Purpose-Owing to the numerous part models and massive datasets used in automobile assembly design, virtual assembly software cannot simulate a whole vehicle smoothly in real time. For this reason, implementing a new virtual assembly environment for massive complex datasets would be a significant achievement. The paper aims to focus on this problem. Design/methodology/ approach-A new system named "Grid-enabled collaborative virtual assembly environment" (GCVAE) is proposed in the paper, and it comprises three parts: a private grid-based support platform running on an inner network of enterprise; a service-based parallel rendering framework with a sort-last structure; and a multi-user collaborative virtual assembly environment. These components would aggregate the idle resources in an enterprise to support assembly simulation with a large complex scene of whole vehicle. Findings-The system prototype proposed in the paper has been implemented. The following simulations show that it can support a complex scene in a real-time mode by using existing hardware and software, and can promote the efficient usage of enterprise resources. Practical implications-Using the GCVAE, it is possible to aggregate the idle resources in an enterprise to run assembly simulations of a whole automobile with massively complex scenes, thus observably reducing fault occurrence rates in future manufacturing. Originality/value-The paper introduces a new grid-enabled methodology into research on collaborative virtual assembly system which can make the best use of idle resources in the enterprise to support assembly simulations with massively complex product models. A video-stream-based method was used to implement the system; this enables designers to participate ubiquitously in the simulation to evaluate the assembly of the whole automobile without hardware limitations. © Emerald Group Publishing Limited.
CITATION STYLE
Hu, Y., Wu, D., Fan, X., & Zhen, X. (2010). Grid-enabled collaborative virtual assembly environment. Assembly Automation, 30(4), 352–364. https://doi.org/10.1108/01445151011075816
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