As digital technologies transform how the mining industry works and mining operations inform their decision-making on data-driven insights, issues associated with data access and usage also become much more pressing. This group is a community of interest where mining stakeholders can collaborate to identify common practices in data management, develop data interoperability solutions and identify priorities and requirements associated with data access.
WHY IT IS IMPORTANT FOR THE MINING INDUSTRY
As new technologies and systems are adopted in the mining industry, they produce a wider range of data at more granular levels. The insights derived from these new data sources could be used for critical decision-making, forecasting, trend analysis and more.
However, making use of this data is complicated and challenging, as it involves searching, defining, labelling, cleaning, collecting, filtering and modelling large data sets to identify valuable insights. Data access challenges such data ownership and intellectual property concerns and issues with data interoperability further complicate the process.
Therefore, the right data needs to be available and collected and managed effectively throughout the entire end-to-end mine cycle to:
ABOUT THE WORKING GROUP
The Data Access & Usage Working Group aims to address industry challenges associated with data access and usage by identifying best practices for data management, collaborating on defining data access requirements and priorities, and developing data interoperability solutions. The group is made of community operators, equipment and technology suppliers, subject matter experts and leaders from inside and outside the industry who come together in a safe and collaborative space to pave the way forward for our industry.
With the goal of improving 3D Data interoperability, this project group has developed the Open Mining Format (OMF), an open-source file specification to support data interchange across the entire mining community. Learn more
GUIDELINE IN REVIEW – May 2020: The review period for A Standardized Time Classification Framework for Surface Mining is now closed and the final draft is circulating among GMG members within the Data Access and Usage Working Group to vote on publication. If you did not receive the vote information by email or are unsure about your company’s membership status, please contact us
MINING INDUSTRY SURVEY IN PROGRESS. GMG will be releasing a survey to gather insight about the needs of the industry in terms of data. Stay tuned!
This guideline offers recommendations for the consistent classification of surface mining operational activities, statuses, and events into standard time categories and provides a Time Usage Model, which is a visual representation of this framework. The guideline also includes recommended definitions for common industry operational key performance indicators (KPIs) for reporting asset availability and utilization. Click here to read.
This guideline aims to create a common industry vision for the seamless access and use of mobile equipment data across the mine cycle. It identifies onboard datasets that should be openly available to equipment owners in a real-time, read-only format. It also identifies an initial list of the open data elements for onboard mobile mining equipment. Click here to read.
Data and AI are better when they are together. Unfortunately most of today’s Internet of Things (IoT), including location tracking, sensing, and industrial control systems, are disparate systems designed and deployed for one-off applications. That means it is very challenging to aggregate and correlate the heterogeneous data from silo-ed IoT systems for real-time situational awareness and early warnings. This webinar will present the geospatial and IoT standards from the Open Geospatial Consortium (OGC). Click here to watch.
As a direct result of COVID-19 and resulting government health and safety restrictions in operating business, demand dynamics in manufacturing and construction coupled with proximity challenges in mining operations are impacting the mining industry’s ability to maintain operation stability. In this presentation four action areas will be proposed where mining’s leaders and operations need to remain focused and vigilant, and how the industry is responding in these areas. Click here to watch.
With the Forth Industrial Revolution upon us, mining companies are looking to other adjacent industries to see how they can apply technology to their own processes. Many mining companies have stated goals of digitally transforming their mining business. But how do they actually do this? We take a digital transformation journey of an African mining company to see how they have applied technology and where they see the real benefits for their operations. Presenter: David Osborn, Managing Director for Dassault Systemès South Africa. Click here to watch.
Digitalization in mining requires a common language for data exchange between mining machines and the higher-level systems. The webinar will walk through “Open Platform Communication Unified Architecture” (OPC UA), its key benefits and the approach to jointly develop an application-oriented Companion Specification Mining. Click here to watch.
Learn about GMG’s interoperability strategy: – Facilitate industry alignment on interoperability principles and priorities and the forms of commitment required to achieve it. – Develop a roadmap that outlines tangible actions and goals for achieving interoperability. – Work with and leverage the work of other organizations working on aspects of interoperability. This webinar covers what has been done so far, the ongoing work and the next steps for this strategy. Click here to watch.
Lisa Seacat DeLuca, Distinguished Engineer & Master Inventor at IBM AI Applications, presents about Digital Twin Innovation in the Mining Industry. Click here to watch.
Engineers and geologists are using digital twin technology to predict, simulate and optimise across the mine value chain. Unlike the manufacturing industry, inputs to the mine value chain include inherently variable ore, and therefore digital twins require the ability to model how ore variability affects processes across the value chain. Typically, these models have been empirical or physics based, but the advent of digital twin technology provides a link into the real-world operations and twins operational data to digital twin models using machine learning. Click here to watch
The presentation will outline how Siemens Digital Industries Software enables digitalization for the mining industry through focus applications and with holistic digital twins to drive yield. A case study on Komatsu Mining with a focus on predicting equipment systems performance and a second case study on layout planning and optimization for a new sand processing facility will also be presented. Finally, a demonstration on an underground mining plant simulation will be carried out as a conclusion to the session before moving on to Q&A. Click here to watch.