Today, teams in the mining industry are under relentless pressure to deliver elevated safety, performance, and productivity standards. While the turn of the 21st century introduced new processes and tools enabled by computers and the internet, a significant challenge still lay in the need to reference many disconnected data sources. A recent internal study found that users typically need to reference more than 7 systems in order to make critical decisions. This traditional workflow is inefficient, confusing, and frustrating. The industry needs a way to connect, analyze, and visualize data in order to communicate with the rest of the organization and make decisions quickly.
Organizations who are adopting digital transformation strategies to unify all of their asset data are leading the charge in remote asset management, predictive maintenance, and preparing for artificial intelligence/machine learning adoption.
Accelerating digital transformation
A collaborative visual digital twin application is an easy way to get started on any mining digital transformation journey. Connecting text-based data to 2D and 3D data adds visual context and collaborative tools to existing data search workflows. With the reduced cost of data capture in recent years, many organizations have been collecting reality scans of their facilities in an effort to deliver the site to the office. Elevating this data through a simple-to-use 3D viewer enables non-subject-matter experts to gain access to previously siloed data sets by integrating all systems to a single web-based application.
Enabling remote collaboration with operations and maintenance workflows
Remote collaboration is enabled through conversations on the virtual site. Exact locations of equipment, work orders, and points of interest can be shared with any user in the organization. By delivering the site to the office, collaborative digital twins reduce the need to travel to remote assets to confirm site conditions. Remote access to a virtual site also enables remote operations and improves maintenance workflows, resulting in optimized asset outcomes and a safer work environment, less time on site, productivity gains, and improved schedule certainty.
Future artificial intelligence (AI) and machine learning (ML) adoption
By aggregating, analyzing, and visualizing all mining asset data in a single application, organizations are effectively preparing for future AI/ML adoption, which requires all data to be organized in a common format. A digital twin is the perfect way to understand what information an organization has, what is missing, and what needs to be updated.
Read more about the use cases for digital twins in mining, including equipment optimization, asset management, safety, exploration and sustainability, and discover our premier digital twin for mining companies.
Interested in learning more about digital transformation? Download the full whitepaper here.