BIM for mining - Automated generation of information models using a parametric modelling concept

Abstract

Abstract

The adoption of Building Information Modelling (BIM) in construction has greatly improved project delivery, collaboration, and automation. However, its application in mining remains underdeveloped due to the unique challenges of mining projects, such as their vast scale, complexity, and heterogeneity. The present study aims to explore the characteristics and potential for adoption of BIM technology in the mining sector and focuses on the generation of a Mine Information Model (MIM) from raw mine data, addressing a critical gap in the current state of digital transformation in the mining industry. We designed a fully automated workflow employing parametric modelling to generate models of as-excavated underground tunnels and geological block models for mining, utilising analytical data from surrounding rock formations. Two case studies utilising real mine tunnel data from Finland were conducted to validate the proposed automated MIM generation workflow. The input raw data includes reality-captured raw data, such as point clouds or mesh models of tunnels, borehole information, and associated design files. Through the application of topology-based parametric objects and script-driven rules, MIMs can be effectively created for mining operations. This research offers significant potential for advancing the Mine Building Information Modelling (MineBIM) concept, supporting machine control, automation, and digital twin applications. As BIM adoption grows, innovative solutions are expected to improve efficiency, safety, and sustainability in mining. Our code for automating MineBIM modelling is available at: https://github.com/zxy239/MineBIM