Publications / 2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada

Application of Virtual Reality in Task Training in the Construction Manufacturing Industry

Regina Barkokebas, Chelsea Ritter, Val Sirbu, Xinming Li and Mohamed Al-Hussein
Pages 796-803 (2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada, ISBN 978-952-69524-0-6)

Automation in construction manufacturing is becoming increasingly common due to the drive for higher productivity and increased quality. One important consideration in the implementation of automation is the training and maintenance of the equipment. This study proposes an approach to assess the training for assembly/disassembly and maintenance of machines developed for the construction manufacturing industry by using immersive virtual reality (VR). The application of VR allows the collection of data such as the time required to complete the task, the distance travelled, the identification of ergonomic risks (e.g., awkward body posture), and the layout effectiveness, as well as the observation of multiple users performing an identical task under laboratory circumstances. Moreover, VR significantly reduces the costs associated with real mock-ups and the time required for implementation as it allows testing machine designs in a virtual environment that mimics the machine’s real operation setting. To demonstrate the proposed approach, a case study (i.e., VR experiment) is conducted. The primary objective of the case study is to use VR to assess the effectiveness of training using the VR environment for maintenance, and the complexity of the task (i.e., the amount of time needed to understand the task). The VR experiment is performed inside an office room dedicated exclusively for that purpose where participants can move freely, and interactions with the virtual environment are possible through the utilization of a headset and wireless controllers. During the experiment, information is collected both by manual observation and automatic extraction of data from the computer. Based on the analyses of the data collected, the average time to complete the task is determined, and potential areas of design improvement are identified.

Keywords: Virtual Reality; VR; Maintenance; Automation; Training; Construction; Manufacturing;