Indoor positioning systems (IPS) are one such method, used to locate objects and people within buildings. They have the potential to improve digital industrial processes, but they are currently underutilized. In addition, augmented reality (AR) is a critical technology in today’s digital industrial transformation. This article aims to investigate the use of IPS and AR in manufacturing, the methodologies and technologies employed, the issues and limitations encountered, and identify future research opportunities. This study concludes that, while there have been many studies on IPS and navigation AR, there has been a dearth of research efforts in combining the two. Furthermore, because controlled environments may not expose users to the practical issues they may face, more research in a real-world manufacturing environment is required to produce more reliable and sustainable results.

his study explores the impact of augmented reality (AR) on worker performance in manufacturing contexts through an analysis of case studies extant in the literature. Two specific analyses were conducted to assess the impacts of AR technologies on worker performance in terms of objective and subjective metrics, and in terms of their age, experience with the task and experience with the AR device. Regarding objective metrics, the results showed that the task completion time was reduced for some AR devices (projectors, monitors, tablets, smartphones), whereas the use of the head-mounted display (HMD) increased task-completion time; moreover, the error rate was reduced with any AR device compared with traditional methods. Regarding subjective metrics, the analysis underlined that operator perceived a lower workload with the HMD or the monitor compared with traditional methods. The age of operators did not influence performance, while the operators’ experience allowed for the improvement of human performance.